custom/1810/images/ACC Research Report
Transcription
custom/1810/images/ACC Research Report
Submitted to: Industry Canada Office of Consumer Affairs April 2013 Organization Automobile Consumer Coalition (Car Help Canada) 1110A Wilson Avenue #208 Toronto, Ontario M3M 1G7 Report title Classifieds Websites and Used Car Purchases in Canada: How Can We Better Protect Consumers? Report author Nicholas Maronese [email protected] Report methodologists Peter Silverman Thomas Prymak Report coordination Automobile Consumer Coalition i Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada This report is dedicated to the memory of Bob Beattie, formerly of the Used Car Dealers Association of Ontario, and his contributions to curbsider detection and prevention. The ACC would like to thank the Automobile Protection Association (APA) for its administrative support with this report. The Automobile Consumer Coalition received funding from Industry Canada’s Contributions Program for Non-profit Consumer and Voluntary Organisations. The views expressed in the report are not necessarily those of Industry Canada or the Government of Canada. The views expressed in this report are also not necessarily those of the ACC, unless explicitly stated; they instead belong to the persons quoted. ii Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada Table of Contents Summary Introduction Research goals Glossary of acronyms iv 1 2 3 Methodology Review of prior studies Stakeholder interviews Consumer survey 4 4 4 5 Car Sales Fraud on Canadian Classifieds Websites Fraud types and definitions Prevalence of fraud Current fraud prevention techniques 7 9 15 22 In Detail: Prevalence of Online Car Sales Fraud in Canada Consumer survey intent and methodology Consumer survey results and analysis Case studies and interviews 29 29 30 32 Recommendations 36 Conclusions 42 Appendix Research team Bibliography Stakeholder list Consumer survey questionnaire Consumer survey results Examples of fraud websites 43 44 46 48 50 54 96 iii Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada Summary Over the past few years, surveys have confirmed Canadians are among the world’s biggest Internet users, 1 which may explain why the Internet has, in fact, become one of the first places Canadians go to purchase a used car. 2 The used-car-for-sale classifieds listings that used to appear in the back of newspapers or other magazines have moved almost entirely online, to classifieds websites like eBay-owned Kijiji.ca or AutoTrader. Of the roughly three million used cars 3 Canadians buy and sell annually, as many as 600,000 4 trade hands via these websites, and the numbers are likely rising. That is in part because online classifieds make buying and selling used cars so much easier—the most popular sites let private sellers post their listings free of charge (dealerships are sometimes charged a fee), and buyers can often use a search engine built into the site to look for cars in a specific price or model year range, or of a specific make, model, engine and even colour. The internet has made the transaction process easier, too. Used car buyers can now pay a seller they have never met for a car they have never seen in person, in full, using their credit card or an online money transfer service like PayPal. The popularity and ease-of-use of these classifieds websites have also made them attractive to scammers. Fraudsters often try to rob people of their money by either: collecting a legitimate buyer’s cash via an online money transfer and then failing to deliver the car; or by overpaying a legitimate seller for a car, and asking them to return the excess funds—before the seller realizes the scammer’s money transfer did not come through. 5 Canadians also have to be mindful of “curbsiders”—full-time fraud artists with multiple vehicles who pose as private sellers online to circumvent provincial dealer regulations or unload cars with concealed damage. Between nine and 29 percent of all Ontario online classifieds listings are from curbsiders. 6,7 In April 2012, the Automobile Consumer Coalition (Car Help Canada) began looking into the state of online used car sales fraud and fraud prevention and what could be done about it. 1 http://www.comscore.com/Insights/Press_Releases/2013/3/comScore_Releases_the_2013_Canada_Digital_Future_in_Focus_ Report 2 http://www.comscore.com/Press_Events/Presentations_Whitepapers/2011/2010_Canada_Digital_Year_in_Review Also available via http://dwmw.files.wordpress.com/2011/03/comscore-2010-canada-digital-year-in-review.pdf 3 Dennis DesRosiers via Jeremy Cato, “Why used-car sales are booming in Canada.” Globe and Mail September 6, 2012 4 based on data from 2012 Angus Reid-ACC consumer survey 5 6 7 http://www.autotrader.ca/general/info/fraud_protection_tips.aspx http://www.ucda.ca/content/curbsider-research.aspx interview with Allen Atamer, LTAS Technologies, August 12, 2012 iv Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada Reviews of previous studies, along with interviews with the classifieds websites who host these listings and the provincial motor vehicle industry regulatory bodies tasked with combating curbsiding, uncovered several types of online car sales fraud and fraud prevention techniques. Classifieds websites often use a set of filters to weed out fraudulent listings before they are posted, but also let users report suspicious activity or posts that may be scams. Curbsiders are tracked down by investigators from regulatory bodies like the Ontario Motor Vehicle Industry Council (OMVIC), the Vehicle Sales Authority of B.C. (VSA) or the Office de la Protection du Consommateur of Quebec (OPC), who comb classifieds websites looking for multiple car listings with the same phone number or user attached to them—potential curbsiders. Classifieds websites tend to work with police whenever possible in tracking down and criminally prosecuting fraudsters. Provincial regulators are the ones often tasked with investigating and laying charges on curbsiders when appropriate, though their specific methods and approaches can vary greatly province-to-province. Both the websites and the regulators frequently run awareness campaigns informing users of characteristics common to fraudulent or curbsider-posted listings, sometimes with additional tips on how to avoid getting scammed. Despite these efforts, every year thousands of Canadians car shoppers are still scammed out of thousands of dollars each. The RCMP’s Canadian Anti-Fraud Centre catalogued more than 1,300 online car sale scams in 2012, though, because of the social stigma attached to “falling for” online scams, such crimes are almost certainly underreported, and the CAFC’s number likely makes up only a small percent of the actual total. 8 Based on complaints to the CAFC, Canadian consumers are directly defrauded of at least $1.17 million annually9—though because those complaints may represent as few as one percent of the total actual crimes committed, the economic impact may actually be as high as $117 million. Experts estimate curbsiders dodge close to $300 million in taxes every year. 10 Beginning in the fall of 2012, several Canadian car buyers were defrauded a total of more than $225,000 11 in a scheme perpetrated by scammers allegedly from the U.S. 12 The gimmick involved making up a fake premium used car dealership website full of high-end vehicles, with details and images swiped from legitimate dealer sites; linking it to listings posted on popular Canadian classifieds websites; and then asking the potential buyer for a hefty down payment so that they could get it across the border. 8 interview with Daniel Williams, Canadian Anti-Fraud Centre, November 3, 2012 email correspondence with Daniel Williams, Canadian Anti-Fraud Centre, March 25, 2013 10 Bob Beattie via Mark Toljagic, “Curbsiding: Unsafe at Any Price.” Toronto Star April 9, 2011 11 email correspondence with John Cobb, Oklahoma Used Motor Vehicle and Parts Authority, December 18, 2012 12 http://www.omvic.on.ca/news/releases/news_release_2013-01-08.htm 9 v Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada Authorities acknowledge the scammers likely targeted Canadians because they knew the interjurisdictional nature of the crime would make it harder for investigators in both countries to pursue and prosecute them. 13 As part of their research, the Automobile Consumer Coalition commissioned Angus Reid Public Opinion to conduct a survey of Canadian used car shoppers to gauge how prevalent online car sales fraud and curbsiding were. Results showed roughly one in five online used car buyers or sellers encounter at least one instance of fraud while looking for, or looking to sell, a vehicle. 14 One of the most common scams respondents reported running into was fraudulent buyers offering to buy their for-sale car; suspected curbsider listings were also common. A vast majority browsed – and ended up buying or selling their car on – Kijiji, with AutoTrader being the second most used. Most respondents said they were not worried about online fraud, and 64 percent said they did little or no research into fraud types before they started car shopping online. Fraudsters and curbsiders may be continuing to target Canadians in part because of how relatively difficult – as well as time- and labour-intensive – it is for provincial regulatory bodies and authorities to convict and prosecute fraudsters and curbsiders, and how easy it is for scammers to elude them. However, both the websites and regulators are improving their fraud detection and prevention systems; and working on bettering fraud awareness amongst the car-buying Canadian public. More specifically, new technologies are making it easier to detect fraudsters, especially curbsiders; and websites, regulators and other stakeholders are realizing new ways in which they can work together to prevent fraud. Based on the findings of their report, the Automobile Consumer Coalition is recommending regulators and websites pursue these new curbsider detection technologies; that the provinces reevaluate the ways they penalize curbsiders; and that the websites more often work together, and with regulators, to detect and track fraudsters and curbsiders. They also recommend websites and regulators tweak their consumer-targeted fraud awareness campaigns so that the possible stigma attached to being a victim of online sales fraud is downplayed. Finally, the Coalition encourages the provincial governments to work with the federal government to consider entrusting oversight of online used car sales fraud to an organization with inter-provincial authority. By its nature online fraud transcends provincial and even national borders, and combating this sort of fraud will require cooperation between not just jurisdictions, but between countries. 15 13 interview with Terry O’Keefe, Ontario Motor Vehicle Industry Council, December 14, 2012 14 2012 Angus Reid-ACC consumer survey interview with Terry O’Keefe, Ontario Motor Vehicle Industry Council, December 14, 2012 15 vi Introduction Since the fall of 2012, at least five 16, and likely many more, 17 Canadian car buyers have been defrauded a total of more than $225,000 18 in a new sort of online scam. The gimmick involves making up a fake premium used car dealership website full of high-end vehicles, with details and images swiped from legitimate dealer sites, and linking it to listings posted on popular Canadian classifieds websites. Users interested in the steeply discounted vehicle contact the “sales manager” of the fake dealership – allegedly located in Oklahoma, Texas or Arizona, though the website’s hosted in California – who assures them they will handle shipping of the vehicle and that a pre-purchase inspection is not necessary. The user hands over their credit card information or wires the fake dealership a money transfer of a few thousand dollars to a bank in Georgia – or, in one case, as much as $115,000 – but never winds up seeing the car. “This was the first time we’ve seen [a scam] this elaborate. The websites looked very good, lots of testimonials, they tried to answer all the concerns that anyone might have,” says Terry O’Keefe, Manager of Communications with the Ontario Motor Vehicle Industry Council (OMVIC). “But within two days of our story hitting the news [that the dealership is fake], the phone numbers for Ambient Auto Center [one of the fake dealership’s names, along with Sprint Luxury Autos, Shine Auto Sales and at least four others] went dead and the website went down. Shining a bright light on Ambient certainly made them move on. Do I think they’re gone? Absolutely not. They’ll just pop up again with a new website and a new name.” O’Keefe says the likely U.S.-based scammers are probably targeting Canadians because they know the inter-jurisdictional nature of the crime makes it harder for investigators on both sides of the border to pursue and prosecute them. It is a tactic that takes full advantage of the burgeoning online used car market. “I don’t see this trend ending. I think technology is making it easier and easier for people who want to harm others through fraud to do it,” says O’Keefe. “It’s going to be a growing problem.” Online scams like this, perpetrated by criminals both in Canada and abroad, happen every day on dozens of Canadian classifieds websites like Kijiji.ca, Craigslist, AutoTrader and Wheels.ca. The RCMP’s Canadian Anti-Fraud Centre catalogued more than 1,300 online car sale scams in 2012—roughly 1,174 scams by suspect sellers and 167 by suspect buyers. Acts of curbsiding – of car dealers posing as private sellers in order to circumvent provincial regulations or offload a vehicle unfit for sale – are likely even more prevalent. Experts estimate 16 http://www.omvic.on.ca/news/releases/news_release_2013-01-08.htm http://www.bbb.org/blog/2012/09/original-luxury-autos-a-possible-scam/ 18 email correspondence with John Cobb, Oklahoma Used Motor Vehicle and Parts Authority, December 18, 2012 17 1 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada that between nine and 29 percent 19,20 of online private used car listings in Ontario are posted by curbsiders. While both the classifieds websites and the car dealership regulators in each province try to keep fraudsters and curbsiders, respectively, in check by finding them, shutting them down and, if possible, prosecuting them under franchise or criminal law, some scammers inevitably slip through the cracks. That is why both the websites and regulators are constantly waging consumer awareness campaigns giving car buyers tips on recognizing and avoiding scammers and curbsiders online. The success of these campaigns can sometimes be nullified by conflicting advice from different parties; or, more often, by the consumer’s assumption they could never be taken in by a scam, that “it could never happen to me.” In short, despite the fraud prevention efforts of both the industry and governmental regulatory bodies, online used car sales fraud still exacts an untold amount of damages on the Canadian economy. Used car buyers browsing online classifieds sites are in desperate need of better consumer protection measures. Research goals The Automobile Consumer Coalition began research into online used car sales fraud in early 2012 with several distinct goals in mind. Specifically, the ACC aimed to: • • • • • 19 20 define and catalogue the varieties of online used car sales fraud affecting Canadians; determine how prevalent online used car sales fraud is in Canada; review classifieds websites’ and provincial dealer regulators’ current online used car sales fraud prevention efforts; draft a set of recommendations governmental or industry bodies could pursue to better the efficacy of their fraud prevention efforts; and analyze the effect the implementation of these recommendations would have on Canadian consumers, industry stakeholders and governments. interview with Allen Atamer, LTAS Technologies, August 19, 2012 interview with Bob Beattie, Used Car Dealers Association Ontario, October 5, 2012 2 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada Glossary of acronyms ACC AMVIC APA API BBB CAFC CAPTCHA CRA FAQ FBI IBC IC3 ICBC ID IP address NMVTIS NW3C OMVIC OPC OUMVPA RCMP UCDA VIN VSA VSTAG Automobile Consumer Coalition (also known as Car Help Canada) Alberta Motor Vehicle Industry Council Automobile Protection Association application programming interface Better Business Bureau Canadian Anti-Fraud Centre (RCMP-affiliated; formerly PhoneBusters) completely automated public Turing test to tell computers and humans apart Canada Revenue Agency frequently asked questions Federal Bureau of Investigation (U.S.) Insurance Bureau of Canada Internet Crime Complaint Centre (FBI-affiliated; U.S.) Insurance Corporation of British Columbia identification internet protocol address (used to identify a computer’s location) National Motor Vehicle Titling Information System (U.S.) National White Collar Crime Center (FBI-affiliated; U.S.) Ontario Motor Vehicle Industry Council Office de la Protection du Consommateur of Quebec Oklahoma Used Motor Vehicle and Parts Authority Royal Canadian Mounted Police Used Car Dealers Association (Ontario, Canada) vehicle identification number Motor Vehicle Sales Authority of British Columbia Vehicle Safe Trading Advisory Group (U.K.) 3 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada Methodology Research was conducted in three different ways: 1) via a review of previously published studies on the topic; 2) via interviews with stakeholders (including various Canadian classifieds websites; fraud prevention experts; and representatives of the used car industry and associated regulatory bodies); and 3) via a widely distributed consumer survey coordinated by the Automobile Consumer Coalition and Angus Reid Public Opinion. A pair of ACC-affiliate methodologists were tapped to help coordinate the research-gathering process, and the report was reviewed by select stakeholders prior to the composition of a final draft. Review of prior studies Research began with a search for any and all previously published studies, reports and scholarly articles on or related to online used car sales fraud. (Though the ACC decided early on to focus on fraud perpetrated on classifieds websites, this search was broad enough to include studies and articles on fraud perpetrated on online auctions.) Materials not directly relevant to the topic were filtered out. Mainstream media articles – from newspapers, periodicals and websites – were also collected, filtered and sorted (see the appendix for a bibliography). Note: while the ACC came across a large swath of mainstream media articles on online used car sales fraud – most of these were largely repetitive tips-lists on how to detect and avoid fraudsters – there were few publically available studies and scholarly articles on the issue, especially recently published, current materials (less than five years old) or materials specific to a Canadian context. (The quickly changing nature of online fraud means it does not take long for studies or scholarly articles on the topic to fall out-of-date and thus lose relevance.) The materials the ACC found more often dealt with other types of online fraud, or “offline” used car sales fraud, or online used car sales fraud outside of a Canadian context. The need for a formal study relating specifically to online used car sales fraud on Canadian classifieds websites was apparent. Stakeholder interviews 4 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada A list of stakeholders was compiled, and telephone, email and in-person interviews were conducted over several months. The list included representatives from the most popular Canadian classifieds websites; fraud prevention experts; industry analysts; and representatives from the used car industry and associated regulatory bodies. More specifically, for classifieds websites, the ACC contacted Kijiji.ca Autos, a Canadian market-specific subsidiary of eBay International Inc. and the most popular vehicle classifieds website in the country; and AutoTrader.ca, a subsidiary of Trader Corporation. The ACC was unable to reach a representative of popular classifieds website Craigslist.ca despite repeated attempts. Experts and industry analysts contacted included the RCMP-affiliated Canada Anti-Fraud Centre; curbsider detection software developer Allen Atamer of LTAS Technologies; and the FBI-affiliated Internet Crime Complaint Center. Used car regulatory body representatives contacted included investigators from the Motor Vehicles Sales Authority of B.C. (VSA); the Alberta Motor Vehicle Industry Council (AMVIC); the Ontario Motor Vehicle Industry Council (OMVIC); the Used Car Dealers Association of Ontario (UCDA); and the Office de la Protection du Consommateur (OPC) of Quebec. Note: the ACC has decided to omit from this report some of the information collected in these stakeholder interviews to stop it from being abused by fraudsters or curbsiders. Sensitive information regarding the specifics of current and future fraud prevention techniques, for example, has been withheld. Please contact the report author or relevant stakeholder-party to discuss access to this information. Consumer survey The ACC commissioned market research firm Angus Reid Public Opinion to conduct a consumer survey in mid-November 2012. The survey was filled out by 1,006 Canadian adults (Angus Reid Forum panellists) who had purchased or sold a vehicle online via a classifieds website within the past year. The ACC-drafted survey questionnaire included questions on consumers’ perceptions of online used car sales fraud; which particular websites they most frequented while shopping for or trying to sell a used car; and how often they encountered fraud while shopping or selling. (Angus Reid was able to break out the information collected along several different demographic lines, including age, education, location and income.) The survey questionnaire also asked if respondents would be willing to volunteer for telephone interviews on their experiences shopping online for used cars (it was noted their personal information would be kept confidential). These interviews were used as case studies of Canadian consumers’ personal encounters with fraud. 5 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada For more information on the ACC-Angus Reid consumer survey, see the In Detail: Prevalence of Online Car Sales Fraud in Canada section of this report. 6 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada Car Sales Fraud on Canadian Classifieds Websites Over the past few years, surveys have confirmed Canadians are among the world’s biggest Internet users, which may explain why the Internet has, in fact, become one of the first places Canadians go to purchase a used car. 21 The used-car-for-sale classifieds listings that used to appear in the back of newspapers or other magazines have moved almost entirely online, to classifieds websites like eBay-owned Kijiji.ca or AutoTrader. Of the roughly three million used cars 22 Canadians buy and sell annually, as many as 600,000 23 trade hands via these websites, and the numbers are likely rising. That is in part because online classifieds make buying and selling used cars so much easier—the most popular sites let private sellers post their listings free of charge (dealerships are sometimes charged a fee), and buyers can often use a search engine built into the site to look for cars in a specific price or model year range, or of a specific make, model, engine and even colour. The internet has made the transaction process easier, too. Used car buyers can now pay a seller they have never met for a car they have never seen in person, in full, using their credit card or an online money transfer service like PayPal. The popularity and ease-of-use of these classifieds websites have also made them attractive to scammers. Fraudsters often try to rob people of their money by either: collecting a legitimate buyer’s cash and then failing to deliver the car; or by overpaying a legitimate seller for a car, and asking them to return the excess funds—before the seller realizes the scammer’s money transfer did not come through. 24 Canadians also have to be mindful of “curbsiders”— full-time fraud artists with multiple vehicles who pose as private sellers online to circumvent provincial regulations or unload cars with concealed damage. Roughly 95 percent of curbsiders operate via the internet (as opposed to newspaper or magazine classifieds) according to Bob Beattie, formerly of the Used Car Dealers Association. 25 “The fundamental reason that the online market is more convenient for opportunistic behaviors” – acts of fraud – “is the separation of product and information,” explains Byungtae Lee of Korea’s Advanced Institute of Science and Technology. “Online buyers are greatly dependent on information provided by the seller, which makes it easier for the seller to deceive them. Opportunistic behaviors are initiated by this information asymmetry.” 26 21 http://www.comscore.com/Press_Events/Presentations_Whitepapers/2011/2010_Canada_Digital_Year_in_Review Also available via http://dwmw.files.wordpress.com/2011/03/comscore-2010-canada-digital-year-in-review.pdf 22 Dennis DesRosiers via Jeremy Cato, “Why used-car sales are booming in Canada.” Globe and Mail September 6, 2012 23 24 25 based on data from 2012 Angus Reid-ACC consumer survey http://www.autotrader.ca/general/info/fraud_protection_tips.aspx interview with Bob Beattie, Used Car Dealers Association Ontario, October 5, 2012 Byungtae Lee et al, “Empirical Analysis of Online Auction Fraud: Credit Card Phantom Transactions.” Expert Systems with Applications 37 (2010): 2992 26 7 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada Despite efforts on the part of both the classifieds websites and governmental bodies to correct this asymmetry, acts of fraud are committed against Canadian used car buyers and sellers on a regular basis. Experts estimate Canadian consumers are directly defrauded of as much as $117 million annually, 27 and that curbsiders dodge some $300 million in taxes every year. 28 The more popular a classifieds website is, the more likely fraudsters and curbsiders are to target it. There are dozens of Canadian classifieds websites, but the most widely used ones include Kijiji.ca; AutoTrader; Craigslist; and LesPAC. The largest by far is Kijiji.ca, the Canadian-market-specific classifieds site run by Amsterdambased Marktplaats, which is owned by California-based eBay. Since its launch seven years ago, in 2005, Kijiji.ca has grown to become the number one free online classifieds site in Canada. 29 “Eleven million people use the site on a monthly basis, over forty percent of the Internet population in Canada,” says Christian Jasserand, Head of Customer Support for Kijiji Canada. “As a matter of fact, Kijiji is in the top ten most-visited sites in Canada every month, in the same league as Facebook or YouTube or Hotmail or Gmail.” With 792 new auto listings posted to their autos.kijiji.ca pages every hour, 30 they are also the number one used car classifieds site in Canada, five times bigger than their closest competitor, AutoTrader. 31 AutoTrader.ca is also frequented by millions of visitors monthly; 32 the Etobicoke, Ontario-based Trader Corporation-owned site regularly boasts around 380,000 listings across Canada. 33 Numbers on California-based craigslist.ca are harder to come by (the website has a reputation for being slow to providing feedback to customer or media inquiries, when they do at all). 34 But it is safe to assume craigslist – of which eBay owns a 25-percent share – is the third largest automotive classifieds site in Canada. 35 Mediagrif-owned LesPAC operates exclusively in Quebec. The classifieds site is the secondlargest in that province, after Kijiji, and just ahead of Craigslist. 36 27 email correspondence with Daniel Williams, Canadian Anti-Fraud Centre, March 25, 2013 Bob Beattie via Mark Toljagic, “Curbsiding: Unsafe at Any Price.” Toronto Star April 9, 2011 29 interview with Christian Jasserand, Kijiji Canada, October 29, 2012 30 http://kijijiblog.ca/about-us/ 31 interview with Christian Jasserand, Kijiji Canada, October 29, 2012 32 http://www.dealersmartsolutions.ca/products/autotrader/index.aspx#.UQa7kGckTgZ 33 interview with Ian MacDonald, AutoTrader.ca, November 14, 2012 34 interview with Christian Jasserand, Kijiji Canada, October 29, 2012 35 based on data from 2012 Angus Reid-ACC consumer survey 36 interview with Christian Jasserand, Kijiji Canada, October 29, 2012 28 8 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada Fraud types and definitions There are a number of different types of fraud, but for the purposes of this report, we have broken them into three categories: fraud against car buyers; fraud against car sellers; and curbsiding. Fraud against buyers Fraud against legitimate buyers by bogus sellers often fits into one of two types: scams in which the seller has a vehicle to sell, but misrepresents it somehow or otherwise defrauds the buyer of his money; or scams in which the seller does not actually have a vehicle to sell, but convinces the buyer he does in order to defraud the buyer of his money. The latter – sometimes referred to as a “419 scam” or “Nigerian scam,” because of the unusually high rates of this sort of fraud that once came out of that country, and because 419 is the chapter of the Nigerian criminal code dealing with fraud 37 – is one of the most common types of fraud on used car classifieds websites. The fraudulent listing, sometimes posted to multiple classifieds sites at the same time, is typically of a popular car – to gain visibility on the site – with a below-market-value asking price—to lure in as many prospective buyers as possible. The images attached to the listing are often swiped from other legitimate sellers or dealerships advertising on other websites. Though the listing may have a phone number attached to it, it is typically not the scammer’s actual number, if it is a working number at all. Most fraudsters’ preferred method of communication, however, is via email. 38 “Usually the story is that they’re selling low. You’re buying a $20,000 vehicle for $5,000,” explains Daniel Williams, Media Relations with the RCMP-affiliated Canadian Anti-Fraud Centre, formerly known as PhoneBusters. “One of the top reasons you hear is it’s a lady, and she got the car in a divorce and she doesn’t drive. It’s usually a good story, especially if you want to believe it.” 39 Once the fraudster has established contact with a prospective buyer, he or she will explain why they are unable to meet so that the buyer can view the car in person—typically either the vehicle or the seller is out of the province or country, the fraudster will explain, even if the listing said otherwise. “Scammers typically have a very convincing story for not being able to meet in person—for example, because they work for the military and have just been posted to a faraway locale; or they’re in the middle of a divorce, and they’ve got the car in the divorce, but they don’t 37 interview with Allen Atamer, LTAS Technologies, August 19, 2012 Mark Toljagic, “Taken for a Ride.” Toronto Star October 10, 2009 39 interview with Daniel Williams, Canadian Anti-Fraud Centre, November 3, 2012 38 9 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada drive, and they’ve flown home [to another country] so they can’t meet you,” says Kijiji’s Jasserand. 40 Some fraudsters try to calm buyer’s concerns by offering to ship the vehicle to the buyer’s location for inspection free of charge; again, they will usually have a semi-plausible explanation for why they are able to do this—they have a family member in the transport business, for example. 41 The fraudster may offer the buyer a means to safeguard their monies during the transaction, to further pacify any worries the buyer might have. These safeguards are, of course, also part of the scam, and do not work. “They may send documentation that mimics the eBay design, and allege that eBay will hold the money during the car’s shipping,” says Jasserand. “The idea is to leverage the good name of eBay – eBay is a reputable company – to lure people into thinking this is a legitimate transaction when in fact it’s not.” 42 (It is possible, for example, for fraudsters to use “email spoofing” to send an email that appears to be from an email address affiliated with the “eBay Vehicle Protection Program,” when it is in fact not.) 43 Most fraudsters will insist on a down payment – typically a fraction of the total asking price, with the full amount due on delivery, but sometimes the total asking price – made via a wire transfer like Western Union or MoneyGram, as opposed to a more secure method such as PayPal that “securely links financial information between registered buyers and sellers.” 44 “Once the fraud artist has the 10-digit money transfer number, he or she can walk into any Western Union office in the world and collect the untraceable cash while the buyer is left waiting for a vehicle that never arrives,” writes journalist Mark Toljagic in an article on used car sales fraud for the Toronto Star newspaper. 45 Even if the fraudster has failed to extract any monies from the buyer-victim, he or she may still be able to make use of the buyer’s personal information, collected during the transaction. (Fraudsters may sometimes ask for specific details – addresses, bank numbers, etc. – under the guise the information is required to complete some piece of necessary paperwork.) He or she may be able to sell this information on the black market, where it can be used to enact various forms of identity theft fraud, or he or she may use the information himself when perpetrating future frauds. There are many variations on this type of fraud – some scammers, for example, will trade specifically in fraudulent listings for classic cars 46 – but most follow the template steps above. 40 interview with Christian Jasserand, Kijiji Canada, October 29, 2012 interview with Daniel Williams, Canadian Anti-Fraud Centre, November 3, 2012 42 interview with Christian Jasserand, Kijiji Canada, October 29, 2012 43 “Financial Crime Trend Bulletin: eBay Brand Fraud and Online Vehicle Sales Frauds,” Canadian Anti-Fraud Centre, May 29, 2012 44 Mark Toljagic, “Taken for a Ride.” Toronto Star October 10, 2009 45 ibid. 46 “B.C. Man Arrested in Internet Vintage Car Scam.” Postmedia News August 6, 2008 41 10 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada In late 2012, several Canadians were victimized in a similar sort of scam that involved linking fraudulent listings together via a website for a fake U.S.-based luxury vehicle dealership. The phony website changed names and addresses several times as news of its falsity was broken by mainstream media. These apparently U.S.-based fraudsters would specifically target Canadian classifieds websites, likely in an effort to tie up U.S. and Canadian authorities’ investigations with inter-jurisdictional red tape. “This was the first time we’ve seen [a scam] this elaborate, and this was a sophisticated scam. The websites looked very good, lots of testimonials, they tried to answer all the questions that anyone that has concerns might have,” explains OMVIC’s Terry O’Keefe. “They provide you with the VIN [vehicle identification number] for the car—[the car] just happens to not be in their possession, actually. They’ll provide you with a CARFAX report, so they’ve got some very sophisticated methodology that they’re using to try to rip off Canadian consumers, down to the point of allegedly creating phony emails from Canada border services agency.” 47 For more information on this recent fake dealership scam, see the In Detail: Prevalence of Online Car Sales Fraud in Canada section of this report. Scams in which the fraudster-seller actually has a vehicle, but misrepresents it or otherwise defrauds the buyer of money, are less common, but do occur. These typically involve selling a legitimate buyer a car without allowing them a pre-purchase inspection – as with a “Nigerian scam,” the fraudster will often have a plausible-sounding explanation for why he is unable to meet in person – and completing the transaction before the buyer realizes the car is not at all as it appeared in the listing (the vehicle’s condition may be poorer than advertised, there may be undisclosed flaws, etc.) These fraudsters, too, will sometimes try to entice buyers with free or reduced-cost shipping of the vehicle. Fraud against sellers Fraud against legitimate sellers by bogus buyers often fits into one of two types: scams in which the buyer intends to defraud the seller of both his vehicle and his money; or scams in which the buyer intends to defraud the seller solely of his money. The latter is becoming more common as classifieds websites erect more and more safeguards to protect legitimate buyers from fraudulent sellers. In this scam, a legitimate seller will be contacted by a fraudulent buyer via email with an offer to buy his vehicle. The buyer will explain why he is unable to view, inspect or pay for the vehicle in-person – typically the buyer is out of the province or country – but is nevertheless interested in purchasing the vehicle, and quickly. 47 interview with Terry O’Keefe, Ontario Motor Vehicle Industry Council, December 14, 2012 11 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada The bogus buyer will send the seller the money for the vehicle via what appears to be a legitimate method of payment – an imitation of a payment notice from a secure money transfer website like PayPal – along with some additional money sent apparently either by accident or to pay for shipping, or for some similar reason. The bogus buyer asks the seller to refund the surplus funds via credit card or money transfer; after that refund transaction is complete, the buyer will find out the initial sum the bogus buyer sent never actually cleared, because the payment notice was a forgery. 48,49 “The suspect who’s doing the buying is, of course, out-of-town and can’t come and pay for [your $4,000 car] in person. He asks [via email] ‘Would you accept a payment by PayPal?’ and you say, ‘Sure, PayPal is reputable, that sounds great,’” the Anti-Fraud Centre’s Williams offers an example. “And then the suspect sends you a fake email from what looks like PayPal saying the $4,000 has been taken from the buyer’s account, as well as an additional $1,500 which is for paying the shipper, and so $5,500 has been delivered to the seller.” “Before that [legitimate seller] gets that $5,500, they have to send $1,500 by Western Union to the shipper for whatever reason—the only way they’ll accept payment is by Western Union or something, they give a wonderful rationale why it has to work this way. And the victim is seeing what looks like a real $5,500 coming to them from PayPal, so of course they think all is well and good, everything is backed up. The victim sends off the $1,500 and of course, when they look in their PayPal account, there’s no $5,500. They usually realize it’s a scam when they contact PayPal and say, ‘What gives? You said I was getting $5,500,’ and PayPal gets back to them in fifteen minutes saying, ‘That wasn’t us, that was a false email address. It may have said PayPal, but that wasn’t PayPal.’” 50 These sorts of scammers typically use an application programming interface (API) to automatically send out the exact same message to the posted email addresses of almost every seller with a listing on a website, instead of targeting specific victims by contacting them manually. This increases the fraudster’s chances, of course, of finding a victim. 51 Scams in which the fraudster-buyer defrauds the seller of his money and his car are less common, but do occur. These typically involve buying a car from a legitimate seller without a pre-purchase inspection – as with the other type of fraud-against-sellers, the fraudster will often have a plausible-sounding explanation for why he is unable to meet in person – and having someone pick up the car before the seller realizes the transaction has not cleared. “What it amounts to is a kind of reverse scam, one where you as the legitimate seller are offered more money than your asking price, just to close the deal quickly,” writes the Toronto Star’s Toljagic. “A cashier’s cheque arrives by courier, which your bank will accept at first glance. 48 Mark Toljagic, “Taken for a Ride.” Toronto Star October 10, 2009 interview with Daniel Williams, Canadian Anti-Fraud Centre, November 3, 2012 50 ibid. 51 interview with Ian MacDonald, AutoTrader Canada, November 14, 2012 49 12 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada But the draft actually takes four to six weeks to clear if it originated overseas (and many of them do), long after your vehicle has been picked up. Ultimately, you learn the bank draft is a counterfeit and you're on the hook for the full amount — which is recouped by the bank.” 52 Curbsiding “Curbsiding” is likely more common on Canadian classifieds websites than outright fraud. A “curbsider,” also called a “curber” or “curbstoner,” is basically a fraud artists operating as an unlicensed used car dealer posing but as a private seller on a classifieds site. Curbsiders like to operate outside provincial regulations so that they can sell off vehicles with salvage titles (that is, vehicles branded not roadworthy by provincial authorities); vehicles with an undisclosed history of significant damage; or vehicles with liens still on them (that is, vehicles with outstanding loan payments on them that technically belong to the loan-issuing bank). “Curbsiders disguise themselves as individual sellers or private people that are selling their own car or a relative’s car, but what they are is an illegal and unlicensed dealer who buy cars, usually from salvage yards, patch them up and sell them to consumers, so consumers are not getting what they’re paying for,” says OMVIC Director of Investigations Carey Smith. “OMVIC enforces the Motor Vehicle Dealer Act, and of course [the Act] requires if you’re going to sell cars in Ontario other than your own, you have to be licensed by us, and curbsiders are not, they’re hiding in the bushes.” 53 More specifically, Bob Beattie, former Executive Director of Ontario’s Used Car Dealers Association, defines curbsiding as “essentially the private sale of two or more different vehicles being advertised by the same telephone number or ID within a ninety-day period.” “Any private individual has the right to sell their own car privately, they don’t have to be a car dealer to sell their own car. And there are instances where individuals – certainly a couple oftentimes – might sell two cars. They might even sell them at the same time,” Beattie says. “But anyone advertising more than two – getting into two, three, four, five – within a three-month period is pretty obviously in business to some degree, and it’s only a question of to what degree.” 54 Curbsiding is considered illegal because of the deception involved; in Ontario, curbsiding specifically contravenes the Motor Vehicle Dealer’s Act, which requires a dealership or dealer includes its or his name in any sort of advertisement. 55 Similar regulations apply in most other Canadian provinces. The curbsider listing often lures in prospective buyers with a below-market-value asking price. Though the listing may have a phone number attached to it, this is not always the scammer’s 52 Mark Toljagic, “Taken for a Ride.” Toronto Star October 10, 2009 interview with Carey Smith, Ontario Motor Vehicle Industry Council, October 3, 2012 54 interview with Bob Beattie, Used Car Dealers Association Ontario, October 5, 2012 55 ibid. 53 13 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada actual number; the curbsider often takes advantage of the anonymity of the internet to obscure their true identity. Once the curbsider has established contact with a prospective buyer, he will explain why he is selling the vehicle for a lower-than-average price, and try to answer any other questions the buyer may have; the answers are of course fabrications. If the buyer is still interested, the curbsider will likely insist on a meeting in a public place, one they may say is close to their home or work, even though it is not. During the meeting, the buyer may be offered a pre-purchase inspection, and possibly a test drive. The curbsider may admit to some damage on the car, though this will likely have been repaired and may not be apparent. If the buyer decides to go ahead with the purchase and initiates a transfer of title, it is likely the name on the title will not match the curbsider-seller’s name; the curbsider will often explain he is selling the car for a friend or relative, though, again, this is not the case. It may take some time before the buyer finds out the car has been titled a “rebuild” or “salvage” unfit for sale or for the road, or has some other major damage not disclosed during the pre-purchase inspection, or still has a lien on it, though by this time the curbsider has changed phone numbers and email addresses and is untraceable. Curbsiders may source the vehicles they sell from wrecking yards, from other dealers, through public salvage auctions or, in some provinces, from licensed wholesalers. 56 Generally, however, these are vehicles a licensed dealership would either be legally unable to sell, or would have difficulty selling. OMVIC tracked down a pair of curbsiders in October 2012 who, though separated by hundreds of kilometres, worked together to “tag-team” victims. 57 The salvage-title vehicle would be registered to one of the curbsiders, in Northern Ontario, and peddled to prospective buyers by the curbsider in the greater Toronto area. Other types of fraud Aside from the types outlined above, there are several less common forms of classifieds websitebased used car sales fraud. Legitimate sellers who include their phone number on their vehicle-for-sale classifieds listing are more and more frequently getting phone calls from companies offering to help them find “qualified buyers” for the car for a fee. The company typically promises they will be able to help sell the car for a price higher than market value within 90 days, for a money-back-guaranteed fee of somewhere between $200 and $500, usually paid via credit card. When the car is not sold within this timeframe, the seller will often find it nearly impossible to collect their refund, usually do to some technicality on the credit card company’s part. 58,59 56 interview with John Bachinski, Alberta Motor Vehicle Industry Council, November 1, 2012 http://www.autos.ca/general-news/beware-of-tag-teaming-curbsiders/ 58 ibid. 59 interview with Daniel Williams, Canadian Anti-Fraud Centre, November 3, 2012 57 14 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada These sell-your-car-for-you services can not necessarily be labeled clear-cut examples of fraud, however, says the Anti-Fraud Centre’s Williams, because “it’s a matter of how much work [the company is] actually doing.” The consumer is paying for a service, and complaints may hinge on how effective this service is, technically—not whether or not they’ve been defrauded. “Cloning” or “re-tagging” involves taking the VIN (vehicle identification number) from a car for sale on a classifieds website, reproducing it on a blank metal VIN tag, and fixing it to a similar car that has been stolen. When the stolen vehicle’s new VIN is checked by a prospective buyer, it will show up as a legitimately-titled for-sale vehicle. 60 One scam reported on by the Globe and Mail in 2008 involved a Craigslist used car listing posted by fraudsters posing as the father of an actual Canadian soldier killed in Afghanistan. The asking price for the 2006 BMW in the ad – the soldier never owned a BMW – was $4,000. 61 Another from July 2011 involved an Edmonton-based fraudster who swindled a buyer he met via Kijiji of $10,000. The buyer and seller met near an apartment complex to inspect, then purchase, the fraudulent seller’s 2011 Ford Focus. After they had exchanged the title and keys and the money, the fraudster used a second set of keys to make a sudden getaway using the car. 62 Prevalence of fraud The damage online used car sales fraud deals to both Canadian consumers and the Canadian economy are hard to pin down. Based on the number of complaints they received in 2012, the CAFC estimates online car shoppers were directly defrauded of more than $1.17 million last year, 63 though they admit the crime is likely grossly under-reported. (The complaints they receive may represent as few as one percent of the total actual crimes committed—which would make the economic impact closer to $117 million.) Curbsiders cost Canada an estimated $300 million in taxes every year. 64 Numbers on the prevalence of online used car sales fraud are similarly evasive, though there are some things we know for certain. As classifieds websites have stepped up their fraud detection and prevention efforts, the number of phony listings has dropped off. Most are still finding curbsider detection, however, more difficult. Kijij.ca Autos, because it is the largest classifieds website in Canada, hosts a significantly higher number of fraudulent listings than other sites, though as a percentage, the number is very low. Customer support head Jasserand says roughly one percent of listings posted to the site are 60 interview with Allen Atamer, LTAS Technologies, August 19, 2012 Chris Purdy, “Ad Scam Uses Name, Photo of Soldier Killed in Afghanistan.” Globe and Mail November 11, 2008 62 http://cnews.canoe.ca/CNEWS/Canada/2011/07/14/18417506.html 63 email correspondence with Daniel Williams, Canadian Anti-Fraud Centre, March 25, 2013 64 Bob Beattie via Mark Toljagic, “Curbsiding: Unsafe at Any Price.” Toronto Star April 9, 2011 61 15 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada fraudulent, but that of these, most are quickly detected and removed. He estimates that, at any given time, only 0.1 percent of listings visible on the site are fraudulent. 65 “For the overseas scammers, it’s really a numbers game,” says Jasserand. “They’re constantly fine-tuning their posting techniques, trying to hide, knowing full well that ninety percent of their scam ads are not going to make it to the site.” Jasserand says the website receives only “a very, very small number” of reported instances of fraud, and that the number of “escalations” requiring police attention is, for the entire site, typically less than 100 per month, and recently under 50 per month, more often than not. The Kijiji.ca Autos page specifically gets less than 10 fraud reports per month on average. AutoTrader.ca’s Director of Consumer Marketing, Ian MacDonald, said the percentage of fraudulent listings on his website is similarly in the single digits. A classifieds website trade journal pinned the number of bogus ads posted at around seven percent for AutoTrader in the U.S., but noted that, as with Kijiji, most of these are taken down before they are seen by consumers. 66 AutoTrader receives very few complaints of fraud, MacDonald said, and most fraudulent listings highlighted by consumers tend to be “false positives”—not actual frauds at all. The Canadian Anti-Fraud Centre’s Williams says the organization started separating online car sales fraud from other types of online merchandise-selling fraud in 2012, limiting their pool of useful data. However, using the numbers of complaints they had received regarding one specific type of used car sales fraud as an example, Williams pointed to a relatively fixed rate of fraud across the years 2008 through 2012. He noted that in 2012, the Centre received 1,174 reports of online used car sales fraud where the bogus seller targeted a legitimate buyer; and 167 reports where a bogus buyer targeted a legitimate seller. 67 MacDonald says the scams involving a bogus seller selling a non-existent vehicle – or, sometimes, a stolen vehicle – is more prevalent on AutoTrader than scams involving bogus buyers targeting legitimate sellers. 68 But Kijiji’s Jasserand says increasingly successful efforts to deter fraudsters from placing bogus listings have forced some to change strategies and instead try to defraud legitimate sellers. “This year, we’re seeing a dramatic increase in scam activity on what we call ‘the reply side,’ affecting the sellers. That’s the hot new trend in scams,” he says. “Because it’s become so difficult to fraud in other ways, we’re seeing a lot of fraud going the other way, through the replies.” Curbsiding seems to pose a bigger problem for both websites than outright fraud does; listings posted by curbsiders more closely mimic legitimate postings – and are thus harder to detect – and are much more prevalent. 65 interview with Christian Jasserand, Kijiji Canada, October 29, 2012 “Fraud: Global Threat and Growing.” Classified Intelligence Report 12.21 (2011): 6 67 interview with Daniel Williams, Canadian Anti-Fraud Centre, November 3, 2012 68 interview with Ian MacDonald, AutoTrader.ca, November 14, 2012 66 16 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada The most commonly printed statistics on curbsiding in Canada come from the Used Car Dealers Association of Ontario’s national surveys, which they conduct regularly on behalf of several provincial dealership regulator organizations. According to the most recent UCDA estimates, roughly 29 percent of used car listings on classifieds websites in Ontario are posted by curbsiders; across Canada, the number ranges between 18 and 21 percent of total listings. 69 The UCDA survey usually includes thirty to forty thousand listings collected across several months. (Ads posted repeatedly over those several months are counted only once.) The UCDA then analyzes the listings and tallies the number of contact phone numbers tied to two or more separate listings—suspected curbsiders. The percentage represents the number of listings posted by suspected curbsiders over the total number of listings surveyed. 70 According to Bob Beattie, formerly of the UCDA, the percentage of curbsider listings both online and in printed classifieds periodicals or newspapers has not changed markedly in the past 25 years—“it varies anywhere from about 17 percent to about 24 percent.” A detailed breakdown of the UCDA’s latest Ontario survey, conducted between October 2011 and January 2012, found the vast majority of the 3,961 suspected curbsiders they identified – some 2,767, or 70 percent of them – had posted listings for just two different cars in that period. Six had posted listings for twenty or more cars. OMVIC’s Smith says the regulator opened 703 curbsider investigations in 2011, most of them based on complaints they had received. Survey results from the Motor Vehicle Sales Authority (VSA) of B.C. echo the UCDA’s estimate, that 25 to 30 percent of listings on classifieds websites are posted by curbsiders. Ian Christman, the VSA’s Registrar of Motor Dealers and Privacy Officer, says a 2009 survey of the British Columbia vehicle owners’ registry turned up some 1,800 non-dealers who had had 25 or more cars registered to their name over the previous two years. Two years later, in 2011, that number had gone down roughly 10 percent—“now whether they’ve learned to hide themselves better or have removed themselves from the industry, we don’t know,” Christman says. The top two names on that list – suspected curbsiders – had sold some 400 cars each per year. 71 Kijiji’s Jasserand cautions the numbers may not be quite that easy to track. “These people [scammers] will constantly change the account they are using, with a view to covering their tracks and going underground, and this is the reason – along with the fact they’re legitimately local people [as opposed to scammers overseas] – that it’s a little bit difficult to come up with a percentage when it comes to curbsiders.” Allen Atamer is the Principal Engineer at LTAS Technologies, which develops the Harmari Curbsider Report software used to track curbsiders online. He is similarly wary of the UCDA’s 69 http://www.ucda.ca/content/curbsider-research.aspx interview with Bob Beattie, Used Car Dealers Association Ontario, October 5, 2012 71 interview with Ian Christman, Motor Vehicle Sales Authority of B.C., October 5, 2012 70 17 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada 29 percent figure. “The [UCDA survey doesn’t] get rid of dealers, because dealers post in Kijiji as private sellers all the time. Why? To avoid the fifteen dollars charge per ad,” explains Atamer. “A significant portion of that 29 percent is [legitimate] dealers, ones who should be charged with inappropriate advertising according to the Motor Vehicle Dealers Act.” 72 Beattie concedes that legitimate dealers who misrepresent themselves as private sellers are indeed included in the UCDA’s number, and, along with unregistered dealers and big curbsiders, make up some of the names at the top of the list with 20 or more cars for sale. But he argues that because, as Atamer notes, they are in violation of the Act – it states dealers must include their name in all advertisements – they deserve to be branded “curbsiders.” Atamer assumed some of the survey results were duplicates of sellers reposting ads, though the UCDA’s Beattie contends duplicates are removed. Atamer’s estimate, which he admits is also just a “finger-in-the-wind” reading, is that around nine percent of classifieds listings posted in Ontario are curbsiders’. “There’s an unknown in there, too,” Atamer says. “Some percentage of the ads on Kijiji doesn’t post a phone number, so there’d be no way to correlate them unless you were to somehow shop the car and they give you the phone number. So there’s a little uncertainty there, but for the most part, 90 percent of the Kijiji ads have phone numbers.” Atamer figures the number of curbsiders in other, less heavily regulated provinces is likely higher than nine percent. He also says that a survey of listings on Craigslist – which are more likely to not include a phone number – he did for a U.S. client returned a curbsider rate of roughly 17 to 20 percent. A note on fraud reporting Figuring out the impact of online used car sales fraud on Canadian consumers is difficult in part because it is likely most fraud goes unreported. In an international survey on cyber-crime – conducted by market research firm Strategy One on behalf of computer security company Symantec – more than half of internet fraud victims did not report the crime to the police. They noted they had felt there would be little chance the perpetrator would be caught, or that they felt self-blame, that it was partly their fault. Others did not want to be labelled a victim. 73 “In the Symantec survey, in fact, 80 percent of responders said that they did not expect a cybercriminal to get caught,” explains information security expert Wendy Goucher in her article “Being a Cybercrime Victim” in Computer Fraud and Security. “Some people failed to report the crime because they felt they had ‘been stupid’ to allow themselves to get drawn into the scam, and consequently they felt they should not receive any help to extricate themselves.” 72 73 interview with Allen Atamer, LTAS Technologies, August 19, 2012 Wendy Goucher, “Being a Cybercrime Victim.” Computer Fraud and Security (2010): 16-17 18 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada Goucher concludes most victims likely feel little or no motivation to report the cybercrime they have experienced, and in fact may feel motivation to cover it up in order to save face. The Anti-Fraud Centre’s Williams explains the proportion of underreporting is likely similar or worse in Canada. “The vast, vast majority of fraud is not reported to us, and generally speaking, it’s not being reported to anyone. It’s amazing the amount of victims who blame themselves once they’ve been had, and they just write it off as a lesson learned,” he says. “In a lot of cases they’re embarrassed about being defrauded and they tell no one, no one learns from their mistake.” He explains that when police raid and seize criminal fraudsters’ records, a list of victims’ names and information is sometimes among the documents recovered, and that when that list is crossreferenced with the names of victims who had reported the crime to the Centre, the proportion who had is typically between one and five percent. “We accept that what we’re seeing is just a tiny fraction of what’s out there. The numbers that come in just to us may not reflect what’s going on out there—it’s just a reporting issue.” 74 Most dealership regulator representatives and experts said they saw no trend among fraudsters favouring certain classifieds websites, though of course most tend to target websites where listings can be posted for free, since it makes the scam a lot cheaper to run, and since those websites tend to be more popular. The Anti-Fraud Centre’s Williams said fraudsters tend to post on pay-per-listing websites only if they have access to a stolen credit card. 75 The UCDA notes that, in their surveys, they found a higher number of curbsiders used Kijiji.ca than other classifieds websites. “We called it ‘Kijiji: Curbsider Heaven’ in one of our newsletters to our members last year,” Beattie says. “We surveyed Craigslist, Kijiji, AutoTrader, we pull out things like AutoCatch and Wheels and CarPages, and all of those that have private ads, and Kijiji was number one—close to ninety percent [of the curbsiders were posting on Kijiji].” 76,77 Beattie presumes this is because it is free to post listings on Kijiji, but it is more likely because Kijiji is the most popular used car classifieds website in Canada and has more listings generally than any other website. Beattie, Williams and other stakeholders interviewed also said they had found the proportion of fraudulent listings and fraud victim reports relatively consistent between different provinces, though Beattie noted the Quebec-based Automobile Protection Association has found the number of curbsiders to be lower there. 78 John Bachinski, Executive Director for the Alberta Motor Vehicle Industry Council (AMVIC), noted his organization has received very few consumer complaints regarding online used car 74 interview with Daniel Williams, Canadian Anti-Fraud Centre, November 3, 2012 ibid. 76 http://blog.ucda.ca/kijiji-is-curbsider-heaven/ 77 interview with Bob Beattie, Used Car Dealers Association Ontario, October 5, 2012 78 ibid. 75 19 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada sales fraud. He chalked this up to Alberta residents possibly being more tolerant of fraud because they can afford to be, financially, but cannot afford the time to file a complaint. He also suggested it is possible consumers in Alberta are more likely to handle fraud resolution themselves—through small claims court, for example. 79 Ian Christman, Registrar of Motor Dealers and Privacy Officer for the Motor Vehicles Sales Authority of B.C. (VSA) says he has seen a drop in the number of curbsiding complaints from consumers over the past few years, and that it is more and more often a case of unregistered dealers being unaware of the regulations. “We’ve gone from about 3,500 [total—not just curbsiding] consumer complaints down to about 2,700 consumer complaints [between 2011 and 2012],” he says. “We’re on track to do 700 investigations this year when we did 950 last year, and about 1200 a couple of years before that.” 80 Jacques Fugère Jr., Administrative Services Counsellor for the OPC, which monitors curbsiding complaints in Quebec, notes that while the organization does not have specific statistics available on curbsiding, they have seen “complaints related to the sale of used vehicles [increase 40 percent] since April 2010.” 81 Fraudster-victim composition The hundreds of thousands of Canadians who shop for used cars on online classifieds websites every year do not come from a specific region, age group, or income bracket, but fraudsters and curbsiders do target particular groups with the types of cars they use as “click-bait,” or sell illegally. “By and large, the marketplace for these curbed vehicles fall into two very large groups: one is your less expensive vehicles, which would be cars that would be sold anywhere from between two and seven thousand dollars, which in today’s market are pretty inexpensive cars,” Bob Beattie, formerly of the UCDA, says of curbsiders’ cars. “The other ones are the very expensive cars, and these are the accident cars the insurance companies sell at auction for the highest dollar they can get. That’s where the guy is able to buy that $55,000 BMW for $11,000, fix it up and sell it for $25,000, but nobody knew what it went through in its real life. The average selling price of vehicles in the last study we did was close to ten thousand dollars.” 82 The cars fraudsters use to lure consumers to click on a bogus listing often fall into similar groups. Cheaper, compact-size used cars with below-market-value price tags tend to draw consumers with lower incomes, who, due to budgetary constraints, may be more desperate for very cheap used cars and thus more susceptible to scams. “Chances are the people looking for these types of cars are on the lower income scale,” says Allen Atamer of LTAS Technologies. “So these are hard pieces of advice [e.g. fraud avoidance tips like “avoid listings with too-good79 interview with John Bachinski, Alberta Motor Vehicle Industry Council, November 1, 2012 interview with Ian Christman, Motor Vehicle Sales Authority of B.C., October 5, 2012 81 interview with Jacques Fugère Jr., Office de la Protection du Consommateur, March 7, 2013 82 interview with Bob Beattie, Used Car Dealers Association Ontario, October 5, 2012 80 20 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada to-be-true prices”] for them to follow sometimes, especially if they urgently need the car to get to their job to pay for expenses. It’s a necessity for certain folks.” 83 On the other end of the spectrum are the high-end luxury-type automobiles, also advertised with prices well below market value, that draw in buyers who see the huge discount as a compelling incentive to take a risk and, for example, buy a vehicle from out-of-province. “These types of scams are going to target [buyers looking for] high-end luxury vehicles, sometimes exotic vehicles that are worth big dollar amounts; the allure of saving $5,000 or $6,000 or $12,000 by buying remotely makes it worth the risk for some people,” explains OMVIC’s Terry O’Keefe, referring specifically to a spate of U.S.-based car sales fraud that, starting in late 2012, used a fake premium car dealership website to target Canadian consumers. “It’s worth it, because it’s a big savings. And unfortunately, that price that’s too good to be true? That’s not an opportunity. It’s a warning.” 84 Fraudsters also fall into a few specific types. Scammers posting bogus used-car-for-sale listings or soliciting legitimate sellers with bogus offers to buy their car are generally working together as part of a concerted organized crime effort, according to Daniel Williams of the Canadian AntiFraud Centre, and rarely work alone. “It’s typically a sophisticated gang doing the same thing to hundreds if not thousands of people at the same time, and they’re doing a very high-quality job, in a way of speaking,” Williams says. “They can afford to do that, even though they’re only making $4,000 or $5,000 [per victim] because they’re doing it to so many people, they can afford to put out a million-dollar product.” 85 These criminals tend to operate worldwide, Williams says – “they’re happy to rip off people everywhere around the globe” – making it hard to pin down their location, or where their ringleaders might be. “Just based on where the money goes, it goes to Canada, it goes to the U.S., it goes to the U.K., it goes to Spain—it goes to any and everywhere,” he says. Curbsiders, by the nature of the fraud they exercise, tend to operate locally, within Canada. They may be working in concert with other curbsiders, and curbside either on the side or on a full-time basis. Some work out of their home, while some are simply unregistered used car dealerships whose dealer application was turned down, forcing them to work outside of the law. “If you think about the difficulties dealers have in registering a business as a motor vehicle dealer in the province of Ontario, they have to go through a lot of different things,” says Beattie. “They have to go through a criminal record search, they have to make payments into the [consumer] compensation fund, they have to give a complete financial background, all of those things before they can be a registered dealer, in addition to which they have to find a place of business and have it approved locally to be able to operate out of there. Well, that’s all expensive. A telephone number [used to curbside] isn’t.” 83 interview with Allen Atamer, LTAS Technologies, August 19, 2012 interview with Terry O’Keefe, Ontario Motor Vehicle Industry Council, December 14, 2012 85 interview with Daniel Williams, Canadian Anti-Fraud Centre, November 3, 2012 84 21 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada Current fraud prevention techniques Because of the negative impact used car sales scams and curbsiding have on consumers, businesses and the industry as a whole, classifieds websites and provincial dealership regulators use a variety of fraud detection and prevention techniques to try to mitigate the damage done. The classifieds websites themselves typically scan listings for fraud three different ways: using keyword or IP (internet protocol) address-based scanning and filtering before the listing is posted; having human moderators review suspicious listings manually; and by tapping a community of volunteers who similarly search for and flag suspicious listings. “Customer support at Kijiji essentially means ‘trust and safety,’ and by that I mean doing everything we can to preserve the security of the buyers and sellers who use Kijiji on a monthly basis,” explains Kijiji’s Jasserand. “What this means is we’ve put in place procedures, filters to ensure the bad guys don’t come to the site, don’t use it, or if they attempt to do it, it’s going to be very difficult for them to gain any sort of visibility.” While Jasserand could not reveal the details of the site’s built-in filters for security reasons, he was able to explain the role of the “ad moderators” who make up the trust and safety team: “These people work 24-7 to manually screen the ads [listings] based on the recognized level of risk in certain categories based on a certain pattern in ad posting, and so this complements the filter that the technology is doing.” He was also able to explain how the community monitoring process worked to leverage Kijiji’s very active, very engaged 11-million-strong user base. “These people have made Kijiji their own, and a lot of them have great instincts, so if something had escaped us or our filters, if something fraudulent makes it to the site, they will signal us very, very quickly,” Jasserand says. “They will either flag it or email us, or we have actually a small community of volunteers that we trust so much we’ve given them access to remove ads that they deem fraudulent.” Jasserand says based on the tracking tools and metrics they use to measure the success of their fraud prevention techniques, Kijiji is for the most part successful in blocking a vast majority of scammers’ listings from getting visibility on the site. “We’ve realized very quickly that the moment we deprive the scammer of any kind of visibility on the site, they eventually stop, because there’s no point in attempting to post on the site and it’s not going through,” he says. 86 AutoTrader’s Ian MacDonald explains his site works similarly, starting with an automatic prescreening that filters out listings based on certain keywords, unusual pricing points or the location of the uploader. “That’s why when an individual lists a car for sale, there’s a delay of maybe up to 12 hours while it gets automatically moderated,” he says. 86 interview with Christian Jasserand, Kijiji Canada, October 29, 2012 22 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada He says AutoTrader also employs a team of moderators who manually filter through listings following that pre-screening process. The few fraudulent listings that get through that filter are typically reported back to the moderators by users, who can use the “report abuser” button on every listing to report a user or listing they think is a “scam/illegal,” “spam/duplicate,” or is “miscategorised” in the wrong part of the site. MacDonald adds that frauds that target legitimate sellers are usually committed using an application programming interface (API) that automatically emails hundreds or thousands of the site’s users simultaneously with a bogus message expressing interest in buying their car. AutoTrader blocks any sort of mass-emailing with a CAPTCHA system that asks the messagesender a security question – usually to type out the letters in an image of a slightly blurred word or phrase – that can only be completed by a human user. 87 Both sites also work with Canadian vehicle history report service CarProof, which supplies customers shopping for used cars a report with a detailed history of a potential purchase using its VIN. “We’re always watching those websites, so we typically find a lot of those ‘too-good-to-betrue’ vehicle sales as soon as they go up, and we pass them on to our contacts at Kijiji and AutoTrader,” says Shawn Vording, Director, Western Canada Dealer Sales for CarProof. 88 While the tried-and-tested fraud prevention techniques used by both AutoTrader and Kijiji are generally effective, both sites have to constantly adapt to scammers using new techniques that circumvent old security measures. “It’s a constant battle because as you put in place more and more restrictions and systems,” says MacDonald, “obviously these guys are working, they’re always thinking of ways to get around them.” Both sites monitor and compare fraud activity and trends with their corporate counterparts around the globe. Curbsider detection and prevention has apparently proved more difficult for the websites to detect and monitor. “It took us a little bit of time to realize how big a problem curbsiding was. Our focus was really on the overseas fraudsters,” says Jasserand. 89 “It’s a little bit different, since we’re dealing with local people [the curbsiders], and that’s the whole intent of Kijiji, it’s allowing local people to post on the site.” “We have ways to identify these people, but at the same time we realize we can do even more, and right now that means developing a closer relationship [with groups like] OMVIC,” he says. “If [these groups] identify a curbsider who is posting illegally ads on the site, someone who is doing all they can to cover their tracks, we’re going to provide information pertaining to that person. We state it very clearly on our sites, that we will work with law enforcement agencies.” 87 interview with Ian MacDonald, AutoTrader.ca, November 14, 2012 interview with Shawn Vording, CarProof, August 9, 2012 89 interview with Christian Jasserand, Kijiji Canada, October 29, 2012 88 23 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada Kijiji started working with Alberta’s AMVIC in 2011 (the regulatory body is also an advertiser on the site), and their collaboration has already led to the conviction of several curbsiders in that province. Generally, though, the provincial dealership regulatory bodies – the organizations tasked with enforcing each province’s motor vehicle dealer act, which typically prohibits curbsiding – have worked separately from the classifieds websites to track down and prosecute curbsiders. Until recently, these groups’ curbsider detection programs basically relied on complaints from consumers and dealerships, or tips from other enforcement agencies. OMVIC’s investigation unit, which is made up of 13 investigators, launched 703 investigations in 2011, most of them based off of complaints. However, several of these groups, including OMVIC and AMVIC, now also employ the Harmari Report by LTAS Technologies, a classifieds websites analytics tool used to automatically sort through listings and identify suspicious ads. “[Investigators] get a lot of the investigation upfront with the Harmari report,” explains Ontario-based Allen Atamer, who developed the technology. “All the digging and going through ads and manual labour of putting all that data together is done for them and presented in an easy-to-use format, which allows them more time to spend on real foot patrol-type of investigation as opposed to desktop investigation.” 90 The Harmari Report basically does automatically what investigators in the past had to do manually: sort through listings to find a repeat phone number, that is, a phone number attached to multiple used car listings, likely to be a curbsider. OMVIC reports they have found the program very effective at detecting curbsiders—too effective, in fact. “The [Harmari Report] is very good at what it does. The problem is it’s very good at finding curbers, but you just wind up with a big pile of curbers to go after. You end up drowning in the program’s success,” says OMVIC’s Smith. “In fact, the biggest difficulty is the volume—it’s basically an ocean of curbsiders, and you’ve got 15 investigators to deal with it. The process of investigating and prosecuting them takes time and resources, but is otherwise fairly simple and straightforward, and quite doable,” says Smith, formerly the Detective Sergeant of the Halton Regional Police’s fraud investigation unit. (Alberta’s AMVIC – which is currently staffed with 15 investigators – is also now adopting the Harmari Report and figuring out how to best implement it.) Once a potential curbsider is identified, investigators generally conduct as much online research as they can about the person, and then “shop” the vehicle—they try to buy the car. “As soon as they try to sell us the car, we’ll charge them. [We confirm they’re a curbsider] if they’re selling a car that’s not in their name,” says OMVIC’s Smith. 91 90 91 interview with Allen Atamer, LTAS Technologies, August 19, 2012 interview with Carey Smith, Ontario Motor Vehicle Industry Council, October 3, 2012 24 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada While this technique of flushing out curbsiders is common to most regulators, the prosecution of, and penalties handed to, curbsiders varies province to province. In Ontario – where, in 2011, OMVIC closed more than 500 of the 703 curbsider investigations they launched, and helped convict 120 curbsiders – the regulator has lobbied to install a minimum fine for convicted curbsiders. Director of Investigations Carey Smith says OMVIC will sometimes let a “run-of-the-mill” first-time-offense curbsider off easy with a written warning, but that after that they slap the person with the minimum $2,500 fine and, if necessary, push for an even more severe penalty. Repeat offenders can face jail time and fines of up to $50,000, says Smith, which, while it definitely acts as a deterrent, also raises a host of new problems. “Convictions are going down because curbsiders are getting harder to prosecute—the courts are demanding more and more evidence to support a charge, so it takes longer to investigate and to gather evidence,” he says. “At the same time, these curbsiders are often more well-defended, they get lawyers because it’s worth getting a lawyer, and then you drag the whole system down, because now they put up a defense actually.” 92 The regulator spends roughly 50 percent of its legal resources to catching and prosecuting curbsiders. 93 Bob Beattie, formerly of the UCDA, adds specifically that OMVIC may face difficulties even in proving the curbsider is who they say are, or are not – “some of these fellas are quite slippery” – and getting them to appear in court on schedule. 94 John Bachinski of AMVIC says that the regulator sees similar results in Alberta – curbsiders there get a fine averaging $600 for a first offense – but that finding the time to collect evidence is also likely the most difficult part of curbsider prosecution and conviction. “Whenever you go for criminal charges, or a charge under the Fair Trading Act, it is time-consuming, whether it’s an online ad or another type of fraud. It’s often not difficult, it’s just time-consuming to get your evidence collected the proper way, go to the Crown [prosecutor], and get it prosecuted,” he says. Bachinski says AMVIC has not pushed the government to raise the fines for curbsiding, but that they would likely find support if they did. However, because of the lower rate of curbsider fraud in Alberta, the case for a stiffer, more serious penalty has not yet been made. 95 The province has, however, just passed a bill allowing the regulator to use administrative penalties as an enforcement measure; the regulations around these new penalties have yet to be finalized. 96 In B.C., where the legislation is, as the VSA’s Ian Christman puts it, a little more “anemic” and the crime technically unregulated, they employ several novel tactics to force curbsiders into compliance. “We can write a curber a $288 violation ticket – that’s not even the cost of profit on 92 ibid. “OMVIC on Curbsiders,” The Dealer Standard [OMVIC] (Spring 2012): 6 94 interview with Bob Beattie, Used Car Dealers Association Ontario, October 5, 2012 95 interview with John Bachinski, Alberta Motor Vehicle Industry Council, November 1, 2012 96 email correspondence with John Bachinski, Alberta Motor Vehicle Industry Council, February 26, 2013 93 25 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada one car – and after that we either go to civil court and file a cease-and-desist order or we find a Crown council willing to prosecute,” says Christman. “And they’re just really too busy to deal with regulatory offences.” The first step the VSA takes is to educate the curbsider about the benefits of becoming a licensed dealer, and get them to voluntarily comply with the regulations. “We’ve had a big push in the last four months and we have some major people actually signing up to be licensed. How long they stay, we don’t know, but at least they’re trying,” Christman explains. “You’re not worried about how long in the past they’ve been a curber, you don’t go back for back licensing fees, you just go on and get them back into compliance and let’s get going.” If that does not work, they apply pressure by getting other agencies to corner the curbsider, too. “Curbsiders tend to sell from a home when they’re not licensed or zoned to do so, so we talk to the bylaws department to deal with them,” Christman offers an example. “Recently, we started piloting with the Canada Revenue Agency [...] because usually if they’re curbsiding, they’re under-reporting taxes, and that has also started working.” Trying to convict a curbsider under the province’s Motor Dealer Act – the crime carries a $100,000 fine or six months in prison, or both, upon conviction under the Act – is usually used as a last resort, because the VSA cannot find a prosecutor to try such cases. 97 Fraud awareness campaigns Because the chances of being snagged in an online used car sales scam seem smaller than they likely actually are, most consumers on the web have an “it-could-never-happen-to-me” attitude toward internet fraud. 98 Both classifieds websites and regulators attempt to combat this by waging almost-constant awareness campaigns giving users tips on how to spot fraudsters or curbsiders. “While most individuals who use Kijiji have success with buying, selling, renting or connecting with others, from time to time we do receive reports of people attempting to scam or defraud our users,” Kijiji’s Online Safety Tips page warns. “We have found that one of the best ways to address this problem is to ensure that all transactions take place locally and in-person. Remember that Kijiji is a local classifieds web site and Ads are not reviewed before they go live on the site.” 99 The page also notes, “Never send or wire money to sellers or buyers. This includes never mailing a cheque or using payment services like PayPal, eBay Motors Purchase Protection Program, Bidpay, Western Union or Money Gram to pay for items found on Kijiji.” It closes with a nearuniversal piece of advice found on almost every online used car sales fraud tip sheet: “If something sounds too good to be true, it probably is.” 97 interview with Ian Christman, Motor Vehicle Sales Authority of B.C., October 5, 2012 based on data from 2012 Angus Reid-ACC consumer survey; Wendy Goucher, “Being a Cybercrime Victim.” Computer Fraud and Security (2010) 99 https://help.kijiji.net/ca/knowledgebase.php?article=26 98 26 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada AutoTrader’s Fraud Protection Tips page similarly offers a detailed list of ways to spot and avoid fraud online. Specifically, it advises consumers avoid using online escrow (money transfer) services, as almost all of these are fraudulent. 100 Buyers who ask for a partial payment up front and who insist on contact only via email should also be avoided, it warns. Craigslist’s about > scams page goes into even more detail, offering up actual exams of email templates used by scammers to defraud users. 101 They also automatically direct buyers and sellers to this information before a purchase or sale. Aside from linking to these sorts of tips in FAQ (frequently asked questions) sections at the bottom of their front pages, these websites will also sometimes include links to this advice during key points in the buying or selling process. Of course, while these websites want to warn users about the possibility of fraud so that they can avoid the unpleasant experience of being defrauded, they also do not want to over-emphasize the possibility of fraud and potentially scare users away from the website. Regulators’ tip sheets for avoiding curbsiders also sound very much alike, and often cite these red flags as a warning you may be dealing with a curber: i) if you telephone and say “I’m calling about the car for sale,” and the seller replies, “Which car?” ii) if the seller’s asking price is well below market value for the car iii) if any of the seller’s answers sound fishy or “too good to be true” iv) if the seller would rather meet in a public parking lot; if the seller meets you at his home, check if the address on his licence matches the address of the place at which you meet him v) if the seller has other cars sitting around his property with no licence plates vi) if the seller’s registration and driver’s licence (in Ontario) don’t match, and he offers an excuse about it being a friend’s car vii) if the seller is unable or unwilling to offer you a landline or work phone number Ontario’s OMVIC – which directs nearly 100 percent of its consumer education campaign efforts towards curbsiding avoidance tips and fraud warnings – offers consumers a “Creep-o-meter” to help determine how likely it is the seller they are dealing with is a curbsider. 102,103 Alberta’s AMVIC books advertising space directly on Kijiji to ensure consumers see their curbsider avoidance tips. 104 The RCMP also has an online shopping fraud tips page. 105 100 http://wwwa.autotrader.ca/general/info/Fraud_Protection_Tips.aspx http://www.craigslist.org/about/scams 102 http://www.buywithconfidence.ca/consumer-protection/creepometer 103 “OMVIC on Curbsiders,” The Dealer Standard [OMVIC] (Spring 2012): 6 104 interview with John Bachinski, Alberta Motor Vehicle Industry Council, November 1, 2012 105 http://www.rcmp-grc.gc.ca/scams-fraudes/shop-magasinage-eng.htm 101 27 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada While the tips on these pages are generally straight-forward and easy to follow, consumers may not always keep them top of mind while shopping; most consumers seem to inherently assume they could never be taken in by a scammer, that “it could never happen to me.” At the same time, most fraudsters and curbsiders are well-practiced in coming off as convincing instead of suspicious. It is also worth noting that all these separate pieces of advice can sometimes conflict—for example, while AutoTrader’s page advises avoiding escrow services when it comes to paying for a car, the RCMP’s page encourages the use of escrow services. 106 106 ibid. 28 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada In Detail: Prevalence of Online Car Sales Fraud in Canada The ACC commissioned market research firm Angus Reid Public Opinion to conduct a consumer survey in mid-November 2012 in order to figure out how prevalent online car sales fraud is in Canada. The survey questionnaire also asked if respondents would be willing to volunteer for telephone interviews on their experiences shopping online for used cars; these interviews were used as case studies of Canadian consumers’ personal encounters with fraud. Consumer survey intent and methodology During our preliminary research into the topic, it became apparent there was little publically available information on the issue, and that recently published, current studies or articles (less than five years old) or studies specific to a Canadian context were sparse. The ACC decided to conduct a consumer survey into the prevalence of online car sales fraud in Canada in order to complement the numbers already out there. Specifically, the ACC wanted to find out about consumers’ perceptions of online used car sales fraud; which particular websites they most frequented while shopping for or trying to sell a used car; and how often they encountered fraud while shopping or selling. A 13-question survey – with a combination of multiple-choice and open-ended questions – was drafted by the ACC. The questionnaire can be found in the Appendix to this report. The ACC hired market research firm Angus Reid Public Opinion to conduct the survey and distribute it online among their Angus Reid Forum panellists between November 13 and November 19, 2012. The survey was filled out by 1,006 Canadian adults who had purchased or sold a vehicle online via a classifieds website within the past year. The margin of error was +/3.1 percent, 19 times out of 20. The number of survey respondents is broken down below by demographic: gender men women 601 405 age group 18 to 34 years old 35 to 54 years old 55 years old and older 120 427 459 region British Columbia Alberta Saskatchewan and Manitoba 238 141 104 29 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada Ontario Quebec Atlantic Canada 271 149 103 education high school diploma or less college or technical school diploma university degree or more 183 527 296 annual household income less than $50,000 between $50,000 and $100,000 more than $100,000 273 409 194 At the end of the survey questionnaire, respondents were asked if they would like to volunteer for a telephone interview on their online used car shopping experience; they were promised anonymity, and that their personal information would be protected. The ACC received replies from a half-dozen respondents; of these, three had experiences relevant to the study. Their interviews formed the used car sales fraud case studies found below. Consumer survey results and analysis The sample demographic surveyed by Angus Reid included adults from across Canada who had purchased or sold a vehicle online in the previous 12 months. Roughly 0.02 percent of Angus Reid Forum panellists – some 3,000 people – qualified, of which 1,006 were surveyed. This 0.02 percent figure, extrapolated across the Canadian population, would indicate roughly 600,000 Canadian consumers buy or sell a used car via an online classifieds website every year. 107 Of these 1,006 respondents, roughly 80 percent said they did not encounter any sort of fraud during their used car shopping experience; the other 20 percent, however, encountered one of several types of fraud. The most common form of fraud respondents said they had encountered involved a fraudulent buyer contacting them to purchase the car they were trying to sell online— roughly 13 percent of respondents said they encountered this sort of fraud. Five percent said they encountered a dealer who posed online as a private seller but who identified themselves as a dealer when asked—a dealer the Used Car Dealers Association or other regulators might consider a “curbsider” but whom other experts might not. Of the roughly 200 respondents who encountered fraud, 12 percent dealt with curbsiders, while 15 percent said the trouble was that the seller or buyer was out of the country. Five percent said they received a message from a third party asking to help sell their car on their behalf. Generally, a total of 48 percent had some concerns about the buyer or seller. Another 35 percent had 107 email correspondence with Mario Canseco, Angus Reid Public Opinion, January 2, 2013 30 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada payment-related problems; for 13 percent, this included an apparent PayPal-related scam. Five percent said they, as legitimate sellers, ran into the overpayment-and-refund scam problem. A sum of 20 percent had some difficulty with vehicle shipping and delivery, most commonly – according to 11 percent of the 200 fraud-problemed respondents – that the scam buyer wanted to send an agent or third party to pick up the car. 108 Roughly 76 percent of respondents said they had browsed Kijiji.ca before making their online purchase or sale, nearly twice the number of respondents who had said they had browsed AutoTrader (35 percent). As a national average only 23 percent said they had looked at Craigslist, though 69 percent of B.C. residents said they browsed the site (Kijiji was second in the province, at 50 percent). Kijiji was particularly popular in Alberta and Atlantic Canada, while 55 percent of Quebec residents said they had looked at the Quebec-market-only LesPAC. 109 When it came time to make a deal, roughly 60 percent of respondents said they ended up selling their vehicle on, or purchasing it from, Kijiji. Roughly 13 percent of respondents closed the deal on Craigslist, and about the same number did so on AutoTrader. 110 When asked about the type of car respondents had bought or sold online, 23 percent said the vehicle was from a model year between 1996 and 2000, while 19 percent said it was from model years 2001 to 2003. Broken down into specific brands, 15 percent of the vehicles traded were Fords, 10 percent were Hondas, and nine percent were Chevrolet or Toyota. Separated by parent automaker, 23 percent were General Motors products, 16 percent were from Ford, and 13 percent were Chrysler products. Almost all vehicles (97 percent) were used, not new; and most (80 percent) were purchased from a private seller, not a dealer. Roughly 19 percent of vehicles respondents bought or sold online were $1,000 or less; 18 percent were between $2,000 and $4,000. Totaled together, roughly 63 percent were less than $6,000 (except in Saskatchewan and Manitoba, where 25 percent were more than $10,000). 111 Roughly 60 percent of respondents said they had not read the website’s policy on fraud protection before or during their online purchase or sale, and 64 percent said they did not research types of online fraud. Respondents above 55 years old were more likely to have researched fraud types ahead of time, however. Of respondents who did research fraud protection prior to their purchase or sale, 22 percent said they had looked up fraud prevention tips using an Internet search engine; 32 percent looked up the classifieds websites’ fraud prevention policy pages, or browsed blogs and automotive forums online. Less than five percent looked at newspapers or magazines, checked with Consumer Reports or the Better Business Bureau, contacted the seller, or spoke with friends, respectively. 112 108 question 10 question 4 110 question 5 111 question 6 112 question 9 109 31 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada A full 75 percent said they did not use the classifieds website’s recommended payment method; a majority – 65 percent – said they paid with cash, in person. Twenty-two percent used a cheque, while just five percent used credit. Just three percent used an electronic form of payment. 113 Of the almost 200 respondents who encountered some sort of fraud during their shopping or selling experience, 77 percent said their experience was met with some sort of resolution, though the ratio was closer to 50-50 in Quebec; roughly 40 percent said they were very satisfied or moderately satisfied with the way the resolution was handled, while 48 percent were not sure. Twelve percent were dissatisfied. 114 When asked if they would consider buying or selling a vehicle online again, 87 percent said yes, they would. Of those who would not, 29 percent said the possibility of online fraud probably or definitely affected their decision—this number was much lower among respondents aged 18 to 34. 115 The results confirm Kijiji’s market dominance (with regional variations in popularity) and roughly approximate the varying severities of different fraud types as outlined by the stakeholders the ACC interviewed. Curbsiding does seem to be one of the most common sorts of fraud, and fraud against legitimate sellers – apparently on the upswing – does appear from these results to be a quite popular scam, too. The growing prevalence of potential fraudsters contacting legitimate sellers to offer to help them make a sale was also confirmed. Consumers’ awareness of, or concern with, online used car sales fraud seems generally low, especially among those less than 55 years old. A majority of active classifieds users have done little or no research into fraud types or fraud prevention; this could be explained by the “It will never happen to me” attitude some experts spoke of consumers adopting. For a full question-by-question breakdown of the survey results, see the Appendix. Case studies and interviews At the end of the survey questionnaire, respondents were asked if they would like to volunteer for a telephone interview on their online used car shopping experience; of the half-dozen responses the ACC received, three were applicable to the study. They are collected below and presented as case studies. All names have been changed so that personal information could be protected. Case study #1 113 questions 7 and 8 questions 11 and 13 115 questions 1 and 3 114 32 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada Regular users of classifieds websites are of course more likely to encounter online fraud. James Martinez says he frequently browses Kijiji and Craigslist for car, motorcycle and motorhome listings, and that his first run-in with fraud happened in 2010, while shopping for a motorhome on eBay.ca. The vehicle was being sold for just below market value, and, according to car history report service CarFax, had a clean history. While James had heard of online fraud, he admits he had an “it’ll never happen to me” attitude. He exchanged several emails and phone calls with the seller, but took it as a red flag when the seller said he was on vacation out-of-country, was unable to return for a pre-sale inspection, and wanted a down payment via Western Union. James stopped chasing the listing. James says he has also encountered potential curbsiders, most recently in fall 2012 during a trip to Florida. He met with a local seller there who had posted a used Scion for sale roughly $2,000 under market value; there were several indicators something about the sale was amiss, however, primarily that the car did not resemble the one in the listing, and had several dents and poorly painted-over body panels. Case study #2 Curbsiders are often well-practiced in telling a convincing story and coming off as sincere when they are in fact telling lies. Emily Taylor and Martin Banks are a married couple who first took to looking for a used car online, a 2004 to 2006 Toyota Echo, in April 2012. After several weeks of browsing classifieds, looking unsuccessfully for a suitable match, Emily came across a justposted Craigslist ad for a 2005 Echo in good condition for around market value, roughly $5,700. They called up the private seller’s cell phone number and arranged to meet him in the parking lot of the condo where he said he lived. The seller explained the car belonged to his wife, and that he was selling it because they were moving to Dubai for work; the first aid kit under the seat, he explained, was there because his child played soccer. He admitted the car had some minor damage, but had been repaired. After they negotiated a sale price, the seller said the car was actually owned by his company, which would pay for the sales tax. Emily and Martin met with the seller again a short while later to transfer title documents; Emily noted the staff at the out-of-the-way insurance brokerage at which the seller suggested they meet seemed to know the seller quite well. She also pointed out the name on the title ended, suspiciously, with “—Motors Corp.,” but Martin waved off her concerns. They paid with a cashfilled envelope. The following week, the red flags Martin had glossed over pressed him into doing a liens search on the car. He found out it had been a write-off, and had suffered damage worth more than $2,000 (the disclosure on the transfer they had signed noted it was a rebuild). He called the dealership whose name was on the title, who told them they were not affiliated with the seller, but then later admitted he was one of their salespeople. The dealership blamed the seller with failing to transfer the vehicle into his own name, but they stopped making excuses when Martin, a retired lawyer, threatened to sue and report them to the Vehicle Sales Authority (VSA) and Insurance Corporation of British Columbia (ICBC). (Martin figures this may have been because 33 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada they had had run-ins with the VSA and ICBC before). They met with the dealership and got their money back in the exact same envelope; they never reported the curbsiders to the police or VSA since they had resolved the fraud themselves. “We wanted it [the car] to be perfect and right [since] we were tired of searching for so long” Emily explains why they ignored some of the warning signs. Martin adds that though this was their first time shopping for a used car online, they had been aware of the potential for curbsiding and fraud. “But we got taken in,” Martin says. “It happens to someone else, not to you; you’re too smart for that.” The seller was, he notes, very convincing. Case study #3 Fraudsters are constantly adopting new strategies that better their chances of scamming more and more consumers. A group of fraudsters apparently based in the U.S. put to use a new “quality over quantity” technique late 2012 that robbed at least five 116, and likely many more, 117 Canadian car buyers of a total of more than $225,000. 118 The gimmick involved making up a fake premium used car dealership website – so far they have allegedly run through the names Original Luxury Auto of Austin, Texas 119; Shine Auto Sales of Richmond, Illinois 120; Sprint Luxury Auto and Ambient Auto Center of Oklahoma City, Oklahoma; and Husen Original Autos of Phoenix, Arizona121 – and linking it to listings posted on Canadian classifieds websites like Kijiji.ca, Craigslist, AutoTrader and Wheels.ca. The vehicles they advertise are often high-end sports cars or luxury SUVS – “exotic vehicles worth big dollar amounts with big savings that make it worth [buying out-of-country],” says Terry O’Keefe, Manager of Communications with the Ontario Motor Vehicle Industry Council (OMVIC) – with details and photos swiped from legitimate dealership websites. “No one’s going to take the chance on a vehicle that’s only going to cost them five or six thousand dollars,” O’Keefe explains. “So these tend to be high-end luxury vehicles, sometimes exotics, that make the risk worth it for some people, the allure of saving five or six or ten or twelve thousand dollars by buying remotely” While John Cobb of the Oklahoma Used Motor Vehicle and Parts Authority notes he has seen scams of a similar nature in the state, this one is the most successful and widespread he has come across. 122 O’Keefe agrees the Ambient Auto Center scam is unique in its approach. “[Ambient] was the first time we’ve seen anything this elaborate, and this was a sophisticated scam. The websites looked very good, lots of testimonials, they tried to answer all the questions that anyone 116 http://www.omvic.on.ca/news/releases/news_release_2013-01-08.htm http://www.bbb.org/blog/2012/09/original-luxury-autos-a-possible-scam/ 118 email correspondence with John Cobb, Oklahoma Used Motor Vehicle and Parts Authority, December 18, 2012 119 email correspondence with victim 120 interview with Terry O’Keefe, Ontario Motor Vehicle Industry Council, December 14, 2012 121 http://www.omvic.on.ca/news/releases/news_release_2013-01-08.htm 122 email correspondence with John Cobb, Oklahoma Used Motor Vehicle and Parts Authority, December 18, 2012 117 34 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada that has concerns might have,” he says. “Basing Ambient in Oklahoma, it’s an awfully far place from Canada—you’re not going to drive down there to look at the car, so they thought of some ways around some common questions. They provide you with [a legitimate] VIN for the car— [the car] just happens to not be in their possession. They’ll provide you with a CARFAX report. They’ll even go to the point of allegedly creating phony emails from Canada border services agency.” O’Keefe related the story of one particular victim that wired Ambient more than $115,000 for a Ferrari. After he sent them a deposit, he received an email that was purportedly from Canada border services to Ambient saying they could not allow the further import of the vehicle unless the vehicle was paid for in full. Ambient forwarded the message to the consumer, saying, “We can’t get the car into Canada unless you wire us the rest of the money.” He did. The fraudsters typically ask for the cash via a wire transfer, though money may not be all they are after. O’Keefe notes they might also mine victims for their personal information, since this sort of information is in high demand on the black market—fraudsters generally use stolen identities to conduct other scams. He also explains that OMVIC is unable to prosecute or investigate fraud of this nature because it qualifies as a provincial offense, but not a criminal one. “Within two days of our story hitting the news, the phone numbers for Ambient went dead and the website went down. Shining a bright light on Ambient certainly made them move on. Do I think they’re gone? Absolutely not. They’ll just pop up again with a new website and a new name,” says O’Keefe. 123 123 interview with Terry O’Keefe, Ontario Motor Vehicle Industry Council, December 14, 2012 35 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada Recommendations The stakeholders interviewed were asked for changes they think could be made by classifieds websites, regulators or governments to reduce the amount of fraud Canadian consumers encounter when shopping for, or selling, used cars online. These recommendations are below. Future fraud detection technologies Some of the most promising developments in online fraud detection and prevention are, not surprisingly, technological. The representatives from classifieds websites the ACC spoke to explained they are, of course, constantly updating their filters and researching and developing new software that can better detect fraudulent listings. In order not to compromise the efficacy of these new technologies, they were unable to go into detail regarding how they work. Third-party developers, like Allen Atamer, Principal Engineer at Toronto-based LTAS Technologies, are working on similar technologies, as mentioned above. The Ontario Motor Vehicle Industry Council (OMVIC) has been using Atamer’s Harmari Curbsider Report software for more than a year, and he is in talks with other provincial regulators, as well as some American clients, who are considering trying it out as well. “[The Harmari Report] takes the long, arduous, tedious task of going through all those ads [looking for curbsiders], does it automatically and presents it in an easy-to-use format,” explains Atamer. 124 The Harmari Report software basically works by, as Atamer says, scanning websites for phone numbers repeated in several different listings and automatically collecting and collating them into a report, something most regulators and their investigators now do manually. Atamer is tweaking the software to counteract several tricks curbsiders used to avoid detection, and to generally improve the efficacy of the software. OMVIC regulators who have worked with the software complain only that it is too effective: “The problem is it’s very good at finding curbers, but you just wind up with a big pile of curbers to go after. You end up drowning in the program’s success,” says Carey Smith, OMVIC’s Director of Investigations. 125 Atamer points out there are other, yet-explored ways classifieds websites or regulators could better detect fraudsters using technology. “Nigerian scam”-type listings that use images stolen from legitimate listings could be caught using software that detects if a photo posted to the website has been used before elsewhere. “[When an image of a car is used on multiple websites,] the classifieds websites could talk to each other, saying ‘this picture was used here before,’” Atamer says, and then together determine which, if any, is a fraud and which the original is. Smith points out the third-party detection software regulators are using to detect curbsiders should be used by the classifieds websites so the listings never get up there in the first place. “If we have software that can identify potential curbsiders, they can, too. They should start to do a 124 125 interview with Allen Atamer, LTAS Technologies, August 19, 2012 interview with Carey Smith, Ontario Motor Vehicle Industry Council, October 3, 2012 36 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada better job of filtering their ads so the curbsiders aren’t on there,” he says. (It is possible, even likely, most classifieds are already working toward this end.) 126 Changes to classifieds website policies Besides constantly improving the technology they use to detect and prevent fraud, classifieds websites also regularly look at updates to their fraud handling policies. The stakeholders the ACC spoke to also had several suggestions for ways the websites could improve. “I’m a part of an organization of Canadian regulators, and we have been having talks with Kijiji about committing to [a new policy wherein] if they get so many repeats of the same phone numbers [in separate listings], they will inquire with that seller to see if they’re a dealer and whether they’re licensed,” explains Ian Christman of B.C.’s Vehicle Sales Authority (VSA). “And if they’re not, then they will start denying them [the ability to post to the site.]” The difficulties in this change in policy reside largely in how to enforce it without violating users’ privacy, he says. 127 OMVIC’s Smith suggested the websites could send automated messages to suspected curbsiders to let them know they’re being monitored, to deter curbsiding activity. 128 Consumers contacted via the Angus Reid-distributed survey also had suggestions for website policy changes, including banning users (or user IP [internet protocol] addresses) who have been reported to have demanded a non-refundable down payment on a vehicle they listed for sale. Another recommended increasing the number of times fraud detection tip sheets or warnings show up during the shopping or selling process. In general, it is apparent the classifieds websites need to commit more resources to fraud detection and prevention, specifically when it comes to curbsiding. Warnings regarding the possibility of a crime occurring do not absolve them of the fact their product enables that crime. It may also be advisable for classifieds websites to better communicate with consumers the measures they are taking and the resources they are committing, even if they cannot, of course, explain exactly how some of these measures work for security reasons. Changes to governmental policies The stakeholders’ suggestions in regards to how governmental or regulator policy could change revolved largely around tightening the loops that fraudsters and curbsiders tend most often to take advantage of. OMVIC’s Smith, for example, suggests changing the way cars are registered in Ontario. “Right now, it’s the buyer’s responsibility to change ownership into their name, but it’d be better if it was the seller’s responsibility, because right now curbsiders leave the old seller’s name on the 126 “Fraud: Global Threat and Growing.” Classified Intelligence Report 12.21 (2011) interview with Ian Christman, Motor Vehicle Sales Authority of B.C., October 5, 2012 128 interview with Carey Smith, Ontario Motor Vehicle Industry Council, October 3, 2012 127 37 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada ownership and don’t even register the cars in their names,” he says. 129 A change in governmental policy could also help trap the curbsiders that do register a vehicle in their name before passing it off to a victim, by tracking people who frequently register, then sell, multiple vehicles. “[The registration system is] so porous,” the Automobile Protection Agency’s George Iny is quoted in a Toronto Star article. “It [catching curbsiders] is not a priority at the Ministry [of Transportation]. They're not being accountable.” 130 Iny suggests – much like LTAS Technologies’ Atamer – that, in Ontario, that ministry could likely quite easily identify curbsiders through databases and broad lot inspections. The other major way in which regulation and legislation could be changed to clamp down on curbsiders is in how they are prosecuted and penalized. This does not necessarily mean increasing fines or penalties or making it harder for curbsiders to do business—the VSA’s approach in B.C. is instead to try to make it easier for curbsiders to comply with regulations and become certified dealers, and to mete out fines high enough to discourage them from repeating the crime, but not so high that the charge is too often challenged by the curbsider in court, a problem OMVIC is increasingly facing in Ontario. “OMVIC went for increasing the fines progressively, but those fines have had a different effect than they thought—when that happened, everyone disputed the tickets, and that increased [OMVIC’s] legal costs, and about 80 percent of their investigators’ time is dealing with curbers,” says Christman of the VSA. “Our view is to create a better regulatory method to deal with it. We can increase fines, but not to the extent they have—enough to make it hurt, but not enough to make them wanting to go running to the court every time. We’re also thinking of having the registrar issue [to a curbsider] what’s known as a compliance order, with an administrative penalty and the right to an administrative hearing before the registrar. Proof required is lower, it’s on the civil burden [as opposed to the criminal burden].” The VSA is generally looking at new ways to penalize curbsiders, outside of criminal prosecution. “Under the Business Practices Act, which is where the registrar gets his authority for these compliance orders and penalties, it also allows the registrar to file them under the B.C. Supreme Court, and once filed they become court orders,” Christman explains. “Those can be enforced as court orders, which means I can use the Court Orders Enforcement Act to start proceedings for a person’s paycheque, against their homes and so forth. It’s a civil and administrative way to deal with it, and moves it away from the criminal justice system.” 131 They are also working together with other agencies to corner the curbsider. “Curbsiders tend to sell from a home when they’re not licensed or zoned to do so, so we talk to the bylaws department to deal with them,” Christman offers an example. “Recently, we started piloting with the Canada Revenue Agency [...] because usually if they’re curbsiding, they’re under-reporting taxes, and that has also started working.” Vehicle history report provider CarProof is developing a product – currently being tested in London, Ontario – that similarly ties curbsiders to instances 129 ibid. Mark Toljagic, “Curbsiding: Unsafe at Any Price.” Toronto Star April 9, 2011 131 interview with Ian Christman, Motor Vehicle Sales Authority of B.C., October 5, 2012 130 38 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada of insurance fraud via a database, since “the correlation between insurance fraud and curbsiding and organized crime is extremely high,” says CarProof’s Shawn Vording. “Typically the criminals that are involved in staging collisions are also involved in curbsiding, they’re sourcing the cars that way.” 132 Classifieds website and regulator cooperation Regulators and classifieds websites have more and more frequently been cooperating and sharing information that can help the regulator to track down and prosecute curbsiders; this is true especially in Alberta, where AMVIC, who advertise with Kijiji, have been working together with that website for more than a year. Cooperation between the classifieds websites themselves, however, could improve. “While eBay Motors [Kijiji’s parent company] in the U.S. has been in touch with AutoTrader in the U.S. in regards to fraud prevention, in Canada we’re not,” says Christian Jasserrand of Kijiji.ca. 133 “We don’t work with [rival companies] actually, not currently, and that’s not been a kind of deliberate decision, that’s just been something which hasn’t come about,” Ian MacDonald of AutoTrader concurs. “In the U.K., when I was there, AutoTrader actually created a kind of knowledgesharing forum or organization called VSTAG, and that was a combination of all the different players, whether they are competitors or not, kind of working together on the fraud issue in the U.K. market specifically. There’s nothing like that I know of in Canada.” 134 Information that could be shared between websites for the benefit of consumers include fraud detection and prevention techniques and software; information on listings (for example, the theft of images of cars from legitimate listings for use in fraudulent ones, as mentioned above); and information on users identified as fraudsters, to stop them from simply hopping from site to site when caught. There may be several difficulties with these rival companies working together – better fraud protection gives one a competitive edge over another, something they would lose when fraud prevention techniques or fraudster information is shared – but there should be way work around these. “We haven’t seen a need for [this sort of cooperation], plus they’re a competitor, so it would have been difficult for us to approach them and say, ‘Hey, we’re going to cooperate on something like fraud,’ when in fact the relationship is a little bit tense,” Jasserand says of AutoTrader. MacDonald is a little more optimistic. “Something like that could work here potentially. It’s all about the dedication certain brands show to this issue.” He points out that if a single website refused to cooperate in a knowledge-sharing organization like VSTAG, fraudsters could, quite easily, simply congregate there. “There needs to be kind of a broad, industry-wide understanding of the importance of the issue and the investment and dedication that is required to mitigate those risks across the industry. Maybe that isn’t there, and that’s why that organization [like VSTAG] 132 interview with Shawn Vording, CarProof, August 9, 2012 interview with Christian Jasserand, Kijiji Canada, October 29, 2012 134 interview with Ian MacDonald, AutoTrader.ca, November 14, 2012 133 39 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada isn’t there, but in principle, I think it’s something that could work, sure, if everyone was dedicated to it.” 135 Better cooperation between regulators and provincial ministries could also help in tracking curbsiders and fraudsters. Most provincial regulators work together via a nation-wide regulator organization – meeting occasionally for industry conferences and the like – but inter-province vehicle titling and tracking could still use development. “[Online fraud prevention] is not something that can be done state-by-state or province-by-province. Because the Internet is international scope in terms of boundaries, it’s something that needs to be done at a national level,” says the VSA’s Christman. “We need to have some national standards regarding web advertising, and I think the competition bureau can do that. Constitutionally, the federal government deals with all matters that are cross-jurisdictional, and I think we may need to say that internet advertising, because it crosses all international boundaries, needs to be regulated federally, and some federal standards need to be put in place, including impositions on web hosters or people who do these websites in terms of reporting.” 136 Atamer suggested provincial ministries could work together to build a database similar to the NMVTIS (National Motor Vehicle Titling Information System) in the U.S., which lets each U.S. state communicate with others regarding a vehicle VIN and title. 137 This could help in the interprovince tracking of salvage title cars, for example. Changes to consumer awareness efforts Both regulators and classifieds websites constantly run large-scale consumer awareness campaigns giving them tips on how to detect and avoid curbsiders and fraudsters, but, according to the results of our ACC-Angus Reid consumer survey, most consumers are still either unaware of online used car sales fraud or do not consider it a threat to their online classifieds shopping or selling experience. “As much as we can do ourselves from a technology or moderation point-ofview, ultimately the most powerful thing is actually educating people so they themselves can recognize things that aren’t right if they ever are unfortunate enough to encounter a fraudulent ad or email,” says AutoTrader’s MacDonald. 138 Consumers may be unaware of how prevalent online used car sales fraud and curbsiding is in part because most victims do not report the crime, instead keeping it to themselves out of embarrassment. “The vast, vast majority of fraud is not reported to us, and generally speaking, it’s not being reported to anyone,” says Daniel Williams of the Canadian Anti-Fraud Centre. 139 “The number of victims who blame themselves once they’ve been had is amazing, and they just write it off as a lesson learned. In a lot of cases they’re embarrassed about being defrauded and they tell no one, no one learns from their mistake,” he says. “In many cases, the best that we can hope for – and this is an amazing thing to hope for – is that a victim goes extremely public with 135 ibid. interview with Ian Christman, Motor Vehicle Sales Authority of B.C., October 5, 2012 137 interview with Allen Atamer, LTAS Technologies, August 19, 2012 138 interview with Ian MacDonald, AutoTrader.ca, November 14, 2012 139 interview with Daniel Williams, Canadian Anti-Fraud Centre, November 3, 2012 136 40 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada what’s happened to them, thereby truly inoculating their own circle of friends and families, people who they trust who will listen to the story of what happened.” It may be possible to counter this stigma by working to relieve notions of “victim-blaming” with these fraud awareness campaigns, and to emphasize exactly how prevalent online used car sales fraud is, and how convincing fraudsters and curbsiders can be. Publicizing regulators’ and classifieds websites’ successes in finding and convicting curbsiders and fraudsters may also encourage them to report the crime. “One of the key problems with being a victim of a cybercrime is that there is no obvious way of getting help. If a car is broken into, the police can at least see and acknowledge the crime and the loss [and] at least the case has been taken seriously and there is therefore a motivation to report it,” says information security expert Wendy Goucher. “But what is the motivational reward in reporting cybercrime? The statistics demonstrate that the criminal is unlikely be brought to trial, so positive reinforcement is absent. In fact, there is a risk that victims will be labelled, both by themselves and others, as fools for falling for the temptation in the first place. So positive reinforcement is replaced by negative reinforcement, and why would anyone do something that can lead only to bad results?” 140 Fraud awareness campaigns can be instrumental in removing this negative reinforcement and encouraging the reporting of online used car sales fraud. 140 Wendy Goucher, “Being a Cybercrime Victim.” Computer Fraud and Security (2010): 16-17 41 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada Conclusions As the popularity of purchasing and selling used cars via classifieds websites continues to grow in Canada, the number of fraud victims will only swell. The impact on the Canadian economy will similarly expand, unless measures are taken to increase fraud and curbsider detection, prevention and awareness. Several of those measures are reviewed in this study, and based on that review, the ACC recommends: 1) regulators and websites continue to invest in the development of new fraud detection technologies, and are supplied with additional funding if necessary; 2) provincial authorities review and potentially revise the legislation around fraudster and curbsider prosecution and penalization; 3) and that all stakeholders work to remove the stigma around fraud victimization and encourage fraud reporting by launching awareness campaigns that counteract too-prevalent “victimblaming” attitudes toward online fraud. Most importantly, improving fraud and curbsider detection and prevention methods will require better cooperation between provincial ministries and regulators; between classifieds websites; and between regulators and websites. Because online fraud transcends provincial and even national borders, it may be necessary for the provinces to petition the federal government for some form of national oversight, legislation or organization. “I don’t see this trend [in online used car fraud] ending. I think technology is making it easier and easier for people who want to harm others through fraud to do it,” says OMVIC’s Terry O’Keefe. “It’s going to be a growing problem. It’s going to require cooperation between not just jurisdictions, but between countries.” 42 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada Appendix 43 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada Research team Nicholas Maronese Mr. Maronese organized the research and composition of the report, conducted interviews with stakeholders and coordinated the project’s operation. As a freelance automotive writer and researcher, Mr. Maronese’s work has appeared extensively in Sympatico.ca Autos, as well as the Toronto Star, reaching hundreds of thousands of Canadians. Mr. Maronese has an Honours Bachelor’s degree in Professional Writing from York University in Toronto, Ontario. Mohamed Bouchama Mr. Bouchama helped in the development of the report methodology and conducted several interviews. Mr. Bouchama is Ontario's best-known automobile consumer advocate and a Director with Car Help Canada, also known as the Automobile Consumer Coalition (ACC). For over two decades, and on a daily basis, he has assisted vehicle buyers in finding the lowest car prices, and has listened to and helped thousands of consumers with virtually every aspect of vehicle ownership. His knowledge of the vehicle marketplace in Ontario from the consumer’s perspective is unparalleled. As a consumer advocate, Mr. Bouchama has hosted automobile-related programs on television and radio for fifteen years and has granted hundreds of media interviews during his career; he has been featured in the Toronto Star, the Globe and Mail, and the Toronto Sun. Mr. Bouchama has also lobbied on behalf of vehicle consumers and advised governments at the federal and provincial levels. Peter Silverman Dr. Silverman (PhD, Toronto; Master of Arts, UBC) is one of the report methodologists. Dr. Silverman is a Canadian television business journalist based in Toronto, Ontario. His journalism career began in 1974 as a reporter for Global Television Network; in 1981, he moved to CityTV, where he became a reporter for that station's CityPulse news program (now known as CityNews). He was host of Silverman Helps, an ombudsman-type feature for consumers between 1989 and 2008. In September 2008, Silverman joined Toronto radio station Newstalk 1010 to host a Saturday morning radio show called The Peter Silverman Show. 44 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada He has also worked as an advertising executive entrepreneur and as a professor at the University of Toronto. Dr. Silverman won the Man of the Year Award from the Consumers' Choice Award for Business Excellence in 2006; he has also received awards from the Toronto chapter of Association of Certified Fraud Examiners, and has also been appointed to the Order of Ontario. Thomas M. Prymak Dr. Prymak (PhD, Toronto; Bachelor of Arts, Master of Arts, Manitoba) is one of the report methodologists. Dr. Prymak has been writing, editing, and publishing in various fields for over 25 years. His personal bibliography includes three books and over 125 articles published in various peerreviewed journals, as well as in magazines and newspapers. Two of his books were published by the country’s most prestigious academic publisher, the University of Toronto Press. Besides working in print, Dr. Prymak has experience in both television and radio. As early as the 1970s, he produced and hosted a program on non-profit community TV in Winnipeg, Manitoba. He has occasionally been interviewed on both TV and radio regarding issues of public interest. 45 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada Bibliography scholarly articles and studies Dong, Fei et al. “Combating Online In-Auction Fraud: Clues, Techniques and Challenges.” Computer Science Review 3 (2009): 245-258. “Fraud: Global Threat and Growing.” Classified Intelligence Report [AIM Group] 12.21 (November 2011): 1-22. Goucher, Wendy. “Being a Cybercrime Victim.” Computer Fraud and Security (November 2010): 16-18. Head, Milena and Khaled Hassanein. “Trust in e-Commerce: Evaluating the Impact of ThirdParty Seals” Quarterly Journal of Electronic Commerce 3.3 (2002): 307-325. “Internet Auction Fraud.” Commercial Business Intelligence Inc. (May 2001) Lee, Byungtae et al. “Empirical Analysis of Online Auction Fraud: Credit Card Phantom Transactions.” Expert Systems with Applications 37 (2010): 2991-2999. Schultze, Ulrike and Traci Carte. “Contextualizing Usage Research for Interactive Technology: The Case of Car E-Tailing.” The DATA BASE for Advances in Information Systems 38.1 (February 2007): 29-59. mass-media articles “B.C. Man Arrested in Internet Vintage Car Scam.” Postmedia News 6 August 2008. “CarProof Reports to Roll Out Across Kijiji Canada's Autos Classifieds.” Canada Newswire, 5 January 2011. Cohen, Joel. “Be Wary of Car-buying Scams on the Internet.” Toronto Star 11 September 2010. “Edmunds.com Offers Tips on How to Safely Sell a Used Car.” Manufacturing Close-Up 28 April 2011. Lancaster, Jason. “Poll: Used-Vehicle Buyers Prefer Internet Over Dealer Lots.” Ward's Dealer Business December 2009. 46 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada “Ontario Motor Vehicle Industry Council Warns Consumers To Avoid Curbsiders And Fraudsters By Buying Vehicles Only From Ontario-Registered Dealers.” Canada Newswire 14 October 2010. Purdy, Chris. “Ad Scam Uses Name, Photo of Soldier Killed in Afghanistan.” Globe and Mail 11 November 2008. “Scheme to Sell Stolen Cars on Craigslist Nets 15 Month Term for Vancouver Man.” Canadian Press 28 March 2012. Toljagic, Mark. “Curbsiding: Unsafe at Any Price.” Toronto Star 9 April 2011. Toljagic, Mark. “Illegal Sellers Exploit Online: How to Tell the Difference.” Toronto Star 16 October 2010. Toljagic, Mark. “Taken for a Ride; Think That Online Car Ad Is a Steal? Chances Are, It Is. But Used-car Watchdog Bob Pierce Cautions that on the Web, It May Be You Who's the Mark.” Toronto Star 10 October 2009. Van Alphen, Tony. “‘Curbsiding’ Soaring in GTA, Study Shows.” Toronto Star 2 March 2012. legislation Alberta Fair Trading Act (sections 6; 7; 104; 164) Business Practices and Consumer Protection Act or Motor Dealer Act of B.C (chapter 316, part 3, section 39) Ontario Electronic Commerce Act (chapter 17) case studies Regina V. Ramin Karamali (British Columbia, 2006) 47 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada Stakeholder Contact List classifieds sites government and industry bodies Kijiji.ca Autos http://www.kijiji.ca/autos eBay International Inc. Christian Jasserand, head of customer support Canada Anti-Fraud Centre www.antifraudcentre.ca Daniel Williams, media relations Jeff Thomson Craigslist craigslist.ca/cta craigslist, inc. Toronto Police Services, Financial Crimes Unit 416-808-7300 AutoTRADER.ca http://www.autotrader.ca Trader Corporation Ian MacDonald, director, consumer marketing Carpages.ca http://www.carpages.ca/ Autopath Technologies Inc. driving.ca www.driving.ca/ canada.com Postmedia Network Inc. Used123.ca (Auto123.com) http://www.used123.ca/ Evolio Autonet.ca http://www.autonet.ca/ Canoe Network Quebecor Ontario Motor Vehicle Industry Council (OMVIC) http://www.omvic.on.ca/ Carl Compton, director Casey Smith, director of investigations Terry O’Keefe, manager of communications, media relations and education Used Car Dealers Association of Ontario (UCDA) http://www.ucda.ca/ Motor Vehicles Sales Authority of B.C. (VSA) http://www.mvsabc.com/ http://mdcbc.com/ Ian Christman, registrar Alberta Motor Vehicle Industry Council (AMVIC) http://www.amvic.org/ John Bachinski, executive director Bob Knight, director of investigations UsedCarsCanada.com http://www.usedcarscanada.com/ Strathcom Media Office de la Protection du Consommateur (OPC) http://www.opc.gouv.qc.ca/ Jacques jr Fugère, unité de coordination et de soutien aux activités MonsterAuto.ca http://www.monsterauto.ca/ [email protected] Internet Crime Complaint Center [U.S.—FBI] http://www.ic3.gov/ Elizabeth Walling, Internet crime analyst 48 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada Oklahoma Used Motor Vehicle and Parts Authority (UMVPA) John Cobb, investigator research and informational groups other Georgian College Automotive Business School of Canada Jennifer Sheremeto, marketing specialist CarProof Paul W. Anthony, CEO and president Joe Varkey, vice-president marketing Louis Petro Odette School of Business, University of Windsor Harmari by LTAS Technologies www.harmari.com Allen Atamer AUTO21 Network of Centres of Excellence Stephanie Campeau, director of public affairs and communications R.L. Polk & Co. Automotive data and marketing solutions Lee Meadows, account specialist 49 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada Consumer survey questionnaire AUTOMOBLE CONSUMER COALITION Preliminary Questionnaire 1,000 total respondents, 10-minute interview, Used car owners/buyers Q1. Within the past year, have you considered purchasing or selling a vehicle using an online classifieds website? [MULTIPLE CHOICE, UNLESS No IS CHOSEN] Yes, I considered purchasing a vehicle Yes, I considered selling my vehicle No, I did not consider either [EXCLUSIVE] If “Yes”, ask Q2a If No, ask Q2b Q2a. Which online classifieds websites did you browse when you considered purchasing or selling a vehicle? Please select all that apply. [MULTIPLE CHOICE] eBay Motors Kijiji AutoTrader Craigslist Other [WRITE-IN] Q2b. Did the possibility of online fraud affect whether or not you bought or sold a vehicle online? [SINGLE CHOICE] Definitely affected Probably affected Probably did not affect Definitely did not affect Not sure Q3. Have you purchased or sold a vehicle using an online classifieds website within the past year? [SINGLE CHOICE] Yes, I have No, I have not If “Yes”, ask go to Q4. 50 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada If “No”, TERMINATE Q4. Which online classifieds websites did you browse before purchasing or selling a vehicle? Please select all that apply. [MULTIPLE CHOICE] eBay Motors Kijiji AutoTrader Craigslist Other [WRITE-IN] Q5. Which website did you buy your vehicle from or sell it on? [MULTIPLE CHOICE] eBay Motors Kijiji AutoTrader Craigslist Other [WRITE-IN] Q6. Please describe the vehicle you purchased or sold by filling out the form below. [FORM] Year: [PROVIDE BOX, NUMERIC, FROM 1950 TO 2012] Make: [PROVIDE BOX, WRITE-IN] Model: [PROVIDE BOX, WRITE-IN] Condition: Single Choice, Used / New Bought from / Sold to: Single Choice, Bought from / Sold to Price: [PROVIDE BOX, NUMERIC] Q7. Did you use the classifieds website’s recommended payment method? [SINGLE CHOICE] Yes, I did No, I did not Q8. Which payment method did you use? Please type your response in the box below. [PROVIDE BOX] Q9. Did you do any of the following prior to making the purchasing or selling decision? [ROWS] Read the website’s policy on fraud protection 51 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada Research the types of online fraud prior to making the purchasing or selling decision [COLUMNS] Yes, I did No, I did not If “Yes” to “Researched the types of online fraud prior to making the purchasing or selling decision”, ask Q9a. Q9a. Which resources did you review? Please type your response in the box below. [PROVIDE BOX] Q10. Did you encounter any type of online fraud while shopping for or selling a car via a classifieds website? Please select all that apply. [MULTIPLE CHOICE] Bought from a “curbsider” or dealer posing as private seller Ad placed by dealer posing as private seller online, but who identified as a dealer at their location or over the phone Paid a seller for a car that was not delivered Paid a seller for a car I was unable to view in person beforehand, and the car delivered was not the same as the one advertised Paid a buyer a refund because their cashier’s cheque was above my selling price and later found out the cashier’s cheque was fraudulent Contacted by a buyer whom I recognized was a scammer Other [WRITE-IN] None of these [EXCLUSIVE] If “None of these”, TERMINATE. All others, ask Q10a, Q11, Q12 and Q13. Q10a. Please describe in detail the type of fraud you encountered. Please type your response in the box below. [PROVIDE BOX] Q11. Was your experience with fraud resolved? [SINGLE CHOICE] Yes, it was No, it was not. Q12. Which actions did you take to deal with the fraud you encountered? Please type your response in the box below. 52 Automobile Consumer Coalition Research Report 2012-2013 Classifieds Websites and Used Car Purchases in Canada [PROVIDE BOX] Q13. Are you satisfied or dissatisfied with the arbitration or mediation process of the parties involved in your fraud’s resolution or attempted resolution? [SINGLE CHOICE] Very satisfied Moderately satisfied Moderately dissatisfied Very dissatisfied Not sure FINAL. Every year, thousands of Canadian car buyers, through no fault of their own, become victims of internet-based fraud. This study is part of an effort to better protect consumers from this sort of fraud. If you’ve purchased or sold a car via an online classifieds website and have been a victim of fraud, the Automobile Consumer Coalition would like to interview you about your experience. Please email [email protected]. Your name and personal details will remain confidential. ==30== 53 Preliminary Report Page 1 of 3 AUTOMOBLE CONSUMER COALITION Report of Findings From November 13 to November 19, 2012, Angus Reid Public Opinion conducted an online survey among 1,006 Canadian adults who are Angus Reid Forum panellists and have purchased or sold a vehicle using an online classifieds website within the past year. The margin of error—which measures sampling variability—is +/- 3.1%, 19 times out of 20. Discrepancies in or between totals are due to rounding. Within the past year, have you considered purchasing or selling a vehicle using an online classifieds website? - Almost two-thirds of respondents (64%) considered purchasing a vehicle using an online classifieds website; half (50%) considered selling their vehicle. British Columbians (71%) and Ontarians (69%) more likely to have considered purchasing a vehicle using an online classifieds website. Asked to respondents who considered a transaction: Which online classifieds websites did you browse when you considered purchasing or selling a vehicle? Please select all that apply. - Kijiji was by far the most browsed website (79%), followed by AutoTrader (39%), Craigslist (26%) and eBay Motors (10%). LesPac was very popular in Quebec (62%, second only to Kijiji). Asked to respondents who did not consider a transaction: Did the possibility of online fraud affect whether or not you bought or sold a vehicle online? - Three-in-ten respondents (29%) say the possibility of fraud "definitely" or "probably" affected their decision. Fraud concerns were more prevalent in British Columbia (41%). Which online classifieds websites did you browse before purchasing or selling a vehicle? Please select all that apply. - Once again, Kijiji was the top choice (76%), followed by AutoTrader (35%), and Craigslist (23%). LesPac is the second option in Quebec (55%, behind Kijiji). British Columbians pick Craigslist first (69%). Which website did you buy your vehicle from or sell it on? - In the end, three-in-five sellers/buyers (60%) relied on Kijiji, while less than 15 per cent used other websites. Two-in-five Quebecers (40%) relied on LesPAC, almost half of British Columbians (46%) on Craigslist. CONTACT: Mario Canseco, Vice President, Angus Reid Public Opinion, 877-730-3570, [email protected] Preliminary Report Page 2 of 3 Please describe the vehicle you purchased or sold by filling out the form below. - Year: Most cars purchased or sold were 1996-2000 (23%) or 2001-2003 (19%). Make: 15% of the cars purchases or sold were Ford, 10% were Honda, 9% Chevrolet, 9% Toyota.Condition: Only three per cent of the cars purchased or sold were new, the rest were used. Bought from / Sold to: Four-in-five cars purchased or sold (80%) involved a private seller, only 20% a dealer. Price: About two-in-five purchases or sales (39%) cost between $2,001 and $8,000. Did you use the classifieds website’s recommended payment method? - Only one-in-four respondents (25%) used the recommended payment method. Respondents 18-to-34 (40%) were more likely to do so than those aged 35-to-54 (21%) and those over the age of 55 (26%). Which payment method did you use? Please type your response in the box below. - Almost two thirds (65%) used cash, 22% used a cheque; just 5% relied on credit. Did you do any of the following prior to making the purchasing or selling decision? - A majority (60%) did not read the website’s policy on fraud protection or research the types of online fraud prior to making the purchasing or selling decision (64%). Older respondents are more likely to have taken precautions than middle-aged and younger respondents. Asked to respondents who researched the types of online fraud prior to making the purchasing or selling decision: Which resources did you review? Please type your response in the box below. - Most respondents sought information on the Internet or on the policies of the websites where they saw the vehicles. Did you encounter any type of online fraud while shopping for or selling a car via a classifieds website? Please select all that apply. - Four-in-five (80%) did not encounter any type of fraud. The highest incidence of fraudulent behaviour observed is people being contacted by a buyer who was recognized a scammer (13%), followed by an ad placed by dealer posing as private seller online, but who identified as a dealer at their location or over the phone (5%). Asked to respondents who encountered fraud: Please describe in detail the type of fraud you encountered. Please type your response in the box below. - Roughly half of respondents (48%) expressed concerns about the buyer or seller, while 20% faced problems with shipping and/or delivery, 15% had problems with either price/cost, or vehicle condition and inspection. CONTACT: Mario Canseco, Vice President, Angus Reid Public Opinion, 877-730-3570, [email protected] Preliminary Report Page 3 of 3 Asked to respondents who encountered fraud: Was your experience with fraud resolved? - Four-in-five respondents (77%) say their experience with fraud was resolved. Asked to respondents who encountered fraud: Are you satisfied or dissatisfied with the arbitration or mediation process of the parties involved in your fraud’s resolution or attempted resolution? - Two-in-five (40%) were satisfied with the process; 12 per cent were dissatisfied, the rest are undecided. ==30== CONTACT: Mario Canseco, Vice President, Angus Reid Public Opinion, 877-730-3570, [email protected] Table 1 Q1. Within the past year, have you considered purchasing or selling a vehicle using an online classifieds website? Gender BASE: All Respondents Yes, I considered purchasing a vehicle Total (A) 1006 642 64% Male (B) Age Female (C) 18-34 (D) 405 231 57% 120 79 66% 209 52% 35-54 (E) Region 55+ (F) Yes, I considered selling my vehicle 507 50% 601 411 68% C 298 50% 459 269 59% 64 53% 427 294 69% F 208 49% No, I did not consider either 129 13% 68 11% 61 15% 15 13% 49 11% 65 14% NET: Yes 877 87% 533 89% 344 85% 105 88% 378 89% 394 86% 235 51% BC (G) 238 170 71% HK 128 54% J 22 9% 216 91% HK Comparison Groups: BC/DEF/GHIJKL/MNO/PQR/STUV/WX/YZ Independent T-Test for Means (equal variances), Independent Z-Test for Percentages (pooled proportions) Uppercase letters indicate significance at the 95% level. ACC Custom Express Vision Critical Nov. 22, 2012 D AB (H) 141 77 55% 73 52% 23 16% G 118 84% SK/MB (I) Education ON (J) QC (K) 104 66 63% K 58 56% J 9 9% 271 187 69% HK 119 44% 149 72 48% 34 13% 95 91% K 237 87% 28 19% GI 121 81% 76 51% ATL (L) Household Income Purchased/Sold Vehicle Using Online Classifieds Impact of Online Fraud (Q2b) $50,00 0 To Less Definite Probabl Probabl Definite Top 2 Bottom College Univ Than ly y y Did ly Did Box 2 Box HS Or / Tech Degree <$50,0 $100,0 $100,0 Affecte Affecte Not Not Affecte Did Not Less School + 00 00 00+ d d Affect Affect d Affect (M) (N) (O) (P) (Q) (R) (S) (T) (U) (V) (W) (X) Yes, I Have (Y) No, I Have Not (Z) 103 70 68% HK 53 51% 183 106 58% 527 340 65% 296 196 66% 273 166 61% 409 262 64% 194 134 69% 16 - 21 - 28 - 55 - 37 - 83 - 1006 642 64% - 96 52% 262 50% 149 50% 136 50% 211 52% 97 50% - - - - - - 507 50% - 13 13% 30 16% 68 13% 31 10% 40 15% 54 13% 18 9% 16 100% 21 100% 28 100% 55 100% 37 100% 83 100% 129 13% - 90 87% 153 84% 459 87% 265 90% 233 85% 355 87% 176 91% - - - - - - 877 87% - Table 2 Q2a. Which online classifieds websites did you browse when you considered purchasing or selling a vehicle? Gender Total (A) BASE: Considered purchasing or selling a vehicle in Q1 Kijiji Male (B) Age Female (C) 18-34 (D) Region 35-54 (E) 55+ (F) BC (G) AB (H) SK/MB (I) ON (J) QC (K) 877 696 79% 533 422 79% 344 274 80% 105 83 79% 378 299 79% 394 314 80% 216 123 57% AutoTrader 343 39% 220 41% 123 36% 228 26% 146 27% 82 24% 159 42% F 100 26% 134 34% Craigslist 50 48% F 34 32% eBay Motors 85 10% 73 14% C 44 8% 12 3% 7 7% 36 10% 42 11% 78 36% K 158 73% HIJKL 23 11% 32 9% 12 11% 34 9% 30 8% - - - - 13 2% 7 1% 4 1% 6 1% 6 1% 4 1% 4 1% 2 0% 2 0% 2 0% - 6 2% 2 1% 4 1% 2 1% 1 0% 1 0% 1 0% 2 1% 1 0% 1 0% 3 1% 1 0% 1 0% 2 1% 1 0% - 1 1% - 9 2% - - - 6 2% 2 1% 3 1% - 19 9% 2 1% 5 2% 8 4% - - - 9 2% 9 2% 2 1% 6 2% 3 1% 5 1% 3 1% 2 1% 3 1% 1 0% - 1 1% - 1 1% - - 1 0% 1 0% - - - - LesPAC 76 9% Used Victoria 19 2% 9 1% 8 1% 8 1% 7 1% 5 1% 5 1% 4 0% 3 0% 3 0% 3 0% 3 0% 2 0% 2 0% 2 0% 1 0% 1 0% 1 0% Dealership / dealer site Buy & Sell Castanet Used Regina E Brandon Local Classified NL Classified Annonces Auto Hebdo Used Ottawa Used PEI Car Pages Concessionaive Pembina Valley Online Used (unspecified) Used Everywhere Used Vancouver 2 0% 1 0% 1 0% 1 0% - 1 1% 1 1% 1 1% 1 1% - 2 1% 2 1% 2 1% 2 1% 3 1% 1 0% 1 0% - 94 24% 118 112 95% GIJK 48 41% KL 9 8% Education 9 8% 95 237 82 199 86% 84% G G 39 145 41% 61% KL GHIKL 6 44 6% 19% HIKL 8 24 8% 10% 153 121 79% 459 366 80% 265 209 79% 48 31% 165 36% 9 7% 90 83 92% GK 23 26% K 2 2% 28 18% 116 25% 13 11% 8 9% 11 7% 48 10% 130 49% MN 84 32% M 26 10% 75 62% L - 1 1% 35 8% 15 6% 5 2% - - - 26 17% NO 2 1% - - - - 3 3% - - - 7 3% 3 1% 1 0% - - - - - - - - 1 1% - - 2 1% 1 1% 1 1% - 10 2% 6 1% 7 2% 8 2% 5 1% 3 1% 3 1% 3 1% 3 1% 1 0% 2 0% 2 0% - - - 1 0% - - 7 7% 5 5% 3 3% - - - - - - - - - - - - - - - - 3 1% - - - - - 1 0% 1 0% 1 0% 1 0% 1 0% - - - - - 1 0% 1 0% 1 0% - 2 2% - - - - - - 3 2% 3 2% - - 4 4% - - 1 1% - 3 3% - - - - 2 2% - - - - 2 1% 1 1% - - - - - - - - - 2 1% - - Impact of Online Fraud (Q2b) $50,00 0 To Less Definite Probabl Probabl Definite Top 2 Bottom College Univ Than ly y y Did ly Did Box 2 Box HS Or / Tech Degree <$50,0 $100,0 $100,0 Affecte Affecte Not Not Affecte Did Not Less School + 00 00 00+ d d Affect Affect d Affect (M) (N) (O) (P) (Q) (R) (S) (T) (U) (V) (W) (X) ATL (L) 121 97 80% G 10 8% Household Income Purchased/Sold Vehicle Using Online Classifieds - - 1 0% 1 0% 1 0% 1 0% 1 0% 1 0% 1 0% 1 0% 1 0% 2 1% 1 0% - 233 197 85% R 72 31% Yes, I Have (Y) No, I Have Not (Z) 176 126 72% - - - - - - 877 696 79% - 88 50% PQ 48 27% - - - - - - 343 39% - 56 24% 355 286 81% R 140 39% P 99 28% - - - - - - 228 26% - 14 6% 35 10% - - - - - - 85 10% - 27 12% R 4 2% 2 1% 4 2% 2 1% 2 1% - 36 10% R 7 2% 3 1% 1 0% 4 1% 3 1% 2 1% 2 1% 3 1% - 25 14% P 7 4% - - - - - - 76 9% - 7 4% 3 2% 1 1% 1 1% 1 1% 2 1% 2 1% - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 1 1% 1 1% - - - - - - - - - - - - - - - - - - - 1 0% 1 0% - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 19 2% 9 1% 8 1% 8 1% 7 1% 5 1% 5 1% 4 0% 3 0% 3 0% 3 0% 3 0% 2 0% 2 0% 2 0% 1 0% 1 0% 1 0% 1 0% 1 0% 3 1% 1 0% 2 1% 1 0% 1 0% 1 0% - 2 1% 1 0% 2 1% 1 0% - - Other mentions 23 3% 14 3% 9 3% - 8 2% 15 4% 11 5% HJ Comparison Groups: BC/DEF/GHIJKL/MNO/PQR/STUV/WX/YZ Independent T-Test for Means (equal variances), Independent Z-Test for Percentages (pooled proportions) Uppercase letters indicate significance at the 95% level. ACC Custom Express Vision Critical Nov. 22, 2012 D 1 1% 4 4% J 2 1% 4 3% 1 1% 6 4% 9 2% 8 3% 8 3% 8 2% 5 3% - - - - - - 23 3% - Table 3 Q2b. Did the possibility of online fraud affect whether or not you bought or sold a vehicle online? Gender Total (A) BASE: Did not consider purchasing or selling a vehicle in Q1 Definitely affected Probably affected Probably did not affect Definitely did not affect Not sure NET: Top 2 Box NET: Bottom 2 Box Male (B) Age Female (C) 18-34 (D) 35-54 (E) Region 55+ (F) BC (G) 129 16 12% 68 8 12% 61 8 13% 15 1 7% 49 7 14% 65 8 12% 21 16% 28 22% 13 19% 16 24% 8 13% 12 20% 2 13% 3 20% 9 18% 10 20% 10 15% 15 23% 22 5 23% K 4 18% 1 5% 55 43% 9 7% 37 29% 29 43% 2 3% 21 31% 26 43% 7 11% 16 26% 8 53% 1 7% 3 20% 18 37% 5 10% 16 33% 29 45% 3 5% 18 28% 83 64% 45 66% 38 62% 11 73% 28 57% 44 68% AB (H) SK/MB (I) Education ON (J) QC (K) ATL (L) Household Income Impact of Online Fraud (Q2b) $50,00 0 To Less Definite Probabl Probabl Definite Top 2 Bottom College Univ Than ly y y Did ly Did Box 2 Box HS Or / Tech Degree <$50,0 $100,0 $100,0 Affecte Affecte Not Not Affecte Did Not Less School + 00 00 00+ d d Affect Affect d Affect (M) (N) (O) (P) (Q) (R) (S) (T) (U) (V) (W) (X) 23 3 13% 9 1 11% 34 3 9% 28 1 4% 13 3 23% 30 3 10% 68 11 16% 31 2 6% 40 3 8% 54 4 7% 2 22% 3 33% G 3 33% - 6 18% 6 18% 6 21% 5 18% 2 15% 3 23% - 16 24% 11 16% 5 16% 6 19% 7 18% 7 18% 8 15% 15 28% 10 45% 2 9% 9 41% 1 4% 10 43% GJK 7 30% 2 9% 4 17% 3 33% 16 47% 3 9% 9 26% 15 54% 1 4% 7 25% 4 31% 1 8% 5 38% 17 55% 1 3% 7 23% 20 50% 3 8% 10 25% 23 43% 4 7% 12 22% 11 50% 17 74% 6 67% 22 65% 20 71% 7 54% 25 37% 5 7% 27 40% M 36 53% 23 74% N 27 68% 38 70% R Comparison Groups: BC/DEF/GHIJKL/MNO/PQR/STUV/WX/YZ Independent T-Test for Means (equal variances), Independent Z-Test for Percentages (pooled proportions) Uppercase letters indicate significance at the 95% level. ACC Custom Express Vision Critical Nov. 22, 2012 D Purchased/Sold Vehicle Using Online Classifieds 11 37% N 13 43% 3 10% 3 10% 24 80% N Yes, I Have (Y) No, I Have Not (Z) 18 5 28% PQ 5 28% 2 11% 16 16 100% 21 - 28 - 55 - 37 16 43% 83 - 129 16 12% - - - - 21 16% 28 22% - 28 100% 21 57% - - - 21 100% - 6 33% - - - - - - - 10 56% PQ 8 44% 16 100% 21 100% - - 37 100% - 55 43% 9 7% 37 29% - - 55 100% - - - 28 100% 55 100% - 83 100% 83 64% - - 28 34% 55 66% - - - Table 4 Q3. Have you purchased or sold a vehicle using an online classifieds website within the past year? Gender Age Male Female 18-34 35-54 55+ BC Total (B) (C) (D) (E) (F) (G) (A) BASE: All Respondents 1006 601 405 120 427 459 238 Yes, I have 1006 601 405 120 427 459 238 100% 100% 100% 100% 100% 100% 100% Comparison Groups: BC/DEF/GHIJKL/MNO/PQR/STUV/WX/YZ Independent T-Test for Means (equal variances), Independent Z-Test for Percentages (pooled proportions) Uppercase letters indicate significance at the 95% level. ACC Custom Express Vision Critical Nov. 22, 2012 D Region AB (H) 141 141 100% SK/MB (I) 104 104 100% Education ON (J) QC (K) ATL (L) 271 271 100% 149 149 100% 103 103 100% Household Income Purchased/Sold Vehicle Using Online Classifieds Impact of Online Fraud (Q2b) $50,00 0 To Less Definite Probabl Probabl Definite Top 2 Bottom College Univ Than ly y y Did ly Did Box 2 Box HS Or / Tech Degree <$50,0 $100,0 $100,0 Affecte Affecte Not Not Affecte Did Not Less School + 00 00 00+ d d Affect Affect d Affect (M) (N) (O) (P) (Q) (R) (S) (T) (U) (V) (W) (X) 183 183 100% 527 527 100% 296 296 100% 273 273 100% 409 409 100% 194 194 100% 16 16 100% 21 21 100% 28 28 100% 55 55 100% 37 37 100% 83 83 100% Yes, I Have (Y) 1006 1006 100% No, I Have Not (Z) - Table 5 Q4. Which online classifieds websites did you browse before purchasing or selling a vehicle? Gender Total (A) BASE: Purchased or sold a vehicle in the past year in Q4 Kijiji Male (B) Age Female (C) 18-34 (D) 35-54 (E) Region 55+ (F) BC (G) AB (H) 1006 763 76% 601 450 75% 405 313 77% 120 87 73% 427 325 76% 459 351 76% 238 120 50% AutoTrader 352 35% 223 37% 129 32% 48 40% 155 36% 149 32% Craigslist 230 23% 149 25% 81 20% 34 28% 95 22% 101 22% LesPAC 83 8% 47 8% 36 9% 31 7% 36 8% eBay Motors 78 8% 10 2% 25 6% Used Victoria 20 2% 14 1% 10 1% 68 11% C 13 2% 9 1% 6 1% 16 13% E 5 4% 7 2% 5 1% 4 1% 1 1% 1 1% - 10 2% 3 1% 4 1% 48 10% DE 9 2% 10 2% 6 1% 8 1% 7 1% 3 0% 3 0% 2 0% 1 0% 3 0% 2 0% 1 0% - 2 0% 2 0% 1 0% 1 0% 2 0% 3 1% - - 2 0% 4 1% 2 0% 1 0% 3 1% 3 1% - Dealership / dealer site Buy & Sell Castanet Used Regina Auto Hebdo Facebook NL Classified Used Ottawa E Brandon Used PEI Annonces Concessionaive Local Classified Pembina Valley Online Used Everywhere Car Pages Used (unspecified) 10 1% 9 1% 4 0% 4 0% 4 0% 4 0% 3 0% 3 0% 2 0% 2 0% 2 0% 2 0% 2 0% 1 0% 1 1 0% 1 0% 1 0% 1 0% 1 1 0% 1 0% 2 0% 1 0% 1 0% 1 0% - 1 1% 1 1% 1 1% 1 1% 1 1% - 3 1% 1 0% 1 0% 1 0% 1 0% - 8 2% 4 1% 1 0% 2 0% 1 0% - SK/MB (I) Education ON (J) QC (K) 81 34% K 164 69% HIJKL - 141 128 91% GJK 51 36% K 12 9% L - 104 88 85% GK 49 47% GKL 9 9% L - 271 224 83% GK 131 48% GHKL 34 13% KL - 103 95 92% GJK 27 26% K 2 2% 183 140 77% 527 403 76% 296 220 74% 51 28% 171 32% 26 14% 1 1% 24 9% 82 55% L 9 6% 27 15% NO 9 5% 122 23% M 39 7% 130 44% MN 82 28% M 17 6% 26 11% 8 6% 6 6% 47 9% 20 8% 2 1% 6 3% J 10 4% - - - - - - 2 1% - 2 2% - 6 2% 1 0% 2 1% - - - - - - 3 3% J - 3 2% 1 1% 3 2% - - - - - 9 6% - - 9 9% - 2 1% - - - 1 0% - - - - 3 2% 1 1% - 3 1% - 1 1% - - - - 2 1% 2 1% 1 1% - Impact of Online Fraud (Q2b) $50,00 0 To Less Definite Probabl Probabl Definite Top 2 Bottom College Univ Than ly y y Did ly Did Box 2 Box HS Or / Tech Degree <$50,0 $100,0 $100,0 Affecte Affecte Not Not Affecte Did Not Less School + 00 00 00+ d d Affect Affect d Affect (M) (N) (O) (P) (Q) (R) (S) (T) (U) (V) (W) (X) ATL (L) 149 108 72% G 13 9% Household Income Purchased/Sold Vehicle Using Online Classifieds 5 5% 2 1% - 1 1% 4 4% - 2 1% - - - 3 3% - - - 1 1% - 194 134 69% 16 13 81% 21 15 71% 28 19 68% 55 41 75% 37 28 76% 83 60 72% 1006 763 76% - 148 36% P 94 23% 83 43% P 54 28% 4 25% 2 10% 7 25% 7 13% 6 16% 14 17% 352 35% - 3 19% 2 10% 3 11% 10 18% 5 14% 13 16% 230 23% - 37 9% 9 5% - 3 14% 2 7% 8 15% 3 8% 10 12% 83 8% - 22 7% 31 11% R 11 4% 30 7% - 1 5% - 2 4% 1 3% 2 2% 78 8% - 11 2% 9 2% 6 1% 6 2% 4 1% 1 0% 5 2% 4 1% 5 2% 6 1% 4 1% 2 0% 27 14% PQ 7 4% 5 3% 2 1% - - - - - - - 1 4% - - - 1 1% 1 1% - 20 2% 14 1% 10 1% - - 1 2% - 9 2% 6 1% 3 1% 2 0% 2 0% 3 1% 2 0% 2 0% 2 0% 1 0% 2 0% - 1 0% 1 0% 1 0% - 2 1% 2 1% 2 1% 2 1% - 5 1% 5 1% 2 0% 2 0% 3 1% 1 0% 1 0% 2 0% - 2 1% 1 1% - - - - - - - - - 1 4% - - 1 6% - - - 1 4% - - 1 3% 1 3% 1 3% - 1 1% - - 1 5% 1 5% - - - - - - - - - - - - - - - - - - - - - - - - - 1 0% 1 0% 1 0% - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 1 0% 1 - - - - - - - - - - - - - - 10 1% 9 1% 4 0% 4 0% 4 0% 4 0% 3 0% 3 0% 2 0% 2 0% 2 0% 2 0% 2 0% 1 0% 1 - - - 3 1% - - - - - 3 3% - 2 0% 1 0% 1 0% 1 0% 1 0% - - - - - - - - - - - - - - 2 1% - - 1 1% 2 2% - - - - 1 1% - - - - - - 1 1 - - 1 0% - 2 0% - - - - 1 - - - No, I Have Not (Z) 409 311 76% 2 1% 1 0% 1 0% 1 0% 1 0% 1 0% - 273 216 79% R 78 29% Yes, I Have (Y) 56 21% 2 1% 2 1% 1 0% 1 0% 1 0% 2 1% - 1 1% 1 1% 2 1% 1 1% - - - - 1 1% - - - Used (unspecified) Used Vancouver Other mentions Don't know / not stated 0% 1 0% 33 3% 0% 23 4% 1 0% 10 2% - - 2 2% 6 1% 0% 1 0% 25 5% E 1 0% 0% 1 0% 18 8% JL - 2 1 1 1 0% 0% 0% 0% Comparison Groups: BC/DEF/GHIJKL/MNO/PQR/STUV/WX/YZ Independent T-Test for Means (equal variances), Independent Z-Test for Percentages (pooled proportions) Uppercase letters indicate significance at the 95% level. ACC Custom Express Vision Critical Nov. 22, 2012 D - - - - - - - 7 7% JL 1 1% 2 1% 5 3% J - 1 1% 3 2% - - - 1 0% 0% 1 0% 17 3% 2 0% - - 0% - - - - - - - - 13 4% 11 4% 11 3% 8 4% 2 13% 2 10% 1 4% 2 4% 4 11% 3 4% - - 1 0% - - - - - - - 0% 1 0% 33 3% 2 0% - - Table 6 Q5. Which website did you buy your vehicle from or sell it on? Gender Total (A) BASE: Purchased or sold a vehicle in the past year in Q4 Kijiji Male (B) 1006 599 60% 601 340 57% Craigslist 131 13% AutoTrader Age Female (C) 18-34 (D) Region 35-54 (E) 55+ (F) BC (G) AB (H) 120 69 58% 427 260 61% 459 270 59% 238 64 27% 84 14% 405 259 64% B 47 12% 21 18% 59 14% 51 11% 130 13% 84 14% 46 11% 18 15% 61 14% 51 11% LesPAC 62 6% 38 6% 24 6% 11 9% 23 5% 28 6% 109 46% HIJKL 22 9% K 1 0% eBay Motors 26 3% 3 1% 3 3% 4 1% Dealership / dealer site 22 2% 23 4% C 14 2% 8 2% 4 3% 6 1% 19 4% E 12 3% Used Victoria 18 2% 11 2% 7 2% 1 1% 11 3% Buy & Sell 7 1% 4 1% 3 1% - Castanet 7 1% 5 0% 4 0% 3 0% 3 0% 2 0% 2 0% 2 0% 2 0% 1 0% 1 0% 1 0% 1 0% 1 6 1% 1 0% 3 0% 3 0% 2 0% 2 0% 1 0% - 1 0% 4 1% 1 0% - - 1 1% - 1 0% - 1 1% - 1 0% 2 0% - 1 1% 1 1% - - - NL Classified Used Regina E Brandon Facebook Local Classified Pembina Valley Online Used Ottawa Used PEI Auto Hebdo Car Pages Concessionaive Used (unspecified) Used Everywhere 2 0% 1 0% 1 0% 1 0% - - SK/MB (I) Education ON (J) QC (K) Household Income ATL (L) 104 70 67% GK 2 2% 271 182 67% GK 13 5% 149 77 52% G 3 2% 103 83 81% GIJK 1 1% 183 103 56% 527 330 63% 296 166 56% 20 11% 62 12% 15 11% K - 16 15% KL - 66 24% GHKL - 4 3% 7 7% 23 13% 1 1% 5 2% 2 1% 3 3% 11 4% 60 40% GL 4 3% 5 2% 1 1% 3 3% 6 2% 6 1% 18 8% - - 4 1% 3 1% 3 1% - 1 0% 3 1% 1 0% - 6 1% 2 0% 2 0% 3 1% 1 0% 1 0% 1 0% - 7 3% - - - 1 0% - - 1 0% 2 0% 1 0% 1 0% - - - 1 - - Impact of Online Fraud (Q2b) $50,00 0 To Less Definite Probabl Probabl Definite Top 2 Bottom College Univ Than ly y y Did ly Did Box 2 Box HS Or / Tech Degree <$50,0 $100,0 $100,0 Affecte Affecte Not Not Affecte Did Not Less School + 00 00 00+ d d Affect Affect d Affect (M) (N) (O) (P) (Q) (R) (S) (T) (U) (V) (W) (X) 141 123 87% GIJK 3 2% 1 0% 1 0% - Purchased/Sold Vehicle Using Online Classifieds Yes, I Have (Y) No, I Have Not (Z) 409 241 59% 194 99 51% 16 12 75% 21 13 62% 28 16 57% 55 33 60% 37 25 68% 83 49 59% 1006 599 60% - 49 17% 273 177 65% R 34 12% 52 13% 27 14% 1 6% 2 10% 2 7% 8 15% 3 8% 10 12% 131 13% - 61 12% 46 16% 19 7% 1 5% 2 5% 7 8% 130 13% - 12 4% 19 7% - 3 14% 5 18% V 2 7% 2 4% 26 5% 33 17% P 7 4% 1 6% 6 11% 3 8% 8 10% 62 6% - 1 1% 24 13% NO 5 3% 56 14% P 31 8% 9 2% 4 1% 11 3% - - 2 4% - 2 2% 26 3% - 4 4% 2 1% 10 2% 5 2% 6 1% 1 6% 1 5% 1 4% 1 2% 2 5% 2 2% 22 2% - - - - 2 1% 10 2% 6 2% 3 1% 5 1% - - - 1 2% - 1 1% 18 2% - - 1 0% - 1 1% 5 1% 1 0% 4 1% 1 0% - - - - - - 7 1% - - - - - 3 3% J - 9 5% P 9 5% Q 8 4% PQ 1 1% - 3 2% 12 4% N 10 3% - - - - - - - - - - - - - - - - - - - - - - 2 1% 1 0% - - - - - - - - - - - - 1 1% - - - - 1 1% - 1 4% - - - - - - - - - - 1 1% 2 2% - 1 1% - 2 1% - 1 3% - - - 1 5% - - - 4 4% 3 3% - - - - - - - - - - - - - - 2 1% - - - - - - - - - - - - - - - - - - - - - - - 1 0% - - 1 0% 1 0% 1 1 0% - 1 3% - - - 1 5% - - - 1 1% - 2 0% - - - 2 2% - - - - - - - - 1 0% 1 - - - - - - - - - - - 1 0% - - - - - - - - 7 1% 5 0% 4 0% 3 0% 3 0% 2 0% 2 0% 2 0% 2 0% 1 0% 1 0% 1 0% 1 0% 1 - 5 5% - 2 1% 2 1% - - - 3 1% 2 0% 3 1% 1 0% 2 0% 1 0% 1 0% - - - 1 0% 1 0% 1 0% - - - 1 0% 3 1% - - - 6 1% 2 0% 3 1% 2 0% 1 0% 1 0% - - - 1 1% 2 1% 1 1% - - - - - 1 1% - - 1 1% - - - - - 1 0% 1 0% 1 0% 1 0% 1 1 0% 1 0% 1 0% 1 0% 1 0% 1 0% - 1 0% 1 0% 2 1% 1 0% - - 1 0% - - 1 - - - Used Everywhere Other mentions Nothing Don't know / not stated 0% 32 3% 20 3% 0% 12 3% 9 1% 5 1% 4 1% 1 1% 10 2% 0% 21 5% 3 3% F - 4 1% 2 0% 0% 14 6% JL 2 1% 4 2 2 2 2 0% 0% 0% 0% 0% Comparison Groups: BC/DEF/GHIJKL/MNO/PQR/STUV/WX/YZ Independent T-Test for Means (equal variances), Independent Z-Test for Percentages (pooled proportions) Uppercase letters indicate significance at the 95% level. ACC Custom Express Vision Critical Nov. 22, 2012 D - 3 3% 6 2% 8 5% 1 1% 5 3% 0% 15 3% 12 4% 0% 11 4% 13 3% 5 3% - 1 5% 1 4% 2 4% 1 3% 3 4% 0% 32 3% 1 1% - 4 1% 1 1% 1 1% 3 2% 3 1% 3 1% 2 1% 2 0% 4 2% 1 6% - - 1 2% 1 3% 1 1% 9 1% - 1 1% 1 1% 2 1% - - 2 1% 2 0% - 1 0% 2 0% 1 1% - - - - - - 4 0% - - Table 7 Q6a. [Year] Please describe the vehicle you purchased or sold by filling out the form below. Gender Total (A) BASE: Purchased or sold a vehicle in the past year in Q4 1990 or before Female (C) 18-34 (D) 35-54 (E) Region 55+ (F) 120 10 8% 427 49 11% 459 60 13% 38 9% 7 6% 47 11% 49 11% AB (H) SK/MB (I) ON (J) 1991-1995 103 10% 1996-2000 233 23% 189 19% 142 24% 106 18% 91 22% 83 20% 28 23% 27 23% 96 22% 81 19% 109 24% 81 18% 238 39 16% JKL 41 17% HJKL 50 21% 42 18% 2004-2005 122 12% 67 11% 55 14% 18 15% 53 12% 51 11% 20 8% 15 11% 15 14% 69 25% 56 21% H 33 12% 2006-2007 116 12% 124 12% 63 10% 76 13% 53 13% 48 12% 11 9% 19 16% 49 11% 52 12% 56 12% 53 12% 22 9% 24 10% 22 16% 18 13% 13 13% 14 13% 27 10% 33 12% 2008 or after 405 37 9% BC (G) Education 601 82 14% C 65 11% 2001-2003 1006 119 12% Male (B) Age Comparison Groups: BC/DEF/GHIJKL/MNO/PQR/STUV/WX/YZ Independent T-Test for Means (equal variances), Independent Z-Test for Percentages (pooled proportions) Uppercase letters indicate significance at the 95% level. ACC Custom Express Vision Critical Nov. 22, 2012 D QC (K) ATL (L) Household Income Purchased/Sold Vehicle Using Online Classifieds Impact of Online Fraud (Q2b) $50,00 0 To Less Definite Probabl Probabl Definite Top 2 Bottom College Univ Than ly y y Did ly Did Box 2 Box HS Or / Tech Degree <$50,0 $100,0 $100,0 Affecte Affecte Not Not Affecte Did Not Less School + 00 00 00+ d d Affect Affect d Affect (M) (N) (O) (P) (Q) (R) (S) (T) (U) (V) (W) (X) Yes, I Have (Y) No, I Have Not (Z) 141 18 13% 104 14 13% 271 28 10% 149 13 9% 103 7 7% 183 26 14% 527 58 11% 296 35 12% 273 34 12% 409 56 14% 194 18 9% 16 2 13% 21 3 14% 28 3 11% 55 9 16% 37 5 14% 83 12 14% 1006 119 12% - 12 9% 10 10% 25 9% 10 7% 5 5% 20 11% 60 11% 23 8% 30 11% 46 11% 18 9% 2 13% 2 10% 1 4% 6 11% 4 11% 7 8% 103 10% - 38 27% 18 13% 22 21% 16 15% 31 21% 40 27% GHI 17 11% 23 22% 17 17% 45 25% 33 18% 130 25% 102 19% 58 20% 54 18% 72 26% 60 22% 85 21% 71 17% 39 20% 30 15% 1 6% 4 25% 4 19% 4 19% 7 25% 6 21% 14 25% 11 20% 5 14% 8 22% 21 25% 17 20% 233 23% 189 19% - 25 14% 57 11% 40 14% 33 12% 48 12% 23 12% 4 25% 3 14% 2 7% 5 9% 7 19% 7 8% 122 12% - 18 12% 20 13% 22 21% GHJK 14 14% 15 15% 18 10% 16 9% 56 11% 64 12% 42 14% 44 15% M 27 10% 17 6% 51 12% 52 13% P 23 12% 43 22% PQ 1 6% 2 13% 5 24% - 5 18% 4 14% 8 15% 2 4% 6 16% 2 5% 13 16% 6 7% 116 12% 124 12% - - - Table 8 Q6b. [Make] Please describe the vehicle you purchased or sold by filling out the form below. Gender Total (A) BASE: Purchased or sold a vehicle in the past year in Q4 Ford Male (B) Age Female (C) 18-34 (D) 35-54 (E) Region 55+ (F) BC (G) 1006 154 15% 601 93 15% 405 61 15% 120 12 10% 427 68 16% 459 74 16% 238 34 14% 102 10% 54 9% 48 12% 89 9% 54 9% 35 9% 52 12% F 36 8% 31 7% Chevy / Chevrolet 19 16% F 10 8% Toyota 88 9% 46 8% 42 10% 11 9% Dodge 71 7% 46 5% 43 7% 27 4% 28 7% 19 5% GMC 41 4% 26 4% Nissan 39 4% Chrysler AB (H) SK/MB (I) Education ON (J) QC (K) Household Income Purchased/Sold Vehicle Using Online Classifieds Impact of Online Fraud (Q2b) $50,00 0 To Less Definite Probabl Probabl Definite Top 2 Bottom College Univ Than ly y y Did ly Did Box 2 Box HS Or / Tech Degree <$50,0 $100,0 $100,0 Affecte Affecte Not Not Affecte Did Not Less School + 00 00 00+ d d Affect Affect d Affect (M) (N) (O) (P) (Q) (R) (S) (T) (U) (V) (W) (X) ATL (L) Yes, I Have (Y) No, I Have Not (Z) 104 13 13% 271 39 14% 149 17 11% 103 20 19% 183 28 15% 527 89 17% 296 37 13% 273 46 17% 409 57 14% 194 26 13% 16 5 31% 21 5 24% 28 3 11% 55 8 15% 37 10 27% 83 11 13% 1006 154 15% - 28 12% 141 31 22% K 10 7% 9 9% 32 12% 14 9% 9 9% 15 8% 49 9% 38 13% 25 9% 40 10% 22 11% 2 13% 2 10% 4 14% 6 11% 4 11% 10 12% 102 10% - 43 9% 21 9% 11 8% 11 11% 21 8% 13 9% 12 12% 17 9% 16 5% 11 6% 2 13% 2 10% 3 11% 6 11% 4 11% 9 11% 89 9% - 39 8% 19 8% 13 9% 7 7% 20 7% 18 12% 11 11% 28 9% 40 10% 16 8% 1 6% - 3 11% 6 11% 1 3% 9 11% 88 9% - 5 4% 4 3% 32 7% 25 6% 34 7% 17 4% 16 7% 3 1% 21 8% 12 4% 31 8% 20 5% 15 8% 5 3% 1 6% - 3 14% - 1 4% 1 4% 7 13% 2 4% 4 11% - 8 10% 3 4% 71 7% 46 5% - 20 4% 1 1% 7 4% 27 5% 7 2% 11 4% 19 5% 6 3% - 1 5% 2 7% 1 2% 1 3% 3 4% 41 4% - 26 4% 13 3% 12 3% 18 4% 12 4% 6 4% 6 6% 5 3% 17 3% 17 6% 10 4% 18 4% 6 3% - - 2 7% 3 5% - 5 6% 39 4% - 37 4% 16 3% 11 3% 23 5% 11 5% 5 4% 4 4% 8 3% 7 5% 2 2% 5 2% 13 5% 14 3% 6 3% - 2 10% 1 4% - 2 5% 1 1% 37 4% - 32 3% 17 3% 16 4% 9 2% 1 1% 6 2% 5 3% 2 2% 13 2% 13 4% 6 2% 14 3% 6 3% - - 1 4% - - 1 1% 32 3% - 28 3% 20 3% 8 2% 6 1% 13 3% 14 6% IJ 4 2% 4 3% Hyundai 3 2% 3 3% 5 2% 4 2% 14 3% 10 3% 9 3% 14 3% 3 2% 1 6% - 1 4% 1 2% 1 3% 2 2% 28 3% - 28 3% 23 2% 21 2% 16 2% 19 3% 16 3% 12 2% 8 1% 9 2% 7 2% 9 2% 8 2% 14 3% 7 2% 6 1% 8 2% 11 2% 16 3% 14 3% 4 1% 7 3% 5 2% 7 3% 4 2% 3 2% 3 2% 1 1% 1 1% 2 2% 3 3% 2 2% 1 1% 11 4% 8 3% 5 2% 7 3% 9 6% GJ 3 2% - 4 4% VW / Volkswagen 7 6% F 9 8% EF 3 3% - 10 5% O 6 3% 22 4% Mazda 21 5% B 15 4% 9 8% E 3 3% 14 6% K 6 3% 7 7% 5 5% G 4 4% 21 7% 17 6% 16 4% 19 7% 15 6% G 10 4% 38 7% 23 4% 5 4% 11 11% 8 8% G 6 6% K 3 3% 10 7% 5 3% 15 4% 8 6% 10 7% G 6 4% K 6 4% 22 12% N 12 7% 6 3% 30 11% R 26 10% 32 8% 38 9% 56 11% O 38 7% 3 2% 6 3% 6 3% - 13 2% 10 2% 12 2% 7 1% 12 4% 7 2% 3 1% 9 3% 5 2% 7 3% 3 1% 5 2% 10 2% 10 2% 10 2% 5 1% 8 4% 1 1% 6 3% 5 3% 1 1% - 28 3% 23 2% 21 2% 16 2% - 3 2% 1 1% 2 2% 4 4% 3 3% 2 2% BMW 13 1% 9 1% 4 1% 5 1% 7 2% 5 2% 4 3% - - 3 2% 1 1% 2 1% 5 1% 6 2% 1 0% 7 2% Oldsmobile 9 1% 9 1% 9 1% 8 7 1% 6 1% 6 1% 5 2 0% 3 1% 3 1% 3 1 0% 5 1% 3 1% 4 6 1% 4 1% 6 1% 1 1 0% 1 0% 5 2% 3 3 2% 1 1% - 1 1% - - - 1 1 1% 1 1% 1 1% 1 1 1% - - 3 1% 5 2% 3 1% 2 1 1% 2 1% - 6 1% 5 1% 3 1% 4 3 1% 3 1% 4 1% 4 2 1% 2 1% 1 0% - 5 1% 3 1% 4 1% 5 Honda Pontiac Buick Jeep Subaru Suzuki Volvo Acura 1 1% 4 3% F 1 1% 2 2% 3 - 1 - - - - - 1 4% - - 1 6% - - - - - - - 1 2% - 1 3% - 5 3% P 1 1% - - - 1 4% - - 1 1% 13 1% - - - - 2 1% 3 - - - - - - 1 1% 1 1% 1 1% - 9 1% 9 1% 9 1% 8 - - 1 2% 1 2% 1 2% - - - - - 1 1% - - - Acura Cadillac Kawasaki Kia Mercedes Saturn Yamaha Lincoln Mercury Mitsubishi Infinity Lexus Mini Audi Harley Davidson Jaguar Polaris Eagle Other mentions Don't know / not stated 1% 1% 1% 8 1% 8 1% 7 1% 7 1% 7 1% 6 1% 8 1% 2 0% 6 1% 3 0% 2 0% - 6 1% 5 0% 5 0% 5 0% 5 1% 3 0% 4 1% 2 0% 1 0% 2 0% 1 0% 3 1% 4 0% 4 0% 4 0% 3 0% 3 0% 3 0% 3 0% 2 0% 58 6% 3 0% 3 0% 3 0% 2 0% 1 0% 2 0% 1 0% 1 0% 35 6% 1 0% 1 0% 1 0% 1 0% 2 0% 1 0% 2 0% 1 0% 23 6% 5 1% 1 0% 4 1% 3% F 2 2% 1 1% 1 1% 1 1% 2 2% F 1 1% 1 1% 3 3% 1% 0% 1% 5 1% 2 0% 4 1% 3 1% 2 0% 3 1% 4 1% 2 0% 3 1% 4 1% 1 0% 2 1% 1 0% 1 0% - 3 1% 2 0% 1 0% 2 0% 3 1% 3 1% 4 1% 1 0% 2 1% - 2 1% 1 1% - 2 0% 2 0% 2 0% 3 1% 1 0% 1 0% 2 0% - 2 0% 1 0% 2 0% - 1 0% - 24 6% 2 0% 2 0% 1 0% 1 0% 31 7% 2 1% 3 1% 2 1% 2 1% 2 1% 1 0% 10 4% 1 1 1 0% 0% 0% Comparison Groups: BC/DEF/GHIJKL/MNO/PQR/STUV/WX/YZ Independent T-Test for Means (equal variances), Independent Z-Test for Percentages (pooled proportions) Uppercase letters indicate significance at the 95% level. ACC Custom Express Vision Critical Nov. 22, 2012 D 2 1% - - - 2 1% 1 1% - 1% 1% 1% 1% 1 1% - 4 1% - - 1 1% 2 2% - 3 1% 3 1% 2 1% 2 1% 3 2% 2 1% 1 1% 3 2% - - - 4 1% 1 0% - 2 2% - - - 2 2% - - - 1 1% - - 2 1% 7 5% - - - 10 10% GL - 1 1% 1 1% 1 1% 2 1% 2 1% 1 1% 4 2% N 2 1% 1 1% 2 1% - 2 1% - - - - 2 1% - 1 0% 2 1% - - - - 1 1% - 1 0% - - - - 1 1% - - 1 1% - 1 1% - 1 1% - - 13 9% L - 2 2% 15 8% - - 1 0% 1 0% 16 6% 1 0% - - 1 1% - - 1% 1% 4 1% 7 1% 3 1% 3 1% 2 0% 2 1% 1 0% 2 1% 3 1% 1 0% 4 1% 3 1% 2 0% 2 0% 1 0% 1 0% 3 1% 2 0% 1 0% 1 0% 3 1% 1 0% 2 0% 2 0% 2 0% 31 6% 1 0% 3 1% 3 1% - 1 0% 1% 2% 3 1% 2 1% 3 1% 1 0% 4 1% 4 1% 4 1% 3 1% 2 0% 2 0% 1 1% 2 1% - - - - - - 3 2% - - 1 5% 1 5% - 1 4% - - - - 1 2% - 1 1% 1 0% 2 1% 2 1% - 3 1% - 2 1% 3 2% 2 1% 2 1% - - - - - 1 3% - - - 1 5% - - - - - - - - - - 1 2% - 1 1% - 2 0% - 1 1% 3 2% 2 1% 2 1% 1 1% - 1 6% - - - - - - - - 1 5% - - - 1 3% 1 3% - - - - - - - 1 6% - - - - - - - 1 1% 1 1% 14 7% 1 6% - 1 5% - - 1 2% - 1 3% - - - 2 5% - - 1 5% 3 11% 5 9% 1 3% 8 10% 1 1% - - - - - - 1 0% - 2 0% 2 0% - 1 0% 1 0% 1 0% - 2 1% 2 1% - 12 4% 15 5% 1 0% 2 0% 1 0% 23 6% - - - - - 1% - 1 2% 1 2% 1 2% - 1 3% 1 3% - 1 1% 1 1% 2 2% - - - 1 1% - 8 1% 8 1% 7 1% 7 1% 7 1% - 6 1% 5 0% 5 0% 5 0% - 4 0% 4 0% 4 0% 3 0% 3 0% 3 0% 3 0% 2 0% 58 6% - 1 0% - - - - Table 9 Q6d. [Condition] Please describe the vehicle you purchased or sold by filling out the form below. Gender Total (A) BASE: Purchased or sold a vehicle in the past year in Q4 Used New Male (B) Age Female (C) 18-34 (D) 1006 973 97% 601 578 96% 405 395 98% 120 112 93% 33 3% 23 4% 10 2% 8 7% E 35-54 (E) 427 419 98% D 8 2% Region 55+ (F) BC (G) AB (H) SK/MB (I) 459 442 96% 238 230 97% 141 138 98% 104 101 97% 17 4% 8 3% 3 2% 3 3% Comparison Groups: BC/DEF/GHIJKL/MNO/PQR/STUV/WX/YZ Independent T-Test for Means (equal variances), Independent Z-Test for Percentages (pooled proportions) Uppercase letters indicate significance at the 95% level. ACC Custom Express Vision Critical Nov. 22, 2012 D Education ON (J) 271 266 98% K 5 2% QC (K) ATL (L) Household Income Purchased/Sold Vehicle Using Online Classifieds Impact of Online Fraud (Q2b) $50,00 0 To Less Definite Probabl Probabl Definite Top 2 Bottom College Univ Than ly y y Did ly Did Box 2 Box HS Or / Tech Degree <$50,0 $100,0 $100,0 Affecte Affecte Not Not Affecte Did Not Less School + 00 00 00+ d d Affect Affect d Affect (M) (N) (O) (P) (Q) (R) (S) (T) (U) (V) (W) (X) Yes, I Have (Y) No, I Have Not (Z) 149 140 94% 103 98 95% 183 178 97% 527 513 97% 296 282 95% 273 267 98% 409 394 96% 194 188 97% 16 16 100% 21 20 95% 28 26 93% 55 54 98% 37 36 97% 83 80 96% 1006 973 97% - 9 6% J 5 5% 5 3% 14 3% 14 5% 6 2% 15 4% 6 3% - 1 5% 2 7% 1 2% 1 3% 3 4% 33 3% - Table 10 Q6E. [Bought from / Sold to] Please describe the vehicle you purchased or sold by filling out the form below. Gender Total (A) BASE: Purchased or sold a vehicle in the past year in Q4 Dealer Private seller Male (B) Age Female (C) 18-34 (D) 35-54 (E) Region 55+ (F) BC (G) AB (H) 1006 204 20% 601 120 20% 405 84 21% 120 26 22% 427 85 20% 459 93 20% 238 43 18% 141 16 11% 802 80% 481 80% 321 79% 94 78% 342 80% 366 80% 195 82% 125 89% IJKL Comparison Groups: BC/DEF/GHIJKL/MNO/PQR/STUV/WX/YZ Independent T-Test for Means (equal variances), Independent Z-Test for Percentages (pooled proportions) Uppercase letters indicate significance at the 95% level. ACC Custom Express Vision Critical Nov. 22, 2012 D SK/MB (I) 104 23 22% H 81 78% Education ON (J) 271 62 23% H 209 77% QC (K) 149 37 25% H 112 75% ATL (L) 103 23 22% H 80 78% Household Income Purchased/Sold Vehicle Using Online Classifieds Impact of Online Fraud (Q2b) $50,00 0 To Less Definite Probabl Probabl Definite Top 2 Bottom College Univ Than ly y y Did ly Did Box 2 Box HS Or / Tech Degree <$50,0 $100,0 $100,0 Affecte Affecte Not Not Affecte Did Not Less School + 00 00 00+ d d Affect Affect d Affect (M) (N) (O) (P) (Q) (R) (S) (T) (U) (V) (W) (X) 183 27 15% 527 108 20% 156 85% O 419 80% 296 69 23% M 227 77% 273 50 18% 409 94 23% 194 38 20% 16 2 13% 21 4 19% 223 82% 315 77% 156 80% 14 88% 17 81% 28 8 29% V 20 71% Yes, I Have (Y) No, I Have Not (Z) 55 6 11% 37 6 16% 83 14 17% 1006 204 20% - 49 89% U 31 84% 69 83% 802 80% - Table 11 Q6F. [Price] Please describe the vehicle you purchased or sold by filling out the form below. Gender Total (A) BASE: Purchased or sold a vehicle in the past year in Q4 $1,000 or less Male (B) Age Female (C) 18-34 (D) 1006 196 19% 601 120 20% 405 76 19% 120 19 16% 134 13% 183 18% 72 12% 110 18% 62 15% 73 18% $4,001-$6,000 129 13% 77 13% $6,001-$8,000 82 8% $8,001-$10,000 $1,001-$2,000 $2,001-$4,000 $10,001-$20,000 $20,001+ 35-54 (E) Region 55+ (F) BC (G) AB (H) SK/MB (I) Education ON (J) QC (K) 459 78 17% 238 48 20% 141 18 13% 104 17 16% 271 55 20% 16 13% 20 17% 427 99 23% F 61 14% 77 18% 57 12% 86 19% 33 14% 41 17% 18 13% 25 18% 41 15% 52 19% 52 13% 19 16% 55 13% 55 12% 32 13% 22 16% 10 10% 23 22% K 12 12% 149 36 24% H 19 13% 19 13% 30 11% 49 8% 33 8% 27 6% 39 8% 23 10% 12 9% 9 9% 72 7% 139 14% 48 8% 82 14% 24 6% 57 14% 16 13% E 7 6% 13 11% 28 7% 55 13% 37 8% 71 15% 16 7% 29 12% 71 7% 43 7% 28 7% 10 8% 25 6% 36 8% 16 7% 8 6% 26 18% JL 12 9% 7 7% 22 21% GJL 4 4% Comparison Groups: BC/DEF/GHIJKL/MNO/PQR/STUV/WX/YZ Independent T-Test for Means (equal variances), Independent Z-Test for Percentages (pooled proportions) Uppercase letters indicate significance at the 95% level. ACC Custom Express Vision Critical Nov. 22, 2012 D ATL (L) Household Income Purchased/Sold Vehicle Using Online Classifieds Impact of Online Fraud (Q2b) $50,00 0 To Less Definite Probabl Probabl Definite Top 2 Bottom College Univ Than ly y y Did ly Did Box 2 Box HS Or / Tech Degree <$50,0 $100,0 $100,0 Affecte Affecte Not Not Affecte Did Not Less School + 00 00 00+ d d Affect Affect d Affect (M) (N) (O) (P) (Q) (R) (S) (T) (U) (V) (W) (X) 103 22 21% 183 40 22% 527 107 20% 296 49 17% 24 13% 28 15% 72 14% 98 19% 18 12% 13 13% 23 22% K 15 15% 20 7% 13 9% 5 5% 31 17% N 14 8% 21 8% 30 11% 11 7% 24 16% 9 9% 8 8% 22 8% 9 6% 8 8% Yes, I Have (Y) No, I Have Not (Z) 409 73 18% 194 25 13% 16 1 6% 21 5 24% 28 3 11% 55 12 22% 37 6 16% 83 15 18% 1006 196 19% - 38 13% 57 19% 273 73 27% QR 40 15% 49 18% 57 14% 75 18% 22 11% 32 16% 3 19% 4 25% 2 10% 5 24% 6 21% 3 11% 8 15% 12 22% 5 14% 9 24% 14 17% 15 18% 134 13% 183 18% - 56 11% 42 14% 41 15% 47 11% 23 12% 4 25% 5 24% 2 7% 5 9% 7 8% 129 13% - 48 9% 20 7% 22 8% 34 8% 14 7% - - 4 14% 5 9% 9 24% X - 9 11% 82 8% - 11 6% 31 17% 42 8% 67 13% 19 6% 41 14% 14 5% 27 10% 34 8% 60 15% - 3 14% 6 11% 4 7% 5 14% 9 11% 7 8% 72 7% 139 14% - 2 13% 3 11% 3 11% 4 2% 37 7% M 30 10% M 7 3% 29 7% P 19 10% 33 17% P 26 13% PQ 2 13% 1 5% 4 14% 3 5% 3 8% 7 8% 71 7% - - - - Table 12 Q7. Did you use the classifieds website's recommended payment method? Gender Total (A) BASE: Purchased or sold a vehicle in the past year in Q4 Yes, I did No, I did not Male (B) Age Female (C) 1006 255 25% 601 156 26% 405 99 24% 751 75% 445 74% 306 76% 18-34 (D) 120 48 40% EF 72 60% 35-54 (E) Region 55+ (F) BC (G) 427 89 21% 459 118 26% 238 62 26% 338 79% D 341 74% D 176 74% Comparison Groups: BC/DEF/GHIJKL/MNO/PQR/STUV/WX/YZ Independent T-Test for Means (equal variances), Independent Z-Test for Percentages (pooled proportions) Uppercase letters indicate significance at the 95% level. ACC Custom Express Vision Critical Nov. 22, 2012 D AB (H) 141 44 31% I 97 69% SK/MB (I) Education ON (J) QC (K) ATL (L) Household Income Purchased/Sold Vehicle Using Online Classifieds Impact of Online Fraud (Q2b) $50,00 0 To Less Definite Probabl Probabl Definite Top 2 Bottom College Univ Than ly y y Did ly Did Box 2 Box HS Or / Tech Degree <$50,0 $100,0 $100,0 Affecte Affecte Not Not Affecte Did Not Less School + 00 00 00+ d d Affect Affect d Affect (M) (N) (O) (P) (Q) (R) (S) (T) (U) (V) (W) (X) 104 18 17% 271 69 25% 149 40 27% 103 22 21% 183 45 25% 527 114 22% 86 83% H 202 75% 109 73% 81 79% 138 75% 413 78% O 296 96 32% N 200 68% 273 76 28% 409 103 25% 194 41 21% 16 2 13% 21 1 5% 28 4 14% 197 72% 306 75% 153 79% 14 88% 20 95% V 24 86% 55 15 27% T 40 73% Yes, I Have (Y) No, I Have Not (Z) 37 3 8% 83 19 23% 1006 255 25% - 34 92% 64 77% 751 75% - Table 13 Q8. Which payment method did you use? Gender Male (B) Total (A) BASE: Purchased or sold a vehicle in the past year in Q4 Cash (NET) Age Female (C) 18-34 (D) Region 35-54 (E) 55+ (F) BC (G) 1006 650 65% 601 393 65% 405 257 63% 120 71 59% 427 292 68% 459 287 63% 581 58% 353 59% 228 56% 67 56% 49 5% 29 5% 20 5% 4 3% 264 62% F 19 4% 21 2% 221 22% 11 2% 132 22% 10 2% 89 22% - 10 2% 75 18% Cheque / Cashier's Cheque 93 9% 60 10% 33 8% Certified Cheque 75 7% 42 7% Draft / Bank Draft 42 4% Money Order Credit (NET) Cash Cash in person / on hand / cash face to face Cash on delivery / pick up / COD Cheque (NET) 29 24% 141 88 62% 104 57 55% 250 54% 80 57% 26 6% 11 5% 11 2% 117 25% E 49 11% E 37 8% 6 3% 58 24% 149 91 61% 53 51% 271 183 68% I 160 59% 183 119 65% 527 348 66% 296 183 62% 83 56% 103 71 69% I 62 60% 110 60% 300 57% 171 58% 5 4% 4 4% 14 5% 8 5% 7 7% 8 4% 7 2% 10 4% 52 19% 24 16% 2 2% 19 18% 1 1% 36 20% 34 6% O 15 3% 115 22% 3 2% 37 26% K 15 11% - 15 6% 11 7% 6 6% 14 8% 19 7% 11 7% 6 6% No, I Have Not (Z) 273 192 70% QR 168 62% 409 254 62% 194 119 61% 16 12 75% 21 13 62% 28 16 57% 55 35 64% 37 25 68% 83 51 61% 1006 650 65% - 224 55% 113 58% 10 63% 11 52% 14 50% 34 62% 21 57% 48 58% 581 58% - 1 6% 2 10% 1 4% - 3 8% 1 1% 49 5% - - 1 2% 8 15% 1 3% 11 30% 2 2% 13 16% 21 2% 221 22% - 7 33% 1 4% 5 18% 35 12% 21 8% 4 2% 53 27% P 23 12% 1 6% 4 25% 44 8% 21 5% R 10 2% 97 24% P 38 9% 2 1% 5 2% 70 24% 20 7% R 4 1% 41 15% 2 13% 3 14% 4 14% 3 5% 5 14% 7 8% 93 9% - 16 9% 37 7% 22 7% 12 4% 30 7% 2 13% 3 14% 1 4% 5 9% 5 14% 6 7% 75 7% - - 1 5% - - 1 3% - 42 4% - 8 3% 11 8% 3 3% 14 5% - 6 6% 4 2% 27 5% 11 4% 7 3% 23 6% 4 2% 1 1% - 4 1% 2 1% 1 1% 2 1% 7 1% 3 1% 1 0% 6 1% 2 1% - - - - - - 12 1% - 18 4% 11 2% 8 3% 3 1% 5 4% 3 2% 5 5% 3 3% 16 6% 11 4% 26 5% 17 3% 17 6% 9 3% 12 4% 8 3% 28 7% 13 3% 7 4% 7 4% - - 2 2% 2 2% 51 5% 32 3% - - 1 2% 1 2% - - 1 4% 1 4% 4 2% 1 0% 6 3% 2 1% - 2 2% - - - - - - - - - - - 9 3% 5 3% - - 1 4% 6 11% - 7 8% 17 2% 3 0% 32 3% - - 11 3% 2 2% 9 2% 7 2% 2 1% 3 2% 1 1% 3 1% 9 5% N 4 2% 12 3% 3 1% 13 3% - 1 1% 7 2% 2 1% 12 4% 1 1% - 5 5% 8 2% 1 0% 11 2% 4 1% - 5 4% 5 2% 1 0% 6 2% 2 1% - 3 3% 6 1% 1 0% 15 3% 6 6% 5 5% G 1 1% - 8 4% 6 3% 8 2% 2 0% 14 3% 8 2% 6 2% 5 2% 8 2% 1 1% - - 1 4% 4 7% - 5 6% 18 2% - 11 2% 3 1% 1 1% 5 1% 8 2% 4 2% 2 1% 4 4% 3 1% 11 7% 7 5% G 3 2% 1 1% 9 6% JL 8 5% GJ 1 1% 3 1% 6 2% 4 1% 5 1% 4 2% - - - 2 4% - 2 2% 14 1% - 78 8% 43 7% 35 9% 7 6% 30 7% 41 9% 12 5% 9 6% 8 8% 23 8% 9 9% 35 7% 27 9% 24 9% 36 9% 9 5% - 3 14% 7 25% 6 11% 3 8% 13 16% 78 8% - 59 6% 29 5% 30 7% 5 4% 21 5% 33 7% 10 4% 6 4% 7 7% 15 6% 7 7% 13 7% 26 5% 20 7% 20 7% 24 6% 8 4% - 3 14% 3 8% 11 13% 59 6% - 2 1 - 3 - - - - 1 - 1 1 1 1 1 - - - 7 25% V - 4 7% 3 17 11% G 14 9% G 2 5 3% N 16 9% - - - 3 - 17 4% 4 3% 12 3% 12 1% 5 1% 7 2% 3 1% 51 5% 32 3% 26 4% 16 3% 25 6% 16 4% 4 3% E 8 7% 6 5% 26 6% E 5 1% 25 6% 15 4% 17 2% 3 0% 32 3% 9 1% 1 0% 18 3% 8 2% 2 0% 14 3% 3 3% - Bank Transfer / Wire Transfer 18 2% 7 1% Paypal 14 1% Other Mentions (NET) In person / paid in person / face to face / directly to the seller Free / it was free ATL (L) Yes, I Have (Y) 20 10% P 9 5% 25 4% Electronic Payment (NET) QC (K) Impact of Online Fraud (Q2b) $50,00 0 To Less Definite Probabl Probabl Definite Top 2 Bottom College Univ Than ly y y Did ly Did Box 2 Box HS Or / Tech Degree <$50,0 $100,0 $100,0 Affecte Affecte Not Not Affecte Did Not Less School + 00 00 00+ d d Affect Affect d Affect (M) (N) (O) (P) (Q) (R) (S) (T) (U) (V) (W) (X) 11 8% 33 8% Debit Card ON (J) Household Income 31 30% JK 18 17% JKL 10 10% 29 7% Credit Card / VISA SK/MB (I) 238 160 67% I 143 60% 15 13% E 6 5% Credit / Line of Credit AB (H) Education Purchased/Sold Vehicle Using Online Classifieds 32 7% 28 12% J 18 8% 1 1% - - - - - Free / it was free Trade Other mentions Nothing Don't know / not stated 0% 2 0% 14 1% 5 0% 8 1% 0% 2 0% 10 2% 3 0% 6 1% 0% 4 1% 2 0% 2 0% 2 2% 2 2% 3 3% F 1% 1 0% 5 1% 4 1% 1 0% 7 2% 3 1% 1 0% 1 0% 1 0% 1 0% 3 1% Comparison Groups: BC/DEF/GHIJKL/MNO/PQR/STUV/WX/YZ Independent T-Test for Means (equal variances), Independent Z-Test for Percentages (pooled proportions) Uppercase letters indicate significance at the 95% level. ACC Custom Express Vision Critical Nov. 22, 2012 D 1 1% 2 1% 1 1% 1 1% 1 1% 1 1% 1 1% 0% - 1% - 7 3% - 1 1% 2 1% - 2 1% 2 2% 1 1% 1% 2 1% 2 1% 2 1% 0% 1 0% 7 1% 3 1% 3 1% 0% 1 0% 5 2% 3 1% 0% 1 0% 2 1% 3 1% 1 0% 0% 1 0% 10 2% 1 0% 2 0% - - - - - - - 1 1% 1 1% 3 2% - - - - - - - - - - 2 4% 1 2% - 2 2% 1 1% - - 0% 2 0% 14 1% 5 0% 8 1% - Table 14 Q9. [Read the website's policy on fraud protection] Did you do any of the following prior to making the purchasing or selling decision? Gender Total (A) BASE: Purchased or sold a vehicle in the past year in Q4 Yes, I did No, I did not Male (B) Age Female (C) 18-34 (D) 35-54 (E) 1006 403 40% 601 252 42% 405 151 37% 120 38 32% 427 142 33% 603 60% 349 58% 254 63% 82 68% F 285 67% F Region 55+ (F) 459 223 49% DE 236 51% BC (G) 238 87 37% 151 63% Comparison Groups: BC/DEF/GHIJKL/MNO/PQR/STUV/WX/YZ Independent T-Test for Means (equal variances), Independent Z-Test for Percentages (pooled proportions) Uppercase letters indicate significance at the 95% level. ACC Custom Express Vision Critical Nov. 22, 2012 D AB (H) 141 65 46% L 76 54% SK/MB (I) 104 41 39% 63 61% Education ON (J) 271 120 44% L 151 56% QC (K) ATL (L) Household Income Purchased/Sold Vehicle Using Online Classifieds Impact of Online Fraud (Q2b) $50,00 0 To Less Definite Probabl Probabl Definite Top 2 Bottom College Univ Than ly y y Did ly Did Box 2 Box HS Or / Tech Degree <$50,0 $100,0 $100,0 Affecte Affecte Not Not Affecte Did Not Less School + 00 00 00+ d d Affect Affect d Affect (M) (N) (O) (P) (Q) (R) (S) (T) (U) (V) (W) (X) 149 59 40% 103 31 30% 183 72 39% 527 216 41% 296 115 39% 273 111 41% 409 171 42% 194 65 34% 90 60% 72 70% HJ 111 61% 311 59% 181 61% 162 59% 238 58% 129 66% 16 8 50% V 8 50% Yes, I Have (Y) No, I Have Not (Z) 21 6 29% 28 8 29% 55 10 18% 37 14 38% 83 18 22% 1006 403 40% - 15 71% 20 71% 45 82% S 23 62% 65 78% 603 60% - Table 15 Q9. [Research the types of online fraud prior to making the purchasing or selling decision] Did you do any of the following prior to making the purchasing or selling decision? Gender Total (A) BASE: Purchased or sold a vehicle in the past year in Q4 Yes, I did No, I did not 1006 362 36% 644 64% Male (B) 601 234 39% C 367 61% Age Female (C) 18-34 (D) 35-54 (E) 405 128 32% 120 41 34% 427 126 30% 277 68% B 79 66% 301 70% F Region 55+ (F) 459 195 42% E 264 58% BC (G) 238 84 35% 154 65% Comparison Groups: BC/DEF/GHIJKL/MNO/PQR/STUV/WX/YZ Independent T-Test for Means (equal variances), Independent Z-Test for Percentages (pooled proportions) Uppercase letters indicate significance at the 95% level. ACC Custom Express Vision Critical Nov. 22, 2012 D AB (H) 141 60 43% L 81 57% SK/MB (I) 104 35 34% 69 66% Education ON (J) 271 99 37% L 172 63% QC (K) 149 58 39% L 91 61% ATL (L) Household Income Purchased/Sold Vehicle Using Online Classifieds Impact of Online Fraud (Q2b) $50,00 0 To Less Definite Probabl Probabl Definite Top 2 Bottom College Univ Than ly y y Did ly Did Box 2 Box HS Or / Tech Degree <$50,0 $100,0 $100,0 Affecte Affecte Not Not Affecte Did Not Less School + 00 00 00+ d d Affect Affect d Affect (M) (N) (O) (P) (Q) (R) (S) (T) (U) (V) (W) (X) 103 26 25% 183 66 36% 527 189 36% 296 107 36% 273 95 35% 409 157 38% 194 65 34% 77 75% HJK 117 64% 338 64% 189 64% 178 65% 252 62% 129 66% 16 7 44% V 9 56% Yes, I Have (Y) No, I Have Not (Z) 21 5 24% 28 6 21% 55 10 18% 37 12 32% 83 16 19% 1006 362 36% - 16 76% 22 79% 45 82% S 25 68% 67 81% 644 64% - Table 16 Q9a. Which resources did you review? Gender Total (A) BASE: Purchased or sold a vehicle in the past year AND did research on fraud protection in Q9 Male (B) Age Female (C) 18-34 (D) Region 35-54 (E) 55+ (F) BC (G) 471 103 22% 298 67 22% 173 36 21% 48 13 27% 169 37 22% 254 53 21% 105 26 25% 43 9% 30 6% 26 6% 27 9% 23 8% 18 6% 16 9% 7 4% 8 5% 6 13% 4 8% 2 4% 16 9% 11 7% 10 6% 21 8% 15 6% 14 6% 5 1% 5 1% 2 0% 93 20% 4 1% - - 1 0% 56 19% 1 1% 5 3% 1 1% 37 21% 1 2% - 2 1% 1 1% - 8 17% 35 21% 3 1% 3 1% 2 1% 50 20% 47 10% 24 8% 23 13% 2 4% 16 9% Websites (unspecified) 25 5% 17 6% 8 5% 4 8% Craigslist 16 3% 11 4% 5 3% 10 2% 2 0% 55 12% 7 2% 1 0% 39 13% Read what was on their website / the policies on the website Auto Trader / Auto Trader policy 19 4% 12 3% eBay / eBay warnings Research / Information (NET) Information online / on the internet Research / information on scams / fraud / fraud protection Google search Comparison with other ads Read safety precautions Check with a lawyer Websites (NET) Kijiji Blogs / forums / car forums / car websites Used Victoria website Website Policy (NET) Terms and conditions Online privacy & security policy Vehicle History / Reports / Reviews (NET) AB (H) SK/MB (I) Education ON (J) QC (K) Household Income Purchased/Sold Vehicle Using Online Classifieds Impact of Online Fraud (Q2b) $50,00 0 To Less Definite Probabl Probabl Definite Top 2 Bottom College Univ Than ly y y Did ly Did Box 2 Box HS Or / Tech Degree <$50,0 $100,0 $100,0 Affecte Affecte Not Not Affecte Did Not Less School + 00 00 00+ d d Affect Affect d Affect (M) (N) (O) (P) (Q) (R) (S) (T) (U) (V) (W) (X) ATL (L) Yes, I Have (Y) No, I Have Not (Z) 45 10 22% 144 32 22% 68 9 13% 34 5 15% 84 15 18% 247 54 22% 140 34 24% 129 29 22% 196 40 20% 80 19 24% 9 - 8 - 9 1 11% 13 4 31% 17 - 22 5 23% 471 103 22% - 8 8% 8 8% 9 9% 75 21 28% K 9 12% 8 11% 4 5% 4 9% 2 4% 3 7% 14 10% 9 6% 9 6% 6 9% - 2 6% 3 9% - 6 7% 5 6% 2 2% 26 11% 15 6% 11 4% 12 9% 8 6% 4 3% 14 7% 12 6% 13 7% 8 10% 8 10% 5 6% - - - - - - - 1 11% - - - 3 14% 1 5% - 43 9% 30 6% 26 6% - - 3 23% - 2 2% 2 2% - 1 1% 1 1% - - 1 1% 1 1% - - - - - - - - - - - - - - 1 8% - - 1 5% - 6 9% 5 15% 15 18% 13 16% 1 11% 2 25% - - 3 18% - 29 11% 5 11% 4 6% 2 6% 10 12% 26 11% 11 8% 14 11% 20 10% 3 4% 1 11% 1 13% - - 2 12% - 47 10% - 12 7% 9 4% 8 8% 18 24% K 15 20% GJK 3 4% 1 1% 46 23% 1 1% - 5 1% 5 1% 2 0% 93 20% - - 2 2% 2 2% 1 1% 21 16% 3 2% - - 2 1% 3 1% 1 0% 46 19% - - 2 2% - 27 26% K 7 7% 1 1% 1 1% 1 1% 28 19% K 14 10% 11 8% 10 7% 13 9% M 1 1% 2 1% 1 1% 32 23% 1 2% 9 6% 1 1% 3 9% 2 2% 10 4% 3 2% 14 7% 6 8% - 1 13% - - 1 6% - 25 5% - 2 4% 5 3% 9 4% 2 3% - 1 1% - - 2 2% 7 3% 5 4% 9 5% 1 1% - - - - - - 16 3% - 3 2% 1 1% 16 9% 1 2% - 2 1% 1 1% 13 8% - 5 3% - 1 1% - - - - - - - - - - 6 18% 7 8% 21 16% - - 1 11% 1 8% - 2 9% 10 2% 2 0% 55 12% - 6 9% 3 4% 1 1% 10 13% - 16 11% 4 2% 1 1% 21 11% - 9 20% 4 3% 1 1% 17 12% 3 2% - 7 9% 4 2% 1 0% 31 13% - - 2 2% - - - 4 9% - 10 3% 8 3% 9 5% 4 2% 3 6% - 6 4% 3 2% 7 3% 1 0% 39 15% E 10 4% 9 4% 13 12% HJ - 13 9% MN 7 5% 5 5% 2 2% 4 5% - 2 4% 3 7% 3 2% 6 4% 4 6% 1 1% 1 3% - 4 5% - 6 4% 1 1% 9 7% 4 3% 5 3% 6 3% 2 3% 2 3% - - - - - 1 11% 1 5% 1 5% 19 4% 12 3% - - 1 8% - 11 2% 8 2% 9 3% 7 2% 2 1% 1 1% - - 2 3% 1 1% 2 4% 1 2% 5 3% 1 1% - 4 3% 2 2% 4 2% 3 2% 3 4% 3 4% - - - - - - - - - - 11 2% 8 2% - 7 1% 30 6% 6 2% 25 8% C 1 1% 5 3% - 1 1% 9 5% 6 2% 19 7% 2 2% 12 11% - 1 2% - 2 1% 12 8% 3 9% GJ 2 6% - 5 4% 3 2% - 1 1% 2 2% 1 1% - 3 2% 2 2% 1 1% - - 11 4% 5 2% 9 4% 11 4% O 4 2% 4 2% 5 2% 17 7% 2 1% 7 5% 3 2% 6 5% 4 2% 9 5% - - - - - - - - 12 15% PQ 1 11% - 1 11% 2 15% 1 6% 3 14% 7 1% 30 6% 3 6% 2 4% 2 2% 11 10% 6 8% 1 2% 9 20% 1 1% - 6 7% - - - - - - - - - Blue Book / Kelley Blue Book - - 1 1% - - 1 1% - - 2 1% 1 1% 1 1% 9 5% 3 2% 2 1% 2 1% 1 2% 1 2% - 2 1% 11 4% 2 1% 8 5% 1 2% 1 2% 1 1% 3 2% 7 1% 5 1% 5 1% 2 0% 17 4% 5 1% 4 1% 4 1% 4 1% 17 4% 6 2% 2 1% 3 1% - 1 2% - 1 1% 1 1% 1 1% - 8 3% 3 1% 1 0% 1 0% 3 1% 12 4% 1 1% 3 2% 2 1% 2 1% 9 5% 2 1% 3 2% 3 2% 1 1% 5 3% By appointment / appointment with the seller By phone / contacted the seller by phone 9 2% 6 1% 6 2% 3 1% 3 2% 3 2% - Dealers / contacted the dealership 5 1% 17 4% 5 2% 9 3% - - 8 5% Friends / recommendations from friends 8 2% 6 2% Family members 6 1% 1 0% Mechanics / asked my mechanic 2 0% 3 1 0% 2 Car Fax Carproof Checked the vehicle history Did a lean search Lemon Aid used cars Car facts / car reviews Other vehicle history / reports / reviews mentions Payment Related (NET) Payment option / policy / policy regarding payments A bank / bank online / bank protection PayPal / PayPal website Paid in cash / not accepting cheques Media / Magazines (NET) Newspaper / magazines Le SAAQ Protegeze-vous Magazine Other media / magazines mentions Consumer Agencies (NET) BBB / Better Business Bureau Consumer Reports OPC / Police Service The Consumer Protection Act Contact with Seller (NET) Friends / Acquaintances / Family Members (NET) Other friends / acquaintances / family members mentions 4 1% 4 1% 4 1% 4 1% 4 1% 4 1% 3 1% 5 1% 24 5% 8 2% 7 1% 5 1% 4 1% 3 1% 4 1% 3 1% 4 1% 2 1% 2 1% 4 1% 15 5% 5 2% 5 2% 3 1% 4 1% 19 4% 2 1% 3 1% 2 1% 3 1% 3 1% 2 1% 1 0% 4 2% 15 6% 7 3% 5 2% 1 0% 2 2% 3 3% 1 1% 2 2% 3 3% - 1 1% 1 1% 7 4% 3 2% 2 1% 1 1% 1 1% 7 4% 2 1% 15 6% E 5 2% 4 2% 4 2% 2 1% 9 4% 2 1% 2 1% 2 1% 3 1% 9 4% 4 2% 2 1% 1 2% 2 1% 5 3% B 1 1% 1 - - 3 6% 1 2% 1 2% - 2 1% 1 1% 2 1% 1 1% 1 1% 1 1% 1 1% 1 1% 6 4% 1 1% 4 2% 1 1% 1 1% 8 8% 2 2% 3 3% 2 2% 1 1% 1 1% 1 1% - - 1 1% 1 1% - - 1 1% 3 4% 2 3% - - - - 1 2% 1 2% - 1 1% - - - - - 2 1% 2 1% - - - - - - - 1 1% - 3 2% 2 1% 3 2% 7 5% 3 2% 1 1% - - - - 2 1% 3 1% 3 1% 2 1% 4 2% - - - - - 3 4% - 2 6% - 2 3% 1 1% 1 3% 1 3% 2 2% 1 1% 6 7% 2 2% 1 1% 1 1% 1 0% 3 1% 15 6% 5 2% 4 2% 4 2% - - 11 16% GHJ 1 1% 5 7% 5 7% - - 2 2% 6 7% 2 1% 10 4% - 1 1% 2 2% 3 4% - 3 4% - 2 6% - 1 1% - - 1 3% - - 5 2% 2 1% 2 1% 1 0% 11 4% 5 2% 2 1% - 1 1% - - - 3 4% - 1 1% - 1 1% - - 4 3% - - - - - - 2 3% 4 5% 2 3% - - - - 2 3% - - 2 2% 3 4% - 6 4% 2 1% 2 1% 1 1% 1 1% 4 3% 5 2% 3 1% - 1 1% 1 1% - 3 2% 5 3% 2 1% 11 4% 2 2% - 1 1% 2 3% - - 1 2% 4 3% 1 2% 2 1% 5 2% - - - 2 1% - 2 1% 4 2% - 1 1% - 3 2% - - - - 2 - 1 1 2% - - - 2 1% 1 1 2% 1 2% 1 2% 1 2% 2 2% 1 1% 1 1% - - - - - 3 2% 4 3% 4 3% 1 1% - 1 1% 2 3% 6 9% G 2 3% 4 6% J 2 3% 8 12% HJ 5 7% J 1 1% 1 1% 2 - 1 3% 2 6% 2 6% - 1 1% 1 1% - 1 1% - 1 1% - 1 1% - 1 1% 1 1% - - 1 1% 2 1% 1 1% - 2 3% 2 3% 1 1% 4 5% 1 1% 1 1% 2 3% 1 1% 6 8% 1 1% 1 1% 3 4% Q 1 1% 1 1% 1 11% - - - 1 8% - 1 6% - 1 5% - - - - - - - - - - - - - - - - - 1 11% - 1 8% 1 8% - - - - - 1 5% 1 5% 1 5% - - - - - - - - 1 13% - - - - - - 1 6% - - - - - 1 6% - - - 1 13% - - - - - - - 1 11% - - - 1 6% - 2 1% 1 1% 3 2% - 1 1% - - - - - - - 1 11% - - - - - - - 1 6% - - - - - - - - - 8 4% 2 1% 4 2% 1 1% 1 1% 7 4% 3 4% 2 3% - - - - - - - - - - - - - - - - - - - 1 1% - - - - - - - - - - - - - 3 4% - - 1 11% 1 8% - 2 9% 4 2% 1 1% 1 1% - - - - - - - - - 1 11% - - 2 1% 5 3% 2 3% 2 3% - 2 1% 1 1% - 1 1% 3 2% 1 1% 2 1% - 1 1% 2 2% 1 1% 1 1% 6 5% 4 3% 2 2% - - - 3 2% 8 6% 3 2% 6 3% 1 1% 1 1% - 2 2% 3 2% 2 2% 1 1% 5 4% 1 1% - 4 3% - 1 1% 5 4% 2 1% 3 2% - 1 1% 3 2% 7 5% 3 4% 4 2% 8 3% 2 2% 2 2% 4 2% 3 1% 3 2% 1 1% 3 1% 8 3% 2 1% 3 2% 4 3% 5 4% Q 1 1% 7 5% 6 4% 2 1% 11 6% 3 2% 4 2% 1 1% - - 2 6% 6 7% 1 3% 2 1% 1 1% 4 3% 1 1% 1 3% 5 6% NO 3 4% 3 1% - 3 2% - - - - 1 0% 2 1 1% 1 1 1% 1 - - 4 1% 4 1% 4 1% 4 1% 4 1% 4 1% 3 1% 5 1% 24 5% 8 2% 7 1% 5 1% - 4 1% 19 4% - 7 1% 5 1% 5 1% 2 0% 17 4% 5 1% 4 1% 4 1% 4 1% 17 4% - - 1 5% 9 2% 6 1% - - - - - - - - - 1 11% - 1 8% 1 8% 1 6% 2 9% 1 5% 5 1% 17 4% - 1 11% 2 3% - - - - - - 8 2% - 2 1% - 1 11% - - - 1 6% - 6 1% - - - - - - - - - - 2 - - - - 1 - 1 2 0% 3 - - Other friends / acquaintances / family members mentions Automobile Associations (NET) 1% 7 1% 1% 3 1% 1% 4 2% 5 1% 2 0% 6 1% 2 1% 1 0% 6 2% 3 2% 1 1% - 4 1% 2 0% 58 12% 4 1% 2 1% 40 13% - - 18 10% 1 2% 6 13% Personal experience / I have personal knowledge 10 2% 9 3% 1 1% All of them / all sites / various sites 9 2% 8 2% 8 2% 4 1% 3 1% 17 4% 27 6% 6 2% 6 2% 3 1% 1 0% 3 1% 12 4% 18 6% 87 18% 46 15% CAA / CAA Online BCAA Insurance Company (NET) ICBC / ICBC review My insurance company Other Mentions (NET) Government / government sites RDPRM Used common sense Both / both policies Other mentions Nothing Don't know / not stated 1% - 0% 6 2% - - 1 2% 1 2% 2 1% 5 2% 1 0% 3 1% 1 2% - - - - - - - - - - - - 3% 5 7% 1% 4 2% 1% 2 1% 1% 3 2% 1% 1 1% 2 1% 2 1% 5 2% 2 1% - 3 2% - 1 1% - 1 1% 1 1% 2 1% - - 1 1% 19 14% 1 1% 16 12% 2 1% - 11 13% 4 2% 1 0% 28 11% 7 5% N 3 2% 2 1% - 3 2% - 1 1% 5 7% - - 1 1% - 1 1% - - - - - - - - - - - - - 8 11% 4 9% 1 1% 21 15% 12 18% 3 9% 1 1% 1 1% 18 11% 34 13% 2 2% 5 5% J 4 4% 1 1% 10 10% - 2 1% 8 3% 2 2% 3 4% 1 2% 4 3% - - 1 1% 2 1% 3 2% 2 1% 5 3% 3 2% - 1 2% 1 2% 1 2% - 1 1% 1 1% - 1 2% - - 1 3% - - 5 3% 2 1% - 1 1% 1 1% 3 3% 5 5% 1 1% 1 1% 2 3% 6 8% 1 2% - 1 1% - 2 2% 3 4% 2 2% - 3 6% 2 4% 6 2% 4 2% 6 2% 2 1% 2 1% 7 3% 15 6% 1 1% 2 2% - 5 3% 9 5% 2 1% 3 2% 1 1% 2 1% 1 1% 7 4% 10 6% 1 2% 4 9% 9 6% 7 5% 1 1% 1 1% 4 2% 3 1% 6 2% 2 1% 2 1% 9 4% 7 3% 41 24% B 13 27% F 37 22% 37 15% 18 17% 11 15% 9 20% 32 22% 10 15% - - 1% - 2 2% 3 1% - Comparison Groups: BC/DEF/GHIJKL/MNO/PQR/STUV/WX/YZ Independent T-Test for Means (equal variances), Independent Z-Test for Percentages (pooled proportions) Uppercase letters indicate significance at the 95% level. ACC Custom Express Vision Critical Nov. 22, 2012 D 3 4% 8 12% - 1 3% 1 3% 4 12% K 7 21% 3 4% 10 12% N 9 11% 50 20% M 2 1% 1 1% 5 4% 10 7% N 28 20% 31 16% R 4 2% 8% 1 8% 3 4% Q 1 1% 2 3% 2 3% 1 11% - - - - - 1 11% 1 11% - - 1 8% - 1 13% - - 1 1% 1 1% 5 6% - 1 13% - - - - - - 2 22% 3 23% 1 11% - 1 6% 1 6% 2 12% 1 6% 1 6% - 5% 1 5% 1% 7 1% 1 5% - 5 1% 2 0% 6 1% - - 5 23% 4 1% 2 0% 58 12% - - - - - 2 3% - - 1 11% - - 1 5% 10 2% - 2 3% - - - - - - - - - - - - - - 1 11% - - - - - - 3 23% - - 1 5% 3 14% - - - - - - - - 1 1% 7 9% - - - - - - 2 22% - 1 11% - 2 12% 1 5% 9 2% 8 2% 8 2% 4 1% 3 1% 17 4% 27 6% - 7 5% 5 4% 4 2% 6 3% 5 3% 3 2% 3 2% 6 3% 13 7% 22 17% 34 17% 10 13% 2 22% 4 50% 3 33% 3 23% 6 35% 6 27% 87 18% - 1 1% 2 2% 3 2% 1 1% - - Table 17 Q10. Did you encounter any type of online fraud while shopping for or selling a car via a classifieds website? Gender Total (A) BASE: Purchased or sold a vehicle in the past year in Q4 Contacted by a buyer whom I recognized was a scammer Ad placed by dealer posing as private seller online, but who identified as a dealer Paid a seller for a car that was not delivered Bought from a "curbsider" or dealer posing as private seller Paid a seller for a car I was unable to view in person beforehand, and the car Paid a buyer a refund because their cashier's cheque was above my selling price and later found out the cashier's cheque was fraudulent Buyer / seller was out of the country / overseas Fake / suspicious looking ads Contacted by a company who claimed to have a buyer Other mentions None of these Don't know / not stated 1006 127 13% Male (B) Age Female (C) 405 39 10% 54 5% 10 1% 9 1% 9 1% 7 1% 601 88 15% C 32 5% 8 1% 7 1% 8 1% 5 1% 7 1% 5 0% 4 0% 3 0% 808 80% 5 1% 3 0% 3 0% 1 0% 469 78% 2 0% 2 0% 1 0% 2 0% 339 84% B - 22 5% 2 0% 2 0% 1 0% 2 0% 18-34 (D) 35-54 (E) 120 24 20% EF 8 7% 1 1% 1 1% 3 3% 5 4% EF 1 1% 91 76% Region 55+ (F) 427 54 13% 459 49 11% 19 4% 6 1% 5 1% 3 1% 1 0% 27 6% 3 1% 3 1% 3 1% 1 0% 5 1% 2 0% 3 1% 1 0% 343 80% 2 0% 3 1% 1 0% 1 0% 374 81% BC (G) AB (H) SK/MB (I) Education ON (J) QC (K) Household Income ATL (L) 141 21 15% 104 9 9% 271 31 11% 149 14 9% 103 9 9% 183 24 13% 527 61 12% 296 42 14% 273 28 10% 409 53 13% 4 3% 1 1% 1 1% 1 1% - 5 5% - 18 7% 4 1% 2 1% 2 1% 3 1% 8 5% 3 2% 1 1% 3 2% 1 1% 6 6% 1 1% - 8 4% 1 1% 1 1% 2 1% - 26 5% 4 1% 3 1% 4 1% 4 1% 20 7% 5 2% 5 2% 3 1% 3 1% 10 4% 3 1% 1 0% 4 1% 1 0% 24 6% 1 0% 1 0% 2 0% 3 1% 1 0% - 2 1% 1 1% 1 1% - - 4 1% 3 1% - - - - 1 1% - - 1 1% - 3 1% 3 1% - 1 0% 221 82% - - 1 1% - 85 83% 148 81% 1 1% - - 1 0% 1 0% 1 0% 1 0% 228 84% R 1 0% 4 1% 3 1% 2 0% - 123 83% 3 1% 2 0% 3 1% 1 0% 426 81% 3 1% 1 0% 178 75% 3 3 1 2 2 0% 0% 0% 0% 1% Comparison Groups: BC/DEF/GHIJKL/MNO/PQR/STUV/WX/YZ Independent T-Test for Means (equal variances), Independent Z-Test for Percentages (pooled proportions) Uppercase letters indicate significance at the 95% level. ACC Custom Express Vision Critical Nov. 22, 2012 D 111 79% - 1 1% 90 87% G - - Impact of Online Fraud (Q2b) $50,00 0 To Less Definite Probabl Probabl Definite Top 2 Bottom College Univ Than ly y y Did ly Did Box 2 Box HS Or / Tech Degree <$50,0 $100,0 $100,0 Affecte Affecte Not Not Affecte Did Not Less School + 00 00 00+ d d Affect Affect d Affect (M) (N) (O) (P) (Q) (R) (S) (T) (U) (V) (W) (X) 238 43 18% IJKL 13 5% 1 0% 4 2% 2 1% 2 1% 1 1% 1 1% - Purchased/Sold Vehicle Using Online Classifieds 1 1% 3 1% 2 1% 234 79% - 331 81% 2 0% 194 35 18% P 10 5% 2 1% 3 2% 2 1% 2 1% 16 3 19% V 2 13% - 21 2 10% 28 1 4% 55 2 4% 37 5 14% X 4 11% - 2 10% - 1 4% - - - - 1 2% 1 2% - - - - - - - 1 4% - - - 1 1% - 1 1% - - - - - - - - - - - - - 1 1% 2 1% 144 74% - - - - - - - - - - - - 11 69% 17 81% 25 89% 28 76% - - - - 51 93% S - 76 92% W - - - Yes, I Have (Y) No, I Have Not (Z) 83 3 4% 1006 127 13% - 2 2% 1 1% - 54 5% 10 1% 9 1% 9 1% 7 1% - 7 1% 5 0% 4 0% 3 0% 808 80% - 3 0% - - - Table 18 Q10a. Please describe in detail the type of fraud you encountered. Gender Total (A) Male (B) Age Female (C) 18-34 (D) Region 35-54 (E) 55+ (F) BC (G) AB (H) SK/MB (I) Education ON (J) QC (K) Household Income Purchased/Sold Vehicle Using Online Classifieds Impact of Online Fraud (Q2b) $50,00 0 To Less Definite Probabl Probabl Definite Top 2 Bottom College Univ Than ly y y Did ly Did Box 2 Box HS Or / Tech Degree <$50,0 $100,0 $100,0 Affecte Affecte Not Not Affecte Did Not Less School + 00 00 00+ d d Affect Affect d Affect (M) (N) (O) (P) (Q) (R) (S) (T) (U) (V) (W) (X) ATL (L) Yes, I Have (Y) No, I Have Not (Z) BASE: Purchased or sold a vehicle in the past year AND encountered fraud in Q10 Concerns about Buyer / Seller (NET) 198 95 48% 132 61 46% 66 34 52% 29 10 34% 84 38 45% 85 47 55% The buyer / seller is out of the country / overseas 30 15% 23 17% 7 11% 1 3% 13 15% A Curbsider / a dealer posing as a private seller A third party seller / someone wanting to sell the car for me The buyer is in the Army / Navy 24 12% 9 5% 6 3% 5 3% 4 2% 3 2% 3 2% 3 2% 24 12% 13 10% 7 5% 2 2% 4 3% 3 2% 3 2% 3 2% 1 1% 12 9% 11 17% 2 3% 4 6% 1 2% 1 2% - 3 10% 1 3% 1 3% 1 3% - 8 10% 5 6% 2 2% - - - 2 3% 12 18% 1 3% 5 17% 16 19% D 13 15% 3 4% 3 4% 4 5% 3 4% 2 2% 2 2% 1 1% 5 6% 17 9% 9 7% 8 12% 5 3% 2 1% 69 35% 26 13% 2 2% 1 1% 44 33% 19 14% 3 5% 1 2% 25 38% 7 11% 5 17% F - 12 6% 10 5% 5 3% 5 3% 4 2% 4 2% 3 6 5% 9 7% 2 2% 2 2% 3 2% 2 2% 2 6 9% 1 2% 3 5% 3 5% 1 2% 2 3% 1 The buyer / seller is in another city / province A person selling many cars A dishonest seller / the seller was lying Selling a car they did not own Someone claiming to want to buy the vehicle as a gift Contact with Buyer / Seller (Sub-NET) Sending e-mail / multiple e-mails Aggressive response / contacted several times Phone calls / people calling Payment Related (NET) A PayPal scam / pay through PayPal / accepting PayPal payments The seller wanted money / cash up front / a down payment Overpayment and refund scam Asked for a bank account / banking information Wanted to pay through money transfer / Western Union Sent a fake Cashier's Cheque / Money Order Tax fraud / was not willing to pay taxes Wanted to pay by cheque 60 31 52% I 10 17% 30 18 60% I 8 27% 14 3 21% 50 24 48% 26 12 46% 18 7 39% 35 13 37% 101 48 48% 62 34 55% 45 17 38% 78 41 53% 50 27 54% 5 - 4 3 75% 3 - 4 - 9 3 33% 7 - 198 95 48% - - 6 12% 6 23% - 5 14% 17 17% 8 13% 5 11% 13 17% 8 16% - 1 25% - - 1 11% - 30 15% - 9 15% 4 7% 4 7% - 1 7% 1 7% - 6 12% - 1 4% - - - - - - - - - - - - - - - - - - - - - - - 1 11% - - - 1 25% - - - - - - - - - - - 1 11% - - - 1 3% - 1 25% - - - - - - - - - 1 4% 2 11% 1 3% 1 2% 3 7% 8 10% - - - - - - 3 7% 6 8% 1 2% 1 2% 2 4% 11 22% P 7 14% 24 12% 9 5% 6 3% 5 3% 4 2% 3 2% 3 2% 3 2% 24 12% - - - 5 11% 1 2% 3 7% 1 2% - 5 10% 3 6% 3 6% - 1 4% 2 8% 1 4% - 8 13% 2 3% 3 5% 3 5% 1 2% 1 2% - - - 12 12% 4 4% 2 2% 2 2% 3 3% 2 2% 2 2% 1 1% 12 12% 12 15% 5 6% - - 4 11% 3 9% 1 3% - - - 4 22% 1 6% - - 3 10% 3 10% 1 3% 1 3% - - - - - - - 17 9% - - 1 1% 1 1% 29 37% 16 21% 3 6% 1 2% 17 34% 4 8% - - - - - - 5 3% 2 1% 69 35% 26 13% - 6 8% 4 5% - 1 2% 2 4% 2 4% 2 4% 2 4% 1 2% 1 12 6% 10 5% 5 3% 5 3% 4 2% 4 2% 3 - - - - 2 3% 9 15% - - 3 10% 1 7% 1 2% 3 6% 3 6% 1 2% 2 4% 1 2% 8 16% 3 4% 5 8% 3 10% 1 7% 7 14% - 1 6% 1 3% 9 9% 2 3% 11 18% M 7 11% 4 5% 1 1% 31 37% 8 10% 1 1% 1 1% 26 31% 11 13% 3 5% 1 2% 24 40% 11 18% - - 1 4% - - - 11 31% 5 14% 2 2% 1 1% 39 39% 16 16% 3 5% 1 2% 19 31% 5 8% 3 5% 6 10% 3 5% 2 3% - - 2 6 7% 3 4% 1 1% 1 1% 1 1% 4 5% 1 6 6% 7 7% 2 2% 3 3% 2 2% 2 2% 2 5 8% - 1 3% 1 3% - 6 7% 5 6% 4 5% 3 4% 2 2% - - 12 41% 7 24% E 2 7% - 1 1% 1 1% 1 1% 1 1% 14 17% F 9 11% 1 2% 1 1 7% - - - 1 2% - 10 33% 5 17% 4 29% 1 7% 18 36% 7 14% 8 31% 1 4% 1 6% 5 28% 1 6% 2 7% 1 3% 1 3% - 2 14% - 5 10% 1 2% - - - 2 8% - - 1 3% - 1 7% - - - - 2 4% 2 1 4% 1 4% 2 8% - 1 6% 1 6% 1 6% - - 1 3% 3 9% 1 3% 1 3% - 3 5% 2 3% 1 2% 1 2% 1 1 2% - 17 38% 5 11% 3 7% 3 7% 2 4% 1 2% 2 4% 1 3 4% 3 4% 1 1% 2 3% - 2 3% 2 3% 1 1% 1 - - - - - - - - 2 40% 2 40% 2 50% 1 25% - 1 25% - 4 44% 3 33% 1 14% - 1 20% - 1 25% - - - - - - - - 1 25% - 2 22% - - - - - - - - - - - - 1 14% - - - - - - - - - - - - - - - - - - Wanted to pay by cheque The buyer wanted the vehicle before paying for it Other payment related mentions Vehicle Shipping / Delivery (NET) Wanted to send someone / an agent to pick up the car Asking for us to pay for transportation / delivery Shipping scam / asking for the vehicle to be shipped / delivered Buyer saying they would pay for the car to be shipped to them Delayed delivery 2% 2 1% 2 1% 40 20% 2% 1 1% 1 1% 27 20% 2% 1 2% 1 2% 13 20% 21 11% 7 4% 5 3% 4 2% 2 1% 2 1% 30 15% 13 10% 6 5% 5 4% 3 2% - 8 12% 1 2% - 13 7% 10 5% 6 3% 3 2% 30 15% 10 5% 12 9% C 6 5% 2 2% 1 1% 19 14% 6 5% 9 5% 6 5% 1 3% 5 17% 2 7% 1 3% 1 3% - 2% 2 2% 1 1% 14 17% 8 10% 2 2% 2 2% 1 1% - 1% - 2% 1 2% - 4% - - 1 2% 9 18% 1 4% 5 19% 21 25% 13 22% 9 30% 1 7% 8 13% 1 2% 2 3% 1 2% 1 2% - 5 17% 1 3% - - 1 7% - 5 10% 2 4% 2 4% - 3 12% 2 8% - - - 4 7% 2 7% 6 20% - - - - 1 2% 2 3% 1 2% 10 15% 4 14% 1 1% 15 18% 11 13% 4 5% 2 2% 3 4% 1 1% 1 1% 11 13% 1 2% 1 3% 9 11% 3 4% 3 5% 2 7% 4 6% 4 6% 2 3% 11 17% 4 6% 1 3% 1 3% 1 3% 3 10% 1 3% 4 5% 3 4% 1 1% 15 18% 4 5% 5 6% 2 2% 1 1% 12 14% 5 6% - 3 5% 1 3% 5 6% 3 4% 3 17% 8 23% - 4 11% 3 9% - 1 6% - - - - - 4 29% GK 1 7% 11 22% GK 4 8% 1 4% 4 22% 4 11% 1 4% 2 11% 2 6% 1 7% 1 7% 1 7% 2 14% - 6 12% 2 4% - - 1 6% - 1 3% - 10 17% 1 2% 2 7% 1 3% 1 3% 5 17% 3 10% 1 3% 8 23% 4 11% 5 8% 1 3% - 7 4 3 1 4 2 2 4% 3% 5% 3% 5% 2% 3% 3 2 1 1 2 2 2% 2% 2% 1% 2% 3% 2 1 1 2 1% 1% 2% 2% Other Mentions (NET) 26 18 8 4 10 12 7 13% 14% 12% 14% 12% 14% 12% Fraud / all kinds of fraud / scams 6 5 1 2 4 3 3% 4% 2% 2% 5% 5% The ad seemed fishy / fake / a fake website 5 2 3 1 3 1 1 3% 2% 5% 3% 4% 1% 2% I have experience with / knowledge of 2 1 1 2 1 scammers 1% 1% 2% 2% 2% Other mentions 13 10 3 3 5 5 2 7% 8% 5% 10% 6% 6% 3% Nothing 15 10 5 2 7 6 4 8% 8% 8% 7% 8% 7% 7% Don't know / not stated 7 4 3 3 2 2 2 4% 3% 5% 10% 2% 2% 3% Comparison Groups: BC/DEF/GHIJKL/MNO/PQR/STUV/WX/YZ Independent T-Test for Means (equal variances), Independent Z-Test for Percentages (pooled proportions) Uppercase letters indicate significance at the 95% level. ACC Custom Express Vision Critical Nov. 22, 2012 D - Free shipping / shipping was included in the price Cost / Price / Value (NET) The buyer did not try to negotiate the price / wanted to pay full price The car was advertised for much cheaper than the actual value The deal was too good to be true A low-baller Vehicle Condition / Inspection (NET) Did not let us see the car / wanted us to buy the car without seeing it Willing to buy / pay for the car without seeing it Selling a bad car / a lemon / a car the was in an accident The vehicle was not the same as advertised Could not answer questions about the car 1 1% 20 15% 1 2% - 1 3% 5 17% - 1 4% - 1 3% - 2% 1 1% 1 1% 21 21% 2% 1 2% 1 2% 11 18% 10 10% 4 4% 4 4% 2 2% 1 1% 1 1% 16 16% 7 11% - 10 10% O 4 4% 4 4% - 1 2% 1 2% 1 2% 1 2% 10 16% 2% 1 2% - 1% - 2% - - 9 20% 21 27% R 11 14% 5 6% 4 5% 1 1% - 2 4% 5 10% 5 11% 1 2% 1 2% 1 2% 1 2% - - 2 22% 1 14% 3 6% - 1 20% - - - - - - 1 33% - - - 1 25% - 1 11% 1 11% - 1 2% - - 1 25% - - - - - - - 1 11% - 1 14% - - 21 11% 7 4% 5 3% 4 2% 2 1% 2 1% 30 15% - 1 2% 1 2% 8 10% 4 8% 1 20% - - - 1 11% - 13 7% - 2 4% 1 2% 1 2% 8 18% 2 4% 6 8% 4 5% 1 1% 8 10% 4 5% 1 2% 1 2% - - 1 25% - - - - - - - 2 50% 1 25% 1 33% - 1 25% - 1 11% 2 22% 1 11% 1 14% 1 14% - 10 5% 6 3% 3 2% 30 15% 10 5% - - 1 11% - 13 13% 4 4% 5 8% 2 3% 2 3% 9 15% 2 3% - - - - - - 9 5% - - 1 25% - 1 33% - - 1 11% - 1 14% - 7 4% 3 2% 2 1% 26 13% 6 3% 5 3% 2 1% 13 7% 15 8% 7 4% - - - 1 1% 2 3% - 7 14% 2 4% 2 4% 1 2% 2 4% 4 8% 3 6% 4 15% 1 4% - 1 2% 1 2% 2 3% 7 11% 2 3% 1 2% 1 2% 3 5% 6 10% 4 6% 3 7% 1 2% - 1 7% - 1 6% 2 11% - 4 4% 2 2% - 5 11% 1 2% 1 2% - 10 13% 2 3% 1 1% 2 3% 5 6% 3 4% 2 3% - 1 33% - 2 6% - 2 6% 3 9% - 1 25% 1 14% - 2 11% - 1 20% - - 2 8% - 3 12% 4 15% 1 4% - 3 33% 2 4% - 1 7% 3 21% 1 7% - - 1 7% 1 7% - 3 10% - - 1 25% 1 1% - - - 2 4% - - - - 4 6% - - 2% 2 1% 2 1% 40 20% - 3 3% - - 1 25% 2 6% - - - 2 11% - - 2 40% 1 4% - - 1 2% 6 12% 3 12% - 3 9% 1 3% - - 1 1% 17 22% 8 16% 6 12% G - - - 5 11% 1 6% 2 11% - 2 7% - - 1 4% - - 1 6% 1 6% - 1 3% - 1 3% - - 1 6% - 16 16% 3 3% 4 4% 1 1% 8 8% 6 6% 3 3% 3 7% 4 9% 3 7% 11 22% 1 2% 6 12% Q 3 6% 2 4% 5 10% 2 4% 2 4% 1 2% 5 10% 2 4% 1 20% - - - - - - - - - - - 2 40% 1 20% - 1 25% 1 25% - - 2 50% - 2 29% - - - 3 33% 2 22% - - - - - - - 1 20% - - - 1 25% - 1 33% - 2 50% - 1 11% 1 11% - 2 29% 1 14% - - - - - - - Table 19 Q11. Was your experience with fraud resolved? Gender Total (A) Male (B) Age Female (C) 18-34 (D) 35-54 (E) Region 55+ (F) BC (G) AB (H) SK/MB (I) Education ON (J) QC (K) ATL (L) Household Income Purchased/Sold Vehicle Using Online Classifieds Impact of Online Fraud (Q2b) $50,00 0 To Less Definite Probabl Probabl Definite Top 2 Bottom College Univ Than ly y y Did ly Did Box 2 Box HS Or / Tech Degree <$50,0 $100,0 $100,0 Affecte Affecte Not Not Affecte Did Not Less School + 00 00 00+ d d Affect Affect d Affect (M) (N) (O) (P) (Q) (R) (S) (T) (U) (V) (W) (X) Yes, I Have (Y) No, I Have Not (Z) BASE: Purchased or sold a vehicle in the past year AND encountered fraud in Q10 Yes, it was No, it was not 198 153 77% 132 101 77% 66 52 79% 29 20 69% 84 66 79% 85 67 79% 45 23% 31 23% 14 21% 9 31% 18 21% 18 21% 60 52 87% K 8 13% Comparison Groups: BC/DEF/GHIJKL/MNO/PQR/STUV/WX/YZ Independent T-Test for Means (equal variances), Independent Z-Test for Percentages (pooled proportions) Uppercase letters indicate significance at the 95% level. ACC Custom Express Vision Critical Nov. 22, 2012 D 30 25 83% K 5 17% 14 11 79% 3 21% 50 38 76% K 12 24% 26 13 50% 18 14 78% 35 28 80% 101 72 71% 13 50% GHJ 4 22% 7 20% 29 29% O 62 53 85% N 9 15% 45 33 73% 78 59 76% 50 42 84% 5 3 60% 4 2 50% 3 2 67% 4 3 75% 9 5 56% 7 5 71% 198 153 77% - 12 27% 19 24% 8 16% 2 40% 2 50% 1 33% 1 25% 4 44% 2 29% 45 23% - Table 20 Q13. Are you satisfied or dissatisfied with the arbitration or mediation process of the parties involved in your fraud's resolution or attempted resolution? Gender Total (A) Male (B) Age Female (C) 18-34 (D) 35-54 (E) Region 55+ (F) BC (G) AB (H) SK/MB (I) Education ON (J) QC (K) ATL (L) Household Income Purchased/Sold Vehicle Using Online Classifieds Impact of Online Fraud (Q2b) $50,00 0 To Less Definite Probabl Probabl Definite Top 2 Bottom College Univ Than ly y y Did ly Did Box 2 Box HS Or / Tech Degree <$50,0 $100,0 $100,0 Affecte Affecte Not Not Affecte Did Not Less School + 00 00 00+ d d Affect Affect d Affect (M) (N) (O) (P) (Q) (R) (S) (T) (U) (V) (W) (X) Yes, I Have (Y) No, I Have Not (Z) BASE: Purchased or sold a vehicle in the past year AND encountered fraud in Q10 198 48 24% 31 16% 12 6% 12 6% 132 29 22% 22 17% 10 8% 10 8% 66 19 29% 9 14% 2 3% 2 3% 29 7 24% 7 24% 1 3% 84 23 27% 12 14% 6 7% 4 5% 85 18 21% 12 14% 6 7% 7 8% 60 13 22% 6 10% 5 8% 1 2% 30 6 20% 4 13% 2 7% - Not sure 95 48% 61 46% 34 52% 14 48% 39 46% 42 49% 28 42% 14 48% 35 42% 30 35% 35 58% JK 19 32% 18 60% J 10 33% NET: Top 2 Box 79 40% 51 39% 24 20 4 1 10 13 6 12% 15% 6% 3% 12% 15% 10% Comparison Groups: BC/DEF/GHIJKL/MNO/PQR/STUV/WX/YZ Independent T-Test for Means (equal variances), Independent Z-Test for Percentages (pooled proportions) Uppercase letters indicate significance at the 95% level. ACC Custom Express Vision Critical Nov. 22, 2012 D 2 7% Very satisfied Moderately satisfied Moderately dissatisfied Very dissatisfied NET: Bottom 2 Box 14 3 21% 2 14% - 26 7 27% 6 23% - 18 7 39% 2 11% - 18 36% 4 15% G 9 35% 5 36% 23 46% 2 14% 9 18% 2 14% G 7 50% 50 12 24% 11 22% 5 10% 4 8% 101 23 23% 14 14% 8 8% 9 9% 62 13 21% 9 15% 3 5% 2 3% 45 13 29% 8 18% 3 7% 3 7% 78 18 23% 11 14% 6 8% 8 10% 50 12 24% 10 20% 2 4% 1 2% 5 1 20% - 1 6% 35 12 34% 8 23% 1 3% 1 3% 4 1 25% 2 50% - 3 1 33% 1 33% - 4 2 50% - - 1 25% 1 33% 8 44% 13 37% 47 47% 35 56% 18 40% 35 45% 25 50% 4 80% - 13 50% 9 50% 37 37% 22 35% 21 47% 4 15% 1 6% 20 57% NO 2 6% 29 37% 22 44% 1 20% 17 17% 5 8% 6 13% 14 18% 3 6% - - 9 2 22% 2 22% - 7 3 43% 1 14% - - 1 14% 198 48 24% 31 16% 12 6% 12 6% - 1 11% - 2 50% 4 44% 2 29% 95 48% - 3 75% 2 67% 2 50% 4 44% 4 57% 79 40% - 1 25% 1 33% - 1 11% 1 14% 24 12% - - - Table 21 Q. Gender Gender BASE: All Respondents Male Female Total (A) 1006 601 60% 405 40% Male (B) Age Female (C) 18-34 (D) 601 601 100% 405 - 120 47 39% - 405 100% 73 61% EF 35-54 (E) 427 229 54% D 198 46% F Region 55+ (F) 459 325 71% DE 134 29% BC (G) AB (H) SK/MB (I) Education ON (J) QC (K) ATL (L) Household Income Impact of Online Fraud (Q2b) $50,00 0 To Less Definite Probabl Probabl Definite Top 2 Bottom College Univ Than ly y y Did ly Did Box 2 Box HS Or / Tech Degree <$50,0 $100,0 $100,0 Affecte Affecte Not Not Affecte Did Not Less School + 00 00 00+ d d Affect Affect d Affect (M) (N) (O) (P) (Q) (R) (S) (T) (U) (V) (W) (X) 238 147 62% 141 82 58% 104 69 66% 271 161 59% 149 86 58% 103 56 54% 183 115 63% 527 318 60% 296 168 57% 273 156 57% 409 251 61% 91 38% 59 42% 35 34% 110 41% 63 42% 47 46% 68 37% 209 40% 128 43% 117 43% R 158 39% Comparison Groups: BC/DEF/GHIJKL/MNO/PQR/STUV/WX/YZ Independent T-Test for Means (equal variances), Independent Z-Test for Percentages (pooled proportions) Uppercase letters indicate significance at the 95% level. ACC Custom Express Vision Critical Nov. 22, 2012 D Purchased/Sold Vehicle Using Online Classifieds 194 132 68% P 62 32% Yes, I Have (Y) No, I Have Not (Z) 16 8 50% 21 13 62% 28 16 57% 55 29 53% 37 21 57% 83 45 54% 1006 601 60% - 8 50% 8 38% 12 43% 26 47% 16 43% 38 46% 405 40% - Table 22 Q. Age Gender BASE: All Respondents 18-34 Total (A) 1006 120 12% Male (B) Female (C) 35-54 (E) 55+ (F) BC (G) AB (H) SK/MB (I) Education ON (J) QC (K) ATL (L) 459 - 238 28 12% 141 15 11% 104 11 11% 271 31 11% 149 24 16% 103 11 11% 183 16 9% 527 55 10% - 427 100% - 93 39% 63 45% 40 38% 129 48% 58 39% 44 43% 69 38% 227 43% 325 459 117 54% 100% 49% C Comparison Groups: BC/DEF/GHIJKL/MNO/PQR/STUV/WX/YZ Independent T-Test for Means (equal variances), Independent Z-Test for Percentages (pooled proportions) Uppercase letters indicate significance at the 95% level. ACC Custom Express Vision Critical Nov. 22, 2012 D 63 45% 53 51% 111 41% 67 45% 48 47% 98 54% O 245 46% O 55+ 459 46% 229 38% Household Income Impact of Online Fraud (Q2b) $50,00 0 To Less Definite Probabl Probabl Definite Top 2 Bottom College Univ Than ly y y Did ly Did Box 2 Box HS Or / Tech Degree <$50,0 $100,0 $100,0 Affecte Affecte Not Not Affecte Did Not Less School + 00 00 00+ d d Affect Affect d Affect (M) (N) (O) (P) (Q) (R) (S) (T) (U) (V) (W) (X) 427 - 427 42% 405 73 18% B 198 49% B 134 33% 18-34 (D) Region 120 120 100% 35-54 601 47 8% Age Purchased/Sold Vehicle Using Online Classifieds Yes, I Have (Y) No, I Have Not (Z) 296 49 17% MN 131 44% 273 34 12% 409 42 10% 194 22 11% 16 1 6% 21 2 10% 28 3 11% 55 8 15% 37 3 8% 83 11 13% 1006 120 12% - 83 30% 9 43% 10 36% 18 33% 16 43% 28 34% 427 42% - 156 57% QR 103 53% P 69 36% 7 44% 116 39% 186 45% P 181 44% R 8 50% 10 48% 15 54% 29 53% 18 49% 44 53% 459 46% - Table 23 Q. Region Gender BASE: All Respondents BC Total (A) 1006 238 24% Male (B) Age Female (C) 18-34 (D) 35-54 (E) Region 55+ (F) BC (G) AB (H) SK/MB (I) Education ON (J) QC (K) ATL (L) 601 147 24% 405 91 22% 120 28 23% 427 93 22% 459 117 25% 238 238 100% 141 - 104 - 271 - 149 - 103 - 183 32 17% 141 14% 82 14% 59 15% 15 13% 63 15% 63 14% - 141 100% - - - - 27 15% SK/MB 104 10% 271 27% 69 11% 161 27% 35 9% 110 27% 11 9% 31 26% 53 12% 111 24% - - - - - - - 104 100% - 271 100% - - 22 12% 35 19% 149 15% 86 14% 63 16% 24 20% 40 9% 129 30% F 58 14% 67 15% - - - - 149 100% - 103 56 47 11 44 48 10% 9% 12% 9% 10% 10% Comparison Groups: BC/DEF/GHIJKL/MNO/PQR/STUV/WX/YZ Independent T-Test for Means (equal variances), Independent Z-Test for Percentages (pooled proportions) Uppercase letters indicate significance at the 95% level. ACC Custom Express Vision Critical Nov. 22, 2012 D - - - - 103 100% QC ATL Impact of Online Fraud (Q2b) $50,00 0 To Less Definite Probabl Probabl Definite Top 2 Bottom College Univ Than ly y y Did ly Did Box 2 Box HS Or / Tech Degree <$50,0 $100,0 $100,0 Affecte Affecte Not Not Affecte Did Not Less School + 00 00 00+ d d Affect Affect d Affect (M) (N) (O) (P) (Q) (R) (S) (T) (U) (V) (W) (X) AB ON Household Income Purchased/Sold Vehicle Using Online Classifieds 48 26% NO 19 10% 527 139 26% M 76 14% 296 67 23% 273 65 24% 409 93 23% 194 58 30% 38 13% 31 11% 58 14% 31 16% 54 10% 141 27% M 69 13% 28 9% 95 32% M 32 11% 31 11% 53 19% 48 9% 36 12% 40 10% 117 29% P 62 15% R 39 10% 58 21% QR 35 13% Yes, I Have (Y) No, I Have Not (Z) 16 5 31% U 3 19% 21 4 19% 28 1 4% 55 10 18% 37 9 24% 83 11 13% 1006 238 24% - 1 5% 7 13% 4 11% 17 20% 141 14% - 18 9% 56 29% P 16 8% 1 6% 3 19% 2 10% 6 29% 10 36% TV 3 11% 6 21% 3 5% 16 29% 3 8% 9 24% 6 7% 22 27% 104 10% 271 27% - 1 6% 6 29% 5 18% 15 27% 7 19% 20 24% 149 15% - 15 8% 3 19% 2 10% 3 11% 4 7% 5 14% 7 8% 103 10% - - Table 24 Q. Education Gender BASE: All Respondents HS or less Total (A) 1006 183 18% Male (B) Age Female (C) 18-34 (D) 35-54 (E) 601 115 19% 405 68 17% 120 16 13% 427 69 16% Region 55+ (F) College/tech school 527 52% 318 53% 209 52% 55 46% 227 53% 459 98 21% DE 245 53% Univ degree+ 296 29% 168 28% 128 32% 49 41% EF 131 31% 116 25% BC (G) AB (H) 238 32 13% 141 27 19% 139 58% KL 67 28% Comparison Groups: BC/DEF/GHIJKL/MNO/PQR/STUV/WX/YZ Independent T-Test for Means (equal variances), Independent Z-Test for Percentages (pooled proportions) Uppercase letters indicate significance at the 95% level. ACC Custom Express Vision Critical Nov. 22, 2012 D SK/MB (I) Education ON (J) 271 35 13% 76 54% 104 22 21% J 54 52% 38 27% 28 27% 95 35% K 141 52% QC (K) ATL (L) Household Income Purchased/Sold Vehicle Using Online Classifieds Impact of Online Fraud (Q2b) $50,00 0 To Less Definite Probabl Probabl Definite Top 2 Bottom College Univ Than ly y y Did ly Did Box 2 Box HS Or / Tech Degree <$50,0 $100,0 $100,0 Affecte Affecte Not Not Affecte Did Not Less School + 00 00 00+ d d Affect Affect d Affect (M) (N) (O) (P) (Q) (R) (S) (T) (U) (V) (W) (X) 149 48 32% GHJL 69 46% 103 19 18% 183 183 100% 527 - 296 - 48 47% - 527 100% - 32 21% 36 35% K - - 296 100% 273 71 26% QR 150 55% 409 75 18% R 211 52% 194 16 8% 16 3 19% 21 - 28 11 39% 55 13 24% 37 3 8% 92 47% 11 69% 11 39% 25 45% 52 19% 123 30% P 86 44% PQ 2 13% 16 76% UV 5 24% 6 21% 17 31% 27 73% X 7 19% Yes, I Have (Y) No, I Have Not (Z) 83 24 29% W 36 43% 1006 183 18% - 527 52% - 23 28% 296 29% - Table 25 Q. Household Income Gender BASE: All Respondents <$50,000 $50,000 to less than $100,000 $100,000+ Don't know/prefer not to say Total (A) 1006 273 27% 409 41% 194 19% 130 13% Male (B) Age Female (C) 18-34 (D) 601 156 26% 405 117 29% 251 42% 132 22% C 62 10% 158 39% 62 15% 120 34 28% E 42 35% 22 18% 68 17% B 22 18% F 35-54 (E) 427 83 19% 186 44% 103 24% F 55 13% Region 55+ (F) 459 156 34% E 181 39% 69 15% 53 12% BC (G) 238 65 27% J 93 39% 58 24% KL 22 9% Comparison Groups: BC/DEF/GHIJKL/MNO/PQR/STUV/WX/YZ Independent T-Test for Means (equal variances), Independent Z-Test for Percentages (pooled proportions) Uppercase letters indicate significance at the 95% level. ACC Custom Express Vision Critical Nov. 22, 2012 AB (H) 141 31 22% 58 41% 31 22% K 21 15% SK/MB (I) 104 31 30% J 40 38% 18 17% 15 14% Education ON (J) 271 53 20% 117 43% 56 21% K 45 17% GK QC (K) ATL (L) Household Income Purchased/Sold Vehicle Using Online Classifieds Impact of Online Fraud (Q2b) $50,00 0 To Less Definite Probabl Probabl Definite Top 2 Bottom College Univ Than ly y y Did ly Did Box 2 Box HS Or / Tech Degree <$50,0 $100,0 $100,0 Affecte Affecte Not Not Affecte Did Not Less School + 00 00 00+ d d Affect Affect d Affect (M) (N) (O) (P) (Q) (R) (S) (T) (U) (V) (W) (X) 149 58 39% GHJ 62 42% 16 11% 103 35 34% HJ 39 38% 15 15% 183 71 39% NO 75 41% 16 9% 13 9% 14 14% 21 11% 527 150 28% O 211 40% 92 17% M 74 14% Yes, I Have (Y) No, I Have Not (Z) 296 52 18% 273 273 100% 409 - 194 - 16 3 19% 21 7 33% 28 7 25% 55 20 36% 37 10 27% 83 27 33% 1006 273 27% - 123 42% 86 29% MN 35 12% - - 8 38% 5 24% 15 54% 2 7% 23 42% 6 11% 409 41% 194 19% - 1 5% 4 14% 6 11% 12 32% 10 27% X 5 14% 38 46% 8 10% - 4 25% 5 31% UV 4 25% - - 409 100% - 10 12% 130 13% - 194 100% - -