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Micro
One year after launch,
NEST is shaking up the
UK pension system.
Macro
Growing inequality mars recovery
in the US, says political economist
and commentator Robert Reich.
Meta
102-year-old Creole singer and
trumpeter Lionel Ferbos looks
back at a life like few others.
Chart Art
2010
The digital universe
Rapid expansion:
by 2010, computers,
devices and human
digital activity had
generated roughly
1,227 exabytes
of data.
SE LE CTE D AWARDS for project m print and
on l in e FROM 2011-2014
Annual Multimedia Awards: Silver (Websites)
Astrid Awards: Grand Award (Best of Cover Design – Magazines);
Gold (Covers: Magazines); Silver (Websites: App Launch);
Honors (Photography: Repor tage)
2020 By 2020, this
As technology advances, data
generation accelerates
dramatically. The outcome is an
expanding and increasingly
complex digital universe.
amount is expected
to have multiplied
almost fortyfold, to
40,026 exabytes.
MASTHE AD
to buy, sell or hold any securit y and shall not be deemed an offer to sell
or a solicitation of an offer to buy any securit y.
Publisher
Allianz SE
International Pensions
Königinstrasse 28
80802 Munich, Germany
[email protected]
w w w.allianz.com
· P ROJEC T M is issued in the U.S. by Allianz Global Investors U.S. LLC , an
investment adviser registered with the U.S. Securities and E xchange
Commission
Executive Editor
Brigitte Miksa, International Pensions
Emerging Markets’ Share
Emerging markets take up a
growing share of the total amount
of data generated by humans and
machines. In 2012, total emerging
markets share of the digital
universe made up around
one-third of the generated data.
By 2020 it could reach two-thirds.
Editorial Board
Petra Brandes, Glenn Dial, Dirk Hellmuth, Andreas Hilka, Arne Holzhausen,
Tony Hore, Paul Kelash, Sue King, Jens Reisch, Stacy Schaus, Gerhard
Scheuenstuhl, Reinhardt Schink, Cathy Smith, Mar y Wadsworth-Darby,
John Wallace, Bonnie Wu
Editorial
Christian Gressner, Lois Hoyal, Greg Langley (EiC), Christine Madden,
Oliver Purcell, Marilee Williams
Contributors
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Nikhil Mehta, Justin Pugsley, Bernd Scharrer, Stacy Schaus, Jan Oliver Schwarz
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Copyright: The contents of this magazine are protected by copyright law.
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Machine-made data
Machines and smart devices such
as sensors generate growing
amounts of data. The percentage
share of automated, machinegenerated data has grown from
11% in 2005 to 30% in 2012, and is
expected to reach 42% by 2020.
2
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The PROJECT M cover was created to visualize the expansion of the digital universe. To do so, raw
growth-projection data was fed into a computer program. The program then generated 3-D visualization models of
the growth between today and 2020, at which time the combined data volume is expected to exceed 40,000
exabytes – or 40,000 billion gigabytes. (Artwork/Generative Design: Peter Riedel – www.peterriedel.com)
[email protected]
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Allianz • 63
Opening Bell
Brigitte Miksa
Head of International Pensions
Finding value from
the chatter
“Everyone talks about it, nobody really knows
how to do it, everyone thinks everyone else is doing it,
so everyone claims they are doing it. …”
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Audio
When behavioral economist Dan Ariely posted
his comment on Facebook last year, he poked
fun at the ‘big data’ hype by comparing it to
teenage sex. With 1,676 likes and 82 comments,
few of them disagreeing, Ariely’s quip caused
hardly a ripple on the ocean of information.
The chatter about big data, the collection
and analysis of petabytes of information,
had exploded in mid-2011. Worldwide Google
searches for the term, coined nearly a decade
earlier in astronomy and genomics, have
increased almost by a factor of 10 over the past
three years. Yet, despite Ariely’s cynicism,
there is far more to big data than just talk.
Both humans and machines are creating
a swelling sea of information by churning
out facts which describe their very life cycle –
be it the millions of photos uploaded hourly
to social media networks like Facebook, or
the terabytes of data that machines like
jet engines create during a 60-minute flight.
Once digitalized, the amount of information
doubles roughly every three years, reducing its
analog cousin to irrelevance.
But big data is not just about quantity, it’s
about applying mathematics and increasingly
sophisticated algorithms to extract hidden
insights and meaning from enormous
amounts of unstructured information.
Aided by sufficient computing power,
analysts can now plow through nearly
any amount and diversity of information in
search of probabilities and, by logical
extension, predictions.
While Ariely is right to point a finger at the
excitement that goes with this modern-day
treasure hunt, big data is bringing sweeping
changes to all aspects of life. This edition of
PROJECT M sets out to trace and analyze the
potential as well as the particular challenges
this will likely bring to the financial industry.
Yours sincerely,
Brigitte Miksa, March 2014
Allianz • 3
Contents
Contents
MICRO
FOCUS
(I s s ue s in d e pt h)
( Local kn owledge)
Hidden insights
06 –11
Hidden insights
Big data and digitalization turn both
business and private life upside down.
12 –14
Conference call: Drilling for insights
DJ Patil and Sean Gourley debate the
impact of big data with Ralf Schneider.
15–17
Crunching sense out of big data
Asking the right questions is critical in the
search for hidden value in vast data sets.
18
If … then
Privacy and security expert Fred H. Cate on
developing a rational approach to big data.
19–21
Exploring the future
Jan-Oliver Schwarz on the role of scenario
planning in the financial services sector.
22–23
Back to the future of insurance
Berlin-based friendsurance.de takes aim
at disrupting the insurance market.
24 –27
Reshaping the industry
New technologies, big data and digital
change are disrupting an entire industry.
44–45
28–30
What’s in it for the customer?
Christof Mascher on how technology can
be used to build customer trust.
31–33
Minority warning
Just because we can doesn’t
mean we should, says
Viktor Mayer-Schönberger.
34–35
Automating advice
Stacy Schaus on balancing
automated advice with sound
investment strategies.
36 –37
Fast-forward
The Allianz Digital Accelerator
works to keep ahead of the
digital curve.
38– 40
Watching the world develop
a nervous system
Photographer Rick Smolan on the profound
impact of big data in everyday life.
41–43
Strength in numbers
Carolyn McGregor’s Artemis
project uses human data output to
detect diseases and save lives.
Blurred picture
Children across the globe often work more than they study. Still, the case against child
labor isn’t as straightforward as some may think, says Eric V. Edmonds.
46 – 47
Auto-enrollment shakes up UK pensions
The NEST auto-enrollment scheme targets a looming financial crisis in an
aging population by getting more people to save for their pensions.
48–49
Can elderly well-being be measured – and maintained?
Research can assist policy-makers across the world in developing responses
to mass aging. Approaches, however, vary greatly.
MACRO
( Global opportu n i ti es)
50 – 52
Wired on economics
The hit TV show The Wire tells us more about economics than most dry
analyses, argues economist Peter Antonioni.
53 From the labs
The price of the average data breach is going up while the price for storing data is going down.
Digitalization is changing all facets of business as we know it.
54 – 55
China’s currency steps onto the world stage
The renminbi plays a central role in China’s rise to economic power.
Foreign investors, however, are still not entirely convinced.
56–58
Inequality for all
The US recovery is gathering pace, but too few people are feeling the benefits, argues
political economist, filmmaker and commentator Robert Reich.
59–61
Population aging creates capital repayment risks for government bonds
To avoid the growing risk of bond-repayment default, governments must find
new, sustainable models.
thought leaders in this issue
meta
( Th e ou tsi der’s vi ew)
62 DJ Patil
Data-oriented company
culture is essential.
Page 12
Viktor Mayer-Schönberger
Human reliance on big
data remains a challenge.
Page 31
Carolyn McGregor
Using human data to generate
insights that can save lives.
Page 41
Robert Reich
Why growing inequality is a
threat to financial recovery.
Page 56
The old man and the Cs
At 102, Creole singer and trumpeter Lionel Ferbos is a local legend and the oldest
actively working musician in the jazz capital of the world, New Orleans.
63
Masthead
4
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Allianz
Allianz • 5
Focus
Is sues in depth
Hidden
insights
The explosion in information-gathering
is leading to unprecedented ways of
collecting and combining vast new sets
of data – a resource with huge potential.
What impact will this have on industry,
medicine, social and political policy – as
well as the private individual?
W
ith rain in the air and time to kill, you head into
a department store to do a little shopping. As
you enter, security cameras record your
arrival, while a shopper-tracking camera later records
exactly how much time you spend looking at shoes. After
deciding on a pair, you head to the till and join the queue.
Waiting to pay, you pull out your smartphone, which
constantly feeds your movements and location via GPS
back to the cell phone provider. Feeling proud of your
purchase, you post a picture on Facebook, which
automatically logs your time and location. Your credit card
transaction then registers your payment with the
card supplier, while the loyalty card allows the store to
track your spending habits. As you leave, you call a
friend – another action duly noted by your phone carrier.
In a matter of minutes, your mundane everyday actions
have left a trail of data that reveals more about who you are
6
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Allianz
and what you do – and what you’re likely to do – than you
can possibly imagine. Around the world, millions of others
are doing the same – constantly adding to an ever-growing
universe of raw data. Whether we like it or not, we’re all cogs
in this new universe. That may be an uncomfortable
prospect, but it’s one we quickly need to come to terms
with, as opting out is nearly impossible.
» T he insights that data can reveal are
changing the nature of business, markets
and the societies in which we live.
«
The growth of this digital universe is exploding: the
pervasive use of digital devices and social media is expected
to increase the rate of data production to be 50 times greater
in 2020 than in 2010, according to the information
technology firm IDC. Yet, currently only 0.5% of the world’s
data is being used for analysis, the IDC says, despite a
quarter of it – rising to a third in 2020 – containing
potentially useful information. This untapped value could
be found in anything, such as “patterns in social media
usage, correlations in scientific data from discrete studies,
medical information intersected with sociological data or
faces in security footage,” the IDC wrote in The Digital
Universe in 2020.
Is the quantification of our lives something to fear or
embrace? Already making its impact known, the ‘big data’
universe has the potential to alter almost every aspect of
our lives. Companies and organizations are sorting
through masses of information to extract unexpected
correlations and surprising connections. By knowing more
about us, they can cleverly offer innovations and more
tailored services, from book recommendations and meal
vouchers to loans and insurance policies.
Legitimate privacy concerns
The insights that this data can reveal are changing the
nature of business, markets and the societies in which we
live. Take health: big data can reveal previously hidden
patterns relating to the causes of disease and the effects of
different treatments in order to enable better, more costeffective healthcare. However, there are pitfalls. Edward
Snowden’s revelations on the extent of government
surveillance of the digital activity of hundreds of millions
of people raise concerns over data privacy and security that
are legitimate. Viktor Mayer-Schönberger, co-author of
the book BIG DATA, cautions against over-relying on data
when predicting future events (see pages 31–33). Big data
provides correlations but does not comprehend the
Allianz • 7
Focus
Video
Bonus content in
the PROJECT M app
Focus
We leave a distinct data
exhaust: digital activity
is spurring immense
growth in data
generation, allowing
us to track and analyze
nearly all aspects
of contemporary life.
concept of cause and effect. Data-driven observations may
have the power to change the world, but human
interpretation will remain an irreplaceable factor in our
increasingly digital universe.
Unlocking the value contained in data
As data-driven industries, the potential for change in
the finance and insurance sectors is enormous. Longestablished business models based on face-to-face
interactions are being revolutionized by social media and
digital devices, while the ability to access and interpret a
wealth of new information about existing and potential
clients is opening opportunities for competitors. Cloud
technology has made it possible for firms to store vast
amounts of information. In the past, most of this was
rigidly structured – sheets of numbers, for example.
Now, information is more chaotic: photographs, films,
text, speech or social media streams could all contain
valuable insights on anything from market movements to
demographic trends.
As Volker Stümpflen, CEO of data analytics firm Clueda,
explains, the key to unlocking the value in the data lies in
asking the right questions (see pages 15–17). By using a
complex series of algorithms and visualization tools,
companies such as Clueda are quickly able to analyze huge
amounts of information on a scale far beyond what the
human brain could achieve.
Data leads to tailor-made solutions
Banks and credit card associations are using algorithms to
examine millions of transactions every day to look for
unusual patterns indicating fraud, but they can also
predict things like the probability of divorce as much as
two years in advance – with startling accuracy. By
improving their ability to anticipate changing market
conditions and customer preferences, financial
organizations can also deliver new customer-centric
products and services. The age of relying on focus groups or
averages to determine decisions is disappearing. In
Singapore, when select Citigroup customers swipe their
credit card, the company notes the time and location, and
combines it with data on a customer’s previous spending
habits. Based on this, it can almost instantly send a
personalized discount for a suitable nearby shop or
restaurant via its mobile banking app, potentially gaining a
cut on a further transaction. The system is even able to
learn and improve offers based on performance. And
8
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Allianz
Allianz • 9
Focus
Find out the
ways you may be
a leaving a
data trail at
projectm-online.com
for every Citigroup,
there are countless startups eager to take advantage of
the potential of big data.
The changing face of social
media
With the phenomenal increase in data
collected and the ingenuity of its usage,
companies that already have access to the
largest quantities of information could move
into new spheres of activity, providing further
competition to established players. While
Facebook, Google and Amazon have yet to show signs
of entering the world of finance and insurance, others
have already made their move. The UK’s largest
supermarket chain, Tesco, launched its own banking
service five years ago, offering insurance, credit cards and
loans, with plans to introduce current accounts in 2014.
Combined with loyalty card spending data, the store has a
considerable picture of many of its customer’s lives, giving
it the chance to assess accurately creditworthiness and
offer targeted cross-selling.
In using personal data to sell products, though, firms
must exercise caution not to alarm customers or even risk
legal action. While some may balk at allowing a single
company such a detailed insight into their daily lives, the
number of customer accounts – 6.8 million, and rising –
suggests Tesco’s banking model could be here to stay. With
few brick-and-mortar branches and an emphasis on online
service, it is just one example of how the digital world is
transforming our relationship with providers.
Integral in this is the growth of social media – a doubleedged sword for businesses. While reaching new and
existing customers has never been easier, different
customers require different channels of communication
and a prompt response. They are also able to assess
information and spread opinions quickly on products,
prices and services.
The increase in virtual communication, however,
has strengthened online communities, allowing some
companies to provide a fresh take on a concept that dates
back to the beginning of the insurance industry. Based in
Berlin, friendsurance, for instance, allows users to share
risks and costs within their own communities, no matter
where people are geographically (see pages 22–23).
10
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Allianz
Health benefits and saving lives
By harnessing the power of the digital universe, firms can
create better, more personalized consumer products, save
customers time and money, and drive profit margins. But
by discovering more about how humans function, data can
also help improve our health and save lives.
Our bodies give off thousands of different data signals
every second, most of which go unnoticed and unrecorded.
But within this data lies potentially crucial information
about our physical health. Technology has recently
enabled people to monitor and analyze a small selection of
data related to their own everyday activities. These
wearable devices, in the form of small bracelets, give an
insight into what happens when we exercise, eat and sleep.
Regular users form part of a growing ‘quantified self’
movement, many of whom upload data and exchange tips
and advice in online forums.
A more powerful impact can be seen in the work of
Dr. Carolyn McGregor (see pages 41–43). In collaboration
with IBM, McGregor and her team are developing Artemis,
a platform that captures and processes more than 1,000
data points a second for prematurely born babies. By
identifying patterns in the data, McGregor hopes the
system will allow doctors to detect slight changes in their
vulnerable patients that may signal the onset of a
potentially deadly infection.
The more we quantify our body’s individual make-up,
the more personalized the service we can receive. This
ultimately leads to more effective preventative care and
treatment. As Dr. Craig Feied, professor of emergency
medicine at Georgetown University, points out, there is a lot
of information about patients that doctors are simply
unaware of. “If this were a game of Jeopardy, the category
‘Things Your Doctor Doesn’t Know’ would have so many
entries that it’s scary to think about.” By providing doctors
with more information, we should be able to live longer,
higher-quality lives.
As we begin to get to grips with the vast potential of the
digital universe, we see how data is creating knowledge to
help predict the future, rather than just understand the
past. But we must remember that it is a tool and not a crystal
ball. Data can help us to understand, but it cannot provide
all the answers – and human interpretation remains vital.
before big data and after
The one thing we can be sure of is that the amount of
data will continue to grow. While it can offer tailored
products, better lifestyles and improved healthcare, its
use must be regulated to protect citizens. The
responsibility for this lies not just with lawmakers, but
also with the private sector as creators and keepers of a
large proportion of this data.
The Internet has redefined how the world
communicates, but big data is changing the way we
understand the world. Rick Smolan, photographer and
publisher of the book The Human Face of Big Data (see
pages 38–40), compares it to the world developing a
nervous system. He believes we are standing at a major
period of demarcation in our history – “before big data
and after.” Allianz • 11
Focus
Focus
Drilling for insights
Big data is without doubt a promising resource, but the guidelines for extracting
and ref ining it still have to be written. Handled with care, data securit y and data
privacy will become a competitive advantage for companies.
» PALO ALTO CALIFORNIA
SAN FRANCISCO CALIFORNIA
MUNICH Germany
DJ Patil
Data Scientist, Greylock Partners
Known for coining the term “data
scientist” together with Jeff
Hammerbacher, founder of data
analytics company Cloudera, DJ
has worked at LinkedIn
Corporation, Skype, PayPal and
eBay. As a University of Maryland
faculty member, he focused on
nonlinear dynamics and chaos
theory. DJ worked with the US
Department of Defense to prevent
the proliferation of bioweapons. In
2011, Forbes ranked him and Jeff
Hammerbacher as the #2 data
scientists, second only to Google’s
co-founder Larry Page.
Sean Gourley
Chief Technology Officer, Quid
With a PhD in physics from Oxford
University, Sean has worked in fields
as diverse as nanotechnology and
the mathematics of war. He has
advised the Iraqi government,
briefed the Pentagon and addressed
the United Nations. In his spare
time, he studies string theory
and occasionally returns to the
simpler world of track and field.
Ralf Schneider
Chief Information Officer,
Allianz SE
A mathematician with a PhD in
information technology, Ralf was
named Allianz Chief Information
Officer in 2010. With prior
experience at a midsized consulting
firm and as a sales manager for
Allianz, Ralf now focuses on
providing a standardized IT
platform to a global company.
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Allianz
Schneider: Gentlemen, big data has become
one of the world’s most important resources.
In a way, it resembles oil: it needs to be
extracted, refined and used responsibly to
make full use of its value. What is your take on
the current discussion?
Patil: Behavioral economist Dan Ariely once
compared big data to teenage sex: everyone
talks about it, nobody really knows how to do
it, everyone thinks everyone else is doing it, so
everyone claims they are doing it. “Do you have
a big data strategy?” is now the hip question
to ask at cocktail parties, replacing “Do you
have a social media strategy?” However, its
opportunities, as well as its risks, have to be
taken seriously.
Gourley: There is a lot of hot air in the
discussion, but you can’t ignore it. The analysis
of information created by our everyday use of
computers very likely alters the way we live.
One economic consequence is that granular
information about individual preferences can
improve pricing structures and increase cost
efficiency across all sectors by 5% to 10%.
Schneider: The sheer size of data makes the
topic impossible to ignore, particularly for
insurers. We expect the amount of data to
increase by factor 40 over the next 10 years. At
the same time, computing power continues to
grow exponentially, allowing us to refine the
data in a sensible and responsible manner.
But let me briefly define big data for the
purpose of this conversation as proprietary
information generated and owned by an
agent – for example, a company. In a second
step, the information is analyzed, possibly in
conjunction with additional data gathered
from outside sources.
Patil: That works for me. And you’re right,
Sean, there’s more than just talk. Agriculture
company Monsanto, for instance, just paid
approximately a billion dollars to acquire
Climate Corporation, a company that analyzes
data to provide crop insurance to farmers. On
the other hand, there are clear risks to big data,
and we’re struggling to define good practice.
What is best practice at your company, Ralf?
Schneider: At Allianz, we do less than we
could. We now have the ability to analyze
multitudes of unstructured, unrelated texts
and figures from various sources with a
varying degree of accuracy. Its quantity allows
us to accept a degree of imprecision, and the
advantage of big data is that we are now in a
position to extract meaning from such messy
information. We also have more accurate
predictors for the risks we insure. The danger
is to rely too much on correlations which say
nothing about actual causality.
Gourley: The predictors may become as
detailed as how a person’s education and
driving style affect the premium of his car
insurance.
Schneider: True, but the concept of insurance
can only function if risk is distributed across
various members of a group. For insurers,
information analysis has always been at the
core of understanding the risks they accept. So
while this is not new, the basis for finding new
patterns has expanded. However, neither the
patterns nor the data are personalized. What
we can do is show how a group with similar
age, gender and education behaves – to the
benefit of our clients. Big data enhances our
ability to identify and respond to individual
customer’s needs.
Gourley: Can you give us an example?
Schneider: Sure. Take liability insurance fraud.
These cases often share common patterns:
they take place in the home of the insured,
with visitors; most objects reported as broken
are alike; and the relationship between
the insured and the culprit is similar, too.
If a claim seems suspicious, we look for
aberrations in the patterns to confirm our
initial suspicion. Apart from that, do you
T he sheer
size of data
makes the
topic impossible
to ignore,
particularly
for insurers.
Ralf Schneider
«
Allianz • 13
Focus
» S imilar to
gentlemen have any advice on how insurers
should handle big data?
Patil: I recommend that larger corporations in
general do a data review just like they do a risk
review before they roll out a major project.
Schneider: What exactly do you mean?
Patil: Just because we can with data, doesn’t
mean we should. Every company should
have an internal process of data checks and
balances in place that allows them to make
use of big data in a responsible manner.
Similar to physicians, big data users need to
make efforts to ensure they are acting in an
ethical manner.
Schneider: Absolutely. Increasing opportunities
also bring growing responsibilities. The
question for us is not “What is the legal
maximum?” but “Do we want to do everything
that is legal?” My answer is no, and I
am convinced that data privacy and
data security will eventually become a
competitive advantage. In the meantime,
we’re focusing on building an appropriate
IT infrastructure throughout our global
organization to safeguard our clients’ data.
Gourley: I think it comes down to money and
transparency. If a company makes money
thanks to their customers’ data, they ought
to be up front about it and willing to share
some of that profit with those who made it
possible in the first place: the people
generating the data. In the long run, this will
increase clients’ trust, counter Big Brotherlike concerns and enable us all to make the
most of big data.
Patil: A data-oriented company culture is
essential. The best data-driven companies
start with what we call “silenced sustained
data reading” where they take 15 minutes just
to look at the data. Once that is complete, then
they can dig into the questions. It’s about being
intellectually honest as a team. Data is a team
sport, and it will play out its benefits when it’s
14
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democratized – that is, when accessed by
various entities within a company.
Schneider: So far, we spoke about technology
and its potential. What role will humans play?
Patil: I think this is a false dichotomy. Humans
have one great advantage over technology:
intuition. The best data scientist is one who
brings intuition and information together and
moves effortlessly between both areas.
Schneider: That’s for those of us who are prepared
to work with data. What about the rest?
Patil: Well, it is the data scientist’s job to make
data accessible. From then on, almost everyone
can be educated to deal with data. And we have
already done this successfully with
technology. I can’t think of a single three-yearold who is incapable of using an iPad.
Gourley: Owning the information and the
computing power is not enough. That’s like
having a Ferrari in the garage but no idea how
to drive it. To get the most out of large
quantities of data, human expertise – with the
support of algorithms – needs to structure it in
a meaningful way. The interpretation of data
and its patterns will remain a human task.
Schneider: How do you see the future of big
data evolving, Sean?
Gourley: I see three major trends. First, I expect
people to demand more value back if their data
is used to generate profits. Second, we will see
more visualization, so interfacing with big
data will become easier. Lastly, there will be a
move from prediction to persuasion engines.
While predictions like that of Nate Silver’s 2012
US election outcome are impressive, they
forecast the future based on past actions. More
interestingly, we could arrive at a choice of
future scenarios independent of the past. I
tend to think of this as persuasion engines,
rather than prediction engines.
Schneider: That is very futuristic indeed.
Thank you very much for your time and
insights, Gentlemen. physicians,
big data users
need to make
sure they
are acting in
an ethical
manner.
DJ patil
«
Picture Galler y
Bonus content in
the PROJECT M app
Focus
Crunching sense
out of Big Data
We may have more information than ever before, but it’s
meaningless without structure. Companies such as Quid and Clueda
help us ask the right questions to extract insights from chaos.
A
the big picture
Technology companies
are trying to bring
clarity to huge amounts
of data available in
different formats.
s technology advances at breakneck
speed, building up an avalanche of
data, how does one make sense of the
vast amounts of information crowding into
everyday life?
A number of companies and start-ups
have taken on the ambitious task of developing
digital riggings and computational knowhow powerful enough to offer much-needed
clarity. They aim to build algorithms and
visualization tools that can crunch enormous
amounts of information at incredible speed.
This way, they can assist clients in asking
the right questions of their data.
data-driven insights
One of the companies operating at the
crest of the big data revolution is Quid, a
San Francisco analytics firm founded by
entrepreneur and Oxford-educated physicist
Sean Gourley four years ago.
Already a fixture in a fast-growing industry,
Quid works with technolog y giants,
government agencies and financial-service
providers to deliver astute data-driven insights
that can lead to crucial strategic and analytic
decisions. “We have built an intelligence
platform that people can plug into in
order to understand the complexities of
the world around them,” Gourley explains.
“It’s an ambitious project.”
scaling information mountains
The input for Quid’s analytic products
varies from scientific journals and files
through financial transactions to court
documents – mountains of information that
would other wise be impossible for the
human mind to handle. The result arrives
on the client’s desk in the form of
advanced, interactive, three-dimensional
visualizations and graph structures that
represent an intuitive, deeper grasp of the
problem at hand.
“What we offer is a high-dimensional
mapping structure that provides an
understanding of an industry, a scientific
field or even a political space,” Gourley
explains. “It’s structuring of information
through algorithms and computational
cognitive power – a replication of what an
expert does when establishing relations
Allianz • 15
Focus
and connections in information, but on a
larger and much more complex scale.”
Tapping into huge amounts of data in a
focused way presents enormous advantages
to companies and institutions. An investor
can, for instance, gain invaluable insights
that help him stay ahead of the curve and,
ultimately, the competition. Gourley is
reluctant to talk about hard numbers, instead
emphasizing “the beauty” of drawing
meaning from unstructured information.
“I’m very excited these days. We get to work
with everyone from hedge funds to nonprofits, and they are all now able to plug in and
better understand the complexities,
connections and contexts of the world around
them through data. It’s incredible to see
this happening.”
removing junk and noise
Clueda, an innovative software developer
and manufacturer in Munich, offers a similar
service, but with a focus on the healthcare
and financial-service sectors, while also
planning a jump into social media analytics
in the near future.
Operating under the slogan “Beyond Big
Data,” CEO and founder Volker Stümpflen
describes his service as “associate knowledge
processing.” But his mission remains the
same as Gourley’s: extracting meaning from
the chaos of big data. The Clueda method is
based on models from cognitive science and
brain research and has been refined for the
past 10 years.
Today, the company can produce accurate
reports and visualizations on a host of topics,
fields and relations, based on the targeted
analysis of mind-boggling amounts of input.
“There is a lot of junk and noise in big
data,” argues Stümpflen. “The idea used to be
that you just needed to collect a lot of data
and new knowledge would come from it. Now
we know that you have to remove this junk
and noise for anything to be meaningful, and
to find answers.”
semantic analysis
Clueda’s input comes from all kinds of
unstructured information, Stümpflen further
explains. “Our algorithms are self-learning
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Focus
and scale easily,” he says, “so we expect to
include photographs, films, recorded speech
and social media streams in the future
through semantic analysis and mapping of
relations in social networks.”
Their output can be delivered extremely
fast to benefit, for example, stock traders who
need information speedily, or healthcare
companies that seek detailed knowledge on
product impact in specific markets under
specific conditions. The parameters are
essentially endless. But by structuring data
analysis around key bits of information and
their reach, the method “effectively
transforms clusters of untidy data into
detailed tangible outcomes that can help
decision-making,” Stümpflen says.
In this data-driven field, constantly
widened by advancing technologies and
self-learning algorithms, the role of the
human being becomes another burning
question. Computerized big data analysis
may help derive meaning from oceans of
shapeless knowledge, but what part does
good, old-fashioned human cognitive skill
play in this puzzle?
human involvement
“We still need humans to interpret the
outcomes of analysis,” says Gourley. “This,
however, is not a skill that everyone has. I
think that we will see a schism developing in
terms of skills in the near future. There will be
people who are capable of working with big
data, and people who aren’t.”
Stümpf len, whose algorithms are
deliberately built to imitate the human
mind, also sees human involvement as
vital in asking the right questions and
understanding the answers that arise.
“Humans are exceedingly good at
connecting the dots,” Stümpflen says. “There
are lots of examples where cause and relation
are seemingly clear. But by asking the right
questions, we can eliminate this idea of
automatic correlations and look beyond them
to make the right connections with the
analyses we do. The answers are only useful
because of the contexts in which they are put
to work. And in understanding these patterns,
humans continue to play the leading role.” » w e will still
need humans
to interpret the
outcome of
analysis. this,
however, is not
a skill that
everyone has.
volker
stümpflen
«
Making sense
of complex
data still relies
on human
query and
analysis.
Focus
Focus
Fred H. Cate
Professor of Law
at Indiana University
and Director of the
Center for Applied
Cybersecurity Research
Data privacy and security expert
Fred H. Cate calls for a rational
approach to the excess of data we
generate in the digital world.
IF
T h en
IF you prefer to conduct this telephone interview
over the hotel’s landline, I can call back.
THEN my decision is based on the connection’s quality,
not its data privacy. I do use a mobile phone, including
Google Maps’ location service, which leaves a large
digital footprint. But I decided not to use Facebook.
IF governments and private-sector firms collect more
and more data on individual behavior, what will this
mean for individuals’ rights?
THEN we have to put appropriate oversight
mechanisms in place. The collection needs to be
monitored and an appeals process established to
challenge decisions based on this data.
IF that leaves a feeling of unease
with most people …
THEN I say big data is not necessarily a bad thing. We
are constantly judged on often incomplete information.
Depending on my zip code, my car insurance may be
more expensive than yours for reasons that have more
to do with my neighbor’s driving abilities than my own.
IF big data provides a more comprehensive and accurate
understanding, what are its risks?
THEN we have to be wary not to become overly
enthusiastic. Governments and companies should
continually question their data’s accuracy. This – as
well as the decision-making process based on big data –
needs to be subject to external checks and balances.
IF you consider the debate over Edward Snowden
and the National Security Agency, what are the
implications?
THEN the NSA is exploiting ambiguities in the current
legislation. While I do not condone stealing confidential
information, Snowden deserves credit for initiating the
necessary public debate.
IF you look ahead, what will be one of the challenges
concerning privacy?
THEN we can do better. We have come to accept
outdated legislation, but there is no need to rely on
20-year-old data privacy laws.
To listen to a recording of the interview with Fred H. Cate, please go to PROJECT M online:
projectm-online.com/new-perspectives/if-then-fred-cate
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Focus
EXPLORING
THE FUTURE
The future is largely unknown, but that doesn’t mean you can’t try
to work out what might happen next. This is where scenario
planning comes in. Scenario planning is based on the
premise that you can work out likely variations of the future
by analyzing the main drivers shaping the present.
By Jan Oliver Schwarz, Allianz Strategist
I
f you could travel forward in time to the next
decade, what would you see? A world radically different
or one scarcely changed from the present? Nobody
knows, but one thing seems to be sure: we will live in an
increasingly digital world, where the Internet and
smartphone will reign supreme. Tomorrow’s youth won’t
be able to contemplate a world before the iPhone or
research information without Wikipedia’s or Google’s help.
Just what form this digitally dominated world will
take depends largely on two factors. First, how online
communities develop will have a huge impact. These might
remain communities where people simply exchange
private messages and pictures. Alternatively, these
communities might play an influential role in the business
world, with people turning to them first for financial
advice, as they do currently for travel tips.
Second, game-changing technology will likely alter the
way we communicate and use the Internet. For instance,
semantic technology, namely the intelligent linking of data
from a huge number of different databases, will be able to
transform the Internet into an intelligent vehicle and
answer a search query in a direct and relevant way by
relating your latest search query to previous searches.
exploring future scenarios
Using the scenario-planning approach, we came up with
four scenarios to depict possible variations of a digitalized
future. The first scenario, ‘Brave World on the Move,’
is conservative and envisions a world barely different
from the present day, but with more prevalent Internet
and mobile-phone usage. In this imagined world, people
would still seek out an insurance agent to discuss
queries or a financial advisor to talk about the state
of their finances.
» [online] communities might play an
influential role in the business world, with
people turning to them first for financial
advice, as they do currently for tr avel tips.
«
The second, dubbed ‘Trust in Virtual Communities,’
anticipates virtual communities playing a far more
dominant role. In this scenario, people would turn
to the Internet more often to seek advice and
exchange ideas, also concerning business and financial
matters. Consumers would become active content
providers, distributing content valued by their
peers as sound advice. Digitalization would further
evolve and play a vital role in everybody’s day-to-day life.
The most progressive scenario, called ‘Good Morning,
Intelligence,’ takes this a step further. It visualizes
a virtual world, which responds smartly to the needs
Allianz • 19
Focus
of active consumers. In this future scenario, gamechanging technological advances, such as semantic
technology, would lead to new ways of doing business and
of compiling knowledge. Autonomous and self-driven
customers would easily find the information they seek
online, preferring to rely on the opinion circulated within
a social web-based community rather than that of a
qualified expert.
To stay on top of
digital advances,
financial
institutions will
have to piece
together different
approaches to
clients’ needs.
CHALLENGE FOR FINANCIAL SERVICES
This shift towards a virtual world would present a tough
scenario for the financial services industry, which still
depends on giving advice to people. It would be confronted
with customers who could access the advanced
information they need from the Internet and shun face-toface interaction with a financial advisor. Furthermore,
clients would order customized products based on their
own ideas and needs. And an increasing number of people
would work from home.
The scenario ‘High Tech and Real Friends,’ meanwhile,
visualizes a more moderate world, one which has become
more virtual, but where human contact and exchanging
ideas with another person is still valued and people still
place their trust in identifiable experts and institutions.
Here, semantic technology would support humans in an
intelligent way. This world incorporates the so-called ROPO
effect – ‘research online, purchase offline’ – in which people
research the products or services they want to buy online
before going in person to a branch or shop to close a
contract or buy goods.
Financial institutions in this world would need
to be easily accessible online, offering transparent
information, products and prices. And insurance
companies would need to be present on ‘aggregator
websites,’ where people could easily compare policies.
Contact with customers would remain important.
This currently popular approach is widely predicted
to become more dominant: it has already been adopted
by Spanish banks such as BBVA, which, as well as
building up its digital channel, has radically
redesigned its branches to attract back customers and
not lose that vital personal contact. One of BBVA’s
touchscreen ATMs has even made it into the Museum
of Modern Art in New York.
GIANTS BATTLE WITH INSURERS
If financial service providers want to gear up for these
future challenges, insurance and financial-service
companies need to be prepared. They will need to face
competition, which may present itself in new guises, such
as that presented by Amazon and Google. Amazon has
already started making inroads into the insurance
industry, offering extended warranties in some countries
when you purchase a product. Meanwhile, Google, the
world’s largest search engine,has launched its own carinsurance comparison site.
Fortunately, these Internet giants are unlikely to
develop a huge appetite for taking on the underlying
financial risks, although they may end up capturing the
points of direct interaction with the client – arguably the
sweet spot in the financial-service value chain.
In order to compete effectively in a digitalized world,
companies will need to be present where their customers
are. Insurers and financial service providers will need to
offer customers different access routes to get in touch with
them. Someone young will want to access up-front
information easily online, while some elderly clients will
prefer to go into an agency or branch and talk to an
individual.
» i n order to compete effectively in a
digitalized world, companies will need to
be present where their customers are.
«
Even future younger generations will probably still value
human interaction when it comes to taking financial
investment or protection decisions. But tomorrow’s
customers will undoubtedly have a vast amount of
intelligence, data and knowledge at their disposal, meaning
that companies would need to provide even more
expert and tailored knowledge to compete.
If online communities continue to grow in importance,
we might see the return of peer-to-peer or mutual
insurance, where people insure each other and set risk
selection within their communities. This would hark
back to the very beginning of the insurance industry. After
all, history often repeats itself. Allianz • 21
Focus
Focus
Back to the
future of
insurance
as big data, could lead to better cost
controls and more efficient delivery
of services, he believes.
Progressive Group of Insurance
Companies is one of the forerunners
when it comes to use of data. In 1999, the
US insurer offered Texan customers a
trial program called Autograph, which tracked driving
styles. Today, the firm monitors driving days and times,
higher versus lower speeds and braking styles in Snapshot,
a voluntary program rolled out nationally in the US in 2008
and 2009. Premiums are discounted for careful drivers,
as they are less likely to be involved in crashes, according
to Progressive. While other information is monitored,
the actual location of the car is deliberately ignored.
The company initially placed a surcharge of 9% on what
it considered bad driving; this has been abandoned. Seven
out of 10 participating customers now receive a discount –
on average of about $150 – with Snapshot.
There is demand for usage-based insurance (UBI).
Nearly 90% of respondents were interested in buying UBI
products if the premium did not increase, a recent survey
by consultancy Towers Watson found (Usage-Based
Insurance Consumer Sur vey. Understanding What
Customers Want, 2013). Interest was particularly high
among younger drivers, whose car insurance premiums
are among the highest.
A network of
friends is the key
to a new, highly
innovative
and mutually
beneficial type
of insurance –
with less risk.
With the help of both real and
virtual friends, the cost of
insurance could be brought down
while keeping clients’ risk exposure
low. But many insurers are still
shying away from social media.
I
t had to be Berlin for Tim Kunde and friends. “We aim
to be a game changer for the insurance industry. For
that, we chose to be close to Berlin’s buzzing Internet
community,” Kunde tells PROJECT M in his fifth-floor,
shared office. With exposed brick walls and the back
entrance half blocked by construction work, the building
oozes Berlin ambience.
With the help of his two partners, Kunde, formerly an
employee of Boston Consulting Group, founded
friendsurance.de, an insurance brokerage cum social
media network, where a circle of both real and virtual
‘friends’ share the excess of damages to a person’s car
or mobile phone before traditional insurance pays the
rest of the claim.
Business: casual
Attired in blue jeans and a pullover and sporting a patchy
beard, Kunde needs to walk a fine line with his company
to attract tech-lovers as clients and traditional insurers
as partners. “This sector has not seen much innovation
over the last decades. Yet we are realistic enough to know
that clients look for solidity and reliability when it comes
to insurance.”
Selling the household, personal-liability and legalexpenses insurance of partnering companies such as AXA,
ARAG and others on commission*, friendsurance promises
users – typically known as ‘clients’ by the industry – low
contributions in exchange for high deductibles. “We use
the mechanics of the deductible to lower cost while its
risk is shared across a community of friends,” says Kunde.
Growing the network of registered friends automatically
changes the tariff to include a higher deductible. As the risk
of claims is reduced on the insurer’s side, premiums are
lowered. The savings are retained by friendsurance to cover
damage costs under the deductible with a contribution of
up to €30 ($41) per friend. If the group remains accidentfree throughout the year, part of the pot is paid out.
While the same product can be bought directly from
the insurer, thereby cutting out friendsurance as the
middleman, clients would have to shoulder the higher
deductible without the help of friends. “The vast majority of
customers in the German-speaking countries are too riskaverse to do that and can benefit from our approach,”
Kunde says. Founded in 2010, the 40-employee start-up has
since established itself as a distributor of off-the-rack
insurance products to thousands of users with an average
age of 30 to 35. “But,” adds Kunde, “innovation does not yet
happen on the product side.”
INSURANCE AGENT IN THE BACK SEAT
Next to health care and energy, insurance is the sector
most likely to profit from spreading digitalization and
rising amounts of data. It is “about to explode” with uses
for big data, said Google’s executive chairman Eric E.
Schmidt late last year. The mining and processing
of petabytes (1015 bytes) of information, often referred to
PREVENTING FRAUD BEFORE IT HAPPENS
Despite early adopters like Progressive, a discrepancy still
exists in the industry, according to Craig Beattie, senior
analyst with Celent, a consultant agency focusing on
information technology in the financial services sector.
“Every insurer we speak to says that, if the right flags are
raised, social media information will be reviewed to settle
the claim. On the other hand, firms lock down websites
like Facebook on company computers, indicating that
social media is not part of the insurance business,” says
the author of the report Using Social Data in Claims and
Underwriting (2011).
Social elements can even help prevent fraud from
taking place, Kunde adds. Knowing that it will harm the
circle of friends, friendsurance users are unlikely to
exaggerate claims, he says. New users also tend to seek
out friends they believe to be more prudent. For the group,
such behavior will lower premiums, as well as pay-outs
and administrative costs for the insurer.
“Social media elements can have a dual effect on
insurance,” Kunde says. “By reverting back to the original
concept of mutual support, costs can be reduced for all
parties involved.” * Allianz, the publisher of PROJEC T M, is in dialogue with f riendsurance.de, but not a par tner.
22
•
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Allianz • 23
Focus
Focus
Reshaping the
industry
Big data and new technologies pose
great challenges to the financial services sector,
but could also help redefine an entire industry.
E
arlier this year, the Wall Street Journal’s blog aimed
at chief information officers published a selfcongratulatory post about the use of big data
by financial services firms. The post’s 533 words essentially
repeated the same point over and over, producing such
gems as this quote: “Financial services is a real leader in
big data and analytics,’ said Mr. Bean.”
Acres of coverage
Not once, however, did the article mention what it means
by ‘big data,’ how financial services firms are using it,
what they’re doing with it, or whether the money being
spent on it was producing any results. This has been
the enduring problem with big data. Despite acres of
coverage and a Google Trends line that has exploded to
the highest measurement in just two years, the term
remains ill-defined.
Google engineer Peter Norvig offers an evocative way of
understanding it in Viktor Mayer-Schönberger and Kenneth
Cukier’s book Big Data (see pages 31-33), using the example
of a cave painting and a photo of a horse. While there is an
obvious difference between the two, each remains a still
image. Yet a number of photos displayed at a rate of 24
frames per second and the resulting motion picture
provide far more information. “By changing the amount,
we change the essence,” Norvig is quoted in the book as
saying. It remains the same thing – a set of pictures – but
the sheer volume conveys information about how the
horse moves, how fast it runs, the direction of travel,
whether or not it has injuries, and much more. Added
information offers a more complete image, if it is structured
and presented in a meaningful way.
Similarly, what big data does in the world of finance is
that it allows us to extract patterns from what was just
information. And within those patterns lie unexploited –
and often unknown – opportunities. Working with new
24
•
Allianz
software like Apache’s open-source Making sense
of chaos:
Hadoop framework project and the
a focused
ecosystem of tools that have grown
approach is
needed to
around it, businesses can use the power
extract value
of distributed computing to interrogate from big data.
vast amounts of data quickly, efficiently
and at little cost.
The potential is enormous. Big data comes from a
variety of sources: a lot of the digital exhaust is left by
individuals as they go about their day-to-day business:
searching the web (leaving records of search history,
location, browser information), taking a photograph (time,
date, exposure, location), making phone calls (numbers
being connected) or using their credit cards. Other data is
created more overtly, for example, on social media where a
single tweet has more than two dozen metadata fields. And
a lot of it already exists in the form of vast troves of unread
documents or in data dumps like backup servers. Over
time, this data, tied together with that of other individuals,
accumulates to offer insights.
FINDING THE RIGHT CORRELATIONs
Such data is not always structured. A recent white paper
from Oracle, a database company, estimates that between
80% and 90% of the data owned by banks is unstructured. In
other words, it exists not in neat rows and columns ready to
be plugged into Excel but as documents or in plain text.
That would require weeks if not months to parse. Hadoop,
along with complementary tools such as Mahout (machine
learning) and Hive (data warehousing), is able to deal with
such data by breaking it up and tackling it in little bits. Visa,
for example, used Hadoop to analyze 73 billion transactions
in 13 minutes. Without Hadoop, it would have taken an
entire month.
Examples abound of how big data can be used in realworld scenarios. David Gentle, Fujitsu’s director of
Allianz • 25
Focus
foresight, offers the example of a mobile operator that
noticed its customers were leaving for other networks.
“Then the company realized that they’re operating a digital
service and everything they do with their customers is
generating information.” Gentle says the company
examined phone records of recent departees and found
that they often spoke to a close friend or family member
just before changing providers.
“That indicated that they had been influenced by a
trusted source and just needed some attention to stay
behind. In response, the company automatically checked
the immediate contacts of those who had recently left
and made special offers to their close friends on their
network, something that helped retain customers.”
Separating the wheat from the chaff
More impressive still is the example offered by Andrew
Sheppard, a financial technology consultant, former
hedge-fund CTO and analyst. According to Sheppard,
big data should simply be understood “as anything that
either doesn’t fit in Excel or that requires hours for
Excel to process.”
He points to Counterparty Valuation Adjustment (CVA),
or the value of the risk of default by a counterparty, as a
way to measure the true value of a portfolio. Under new
regulations, a financial institution with strong risk
management will receive a break on its risk capital –
the amount of money needed to run an operation in a
bank, says Sheppard.
However, it is hard for banks to get a handle on this
because such calculations must take millions of possible
scenarios into account, which may take anything from
several minutes to several hours. That is not ideal for
an industry that relies on speed. But with big data analytics,
it is possible to do it with great efficiency.
What does that mean? Sheppard offers an example:
“Let’s suppose for a bank the cost of capital must be about
10%. If you assume the bank has $20 billion of operating
capital and it gets a 10% break on that, it would need
to have $18 billion. Since the cost of capital is 10% for
a bank, that $2 billion less saves $200 million, which goes
straight to the bottom line.”
Sheppard stresses that this is the result of nothing
more than good data wrangling. “The bank hasn’t acquired
one customer, it hasn’t done one deal and it’s done nothing
different other than get a better handle on risk with
big data. And all of a sudden it’s making $200 million
a year more for doing nothing but using data in an
intelligent way,” he says.
Indeed, this is applicable in myriad ways beyond just
regulatory matters. ZestFinance, a firm that helps lenders
26
•
Allianz
Focus
Once big data
make credit decisions for small, shortis structured,
term loans by using big data, has a
it can yield
default rate more than 30% lower than
invaluable
insights.
the industry average, according to the
book Big Data. It does that by looking
at a vast variety of incomplete data rather
than focusing purely on traditionally accepted data points.
Yet, there is also a pitfall to big data, which is the risk of
seeing patterns where there are none. Fortunately, using
big data for finance is easier than using it, for example, to
define policy. “As a user of big data in finance, the final
question is, ‘Can I make money with this?’ If I can, then it’s
good data – and if I can’t, it’s bad data,” says Sheppard.
But big data is no panacea. “The thing is to look at the
areas where it can generate an advantage,” says Gentle. Take
social media. Volker Stümpflen, CEO of Clueda, a German
data analytics firm (see pages 15-17), says there is plenty of
noise on social media, but there are some gems that can be
market-moving. The crucial task is to separate the wheat
from the chaff. The hubs of social networks – people with a
lot of followers – are not necessarily the most reliable, or
indeed the first with the news. Rather, Clueda’s algorithms
are programmed to identify valid information by looking
at the reliability and authority of the sources picking up
and spreading information. Value might lie at the edges of
the network. But above all, it lies in the use of data analysis
to put chaotic information into useable contexts.
Setting the scene for change
Consumers – the people creating a lot of this data – may not
be thrilled by the idea that their digital trails are being
analyzed in such detail. Yet, the benefits of commercial
adoption of big data far outweigh the risks. Returning to the
example of ZestFinance, for every person denied a loan,
there are plenty more who may have struggled to meet
traditional, less accurate assessment criteria who are
now able to get one. Better data analysis means more
accurate decisions.
Customers might not like a telecom operator seeing
who their friends are, but it could mean that they receive
savings on their bills when the operator tries to retain
them. Safe or infrequent drivers could be in a position to
pay lower car-insurance premiums through the
installation of telematics boxes, which gather data as a car
is driven and show that these drivers are reliable.
The benefits, then, are broad. Finance professionals and
businesses of all stripes benefit from greater insight and
efficiency. Consumers get better service, lower prices and
more personalized attention. And a whole new industry
blooms, building on what already exists. The world is set for
some big changes. Allianz • 27
Focus
Focus
What’s in it for
the customer?
To benefit from the digital revolution, one must understand
both business potential and customer needs, writes Christof
Mascher, COO and Management Board member of Allianz SE.
T
Christof
Ma s c h e r
Christof Mascher has
been a member of the
Management Board
and chief operating
officer at Allianz SE since
September 2009.
28
•
Allianz
he digital revolution goes far beyond
digitalization and networking
communication. Smart and mobile
devices, sensors and cognitive systems
bridge physical and even mobile locations
and interactions. The possibility of being
connected anytime, anywhere and with every
kind of device comes with a new level of
convenience: first, people can quickly adapt
their use of technology, and second, people
can better manage their life, gain time and
save money.
The seamless customer journey
If seeking advice or information, customers
can easily reach out to peers via social
networks – and quickly gain transparency on
products, prices or services on a much broader
scale. In Germany, discussions on car
insurance on the popular MOTORTALK online
platform generate up to 7.5 million views
annually. Analysis shows that 25% of these
inquiries receive a response from peers within
10 minutes of posting and 50% within an hour.
This significantly changes the traditional
relationship between the customer and the
insurer. In order to retain the customers’ trust
in our brand, insurers must be equally present,
agile and responsive.
How fast the communication landscape is
changing is evident in the fact that some 15% of
Internet searches relating to insurance are now
conducted on mobile devices. As an absolute
number, this will grow threefold by 2016 in line
with the general growth of mobile commerce.
This embracing of new communication
technology from smartphones and tablets to
social networks is not just restricted to
‘Generation C’ (the connected generation):
already, 75% of customers aged 55+ rely on
social media for purchase decisions in the US
and UK.
In the digital world, companies no longer
control this relationship; consumers are
increasingly making their power felt.
Connectivity significantly reduces transaction
costs, prov ides a never-before-seen
transparency and improves the quality of
direct communication. Customers consuming
on the go can share their experience – positive
or negative – immediately online and seek
to shape and optimize offers. The conversation
is now a dialogue which puts customer
experience much more into focus and
intensifies the existing relationship between
customers, consumers and insurers.
Customers want to have the choice of when
and how to interact with us through multiple
access points – via phone, net, mobile apps or
in person with our agents. They consider the
exchange of information and communication
as one stream, maintaining the conversation
on different devices or face-to-face from where
they originally left off. It is simply part of their
day-to-day life, and they expect real-time
offers and services delivered seamlessly with
the same level of professionalism and
expertise both online and offline.
Finance and insurance companies have
to realize that digital is not just a channel
characteristic. The actual need for change
is radical: it is a business model evolution
A comprehensive
digital strategy
can help
paint a more
wholesome
picture of
issues like
customer trust.
with simplified and competitive offers
that will open up new areas of business
with existing clients as well as gaining access
to new customers – based on seamless
customer journeys.
To benefit, one must first understand
Taking a 360-degree perspective on our
customers diminishes extensively the
traditional product and channel focus of an
insurer. The question is no longer which
product fits best and is best sold via which
channel. Rather it is our clients’ interactions,
points of contact, mobility, whereabouts in
daily life, their activities, changes in
circumstances and corresponding interests
and needs that now help define how risk
mitigation and our products and services are
designed.
The sharing of information has become
an aspect of virtually every daily habit, of
both our digital and physical lives. This
explains how Amazon can recommend us the
ideal book or the ability of Facebook to know
what we like. In 2010, we were already creating
as much information through digital means
every two days as we did from the dawn of
civilization up until 2003, according to Eric
Schmidt, former CEO of Google. In such a
complex environment, how do companies
know when to approach a particular customer
at a particular time and place? This knowledge
comes from data and, to achieve this, the
ability to obtain, filter, understand and
channel customer-related data becomes a
must. A small amount of the data is actually
provided by the customer. According to Forbes
Insights, the majority of consumers will
willingly share information if they perceive it
to be in their favor in order to obtain individual
and competitive offers. The largest part
of the data comes not directly from people
but from interconnected devices. Data
accessibility and the ability to leverage data
to better serve the customer at every
Allianz • 29
Focus
step of our relationship, while respecting
the customer’s privacy, will become a key
competitive advantage.
‘the most trusted partner’
In a world where technology opens new
possibilities to make people’s lives more
convenient – just think of smart homes,
connected cars or e-health – Allianz wants to
offer improved additional value to its
customers. Consumers are expecting new,
individualized ways of being insured,
customized services and prevention, as well
as a free choice of the means to interact
and communicate with us. To deliver exactly
these types of products and services, we
at Allianz embarked on a comprehensive
digital program a couple of years ago.
In this new digital world, however, we want
to remain ‘the most trusted partner.’ It is
therefore of the utmost importance to Allianz
to keep our customer and business-critical
data secure from prying eyes. We carefully
Emerging
patterns: the
denser the cluster
of pixels, the
higher the level
of social trust
in the surveyed
countries.
30
•
Allianz
balance risk by building highly secure data
center hubs for Allianz’s powerful, global
private cloud infrastructure, including
carefully selected security measures. The fact
that we have been offering cyber-risk
protection to business clients since 2013
underlines the point that Allianz is one of
the few players with the size and skills to
ensure customer data privacy is protected
to the highest security standard.
Protecting our customers’ most valuable
asset – trust – remains a core value at Allianz
– especially in the digital world of the
immediate future. A measure of trust: the PROJECT M COver
PROJECT M uses data to create its
award-winning cover art. For the
cover of the magazine’s 11th issue,
global social-trust-level data was
used to generate the ‘TRUST’ image.
Focus
Minority warning
The challenge of big data is not its quantity or variety, but human
over-reliance on its infallibility.
W
hat sounds like a strange location for lunch
turned out to be a great choice for Mark Eveleth.
Seated in a dark corner of a multistory parking
garage in downtown Santa Cruz, California, the police
sergeant was about to unwrap his sandwiches when two
women strolled by, casually checking car doors in search of
an easy burglary. The lunch break led to two arrests.
Eveleth did not pick the spot by chance. He was guided
by Predictive Policing (PredPol), a software program
devised by University of Santa Clara mathematician George
Mohler and colleagues. Based on historic crime data and
updated on a daily basis, PredPol predicts crime hotspots of
164 yards by 164 yards (150m x 150m), including the garage
Eveleth had lunch in.
The incident recalls Steven Spielberg’s Minority Report
(2002), where people are arrested for crimes they are
predicted to soon commit.
What Spielberg envisioned for Washington, DC, in 2054
is only a few steps away from what PredPol and similar
programs do today in the US and UK, warns Viktor MayerSchönberger, professor of law, Internet governance and
regulation at Oxford University. “Big data’s biggest risk is
that it is misused to explain the causality of facts when
all it can do is indicate correlations,” he explains in an
interview with PROJECT M. “Big data reveals something is
happening; however, it cannot explain why.”
PROPENSITY JUDGEMENT
Listing two other key risks – lack of privacy and
data dictatorship – Mayer-Schönberger’s main
concern is that penalties are applied on
the basis of probabilities. Judgment and
punishment based on big data “negate ideas
of fairness, justice and free will,” he and
co-author Kenneth Cukier write in Big Data:
A Revolution That Will Transform How We
Live, Work and Think (2013). A society relying
primarily on big data destroys positive
incentive. “What incentive do I have not to
commit a murder if I am punished anyway?
More mundane: what interest do I have to
improve my lifestyle if my health insurer charges a higher
premium based on my genetic likelihood to suffer diabetes?”
The shortcomings of small and big data alike have been
ignored too long. Mayer-Schönberger points to Robert
McNamara, former US secretary of defense, as an early
victim of data dictatorship. To measure success during the
Vietnam War, McNamara relied on the opposing side’s daily
body count, a figure blown out of proportion by US soldiers
on the ground. “Clearly, our data has become more
sophisticated in the last 50 years. Yet the lesson
to be learned from McNamara is that we need to question
the validity of data and the analysis drawn from it.”
ANECDOTAL ONLY
In Santa Cruz, the numbers look good. From July 2011 to the
beginning of 2012, when PredPol was installed on laptops
in patrol cars, crime rates in the city decreased. Figures for
assault were down by 9%, burglary by 11%, robbery by 27%;
but the number of arrests rose by 56%. “And the only thing
we changed in that period of time was PredPol,” says Steve
Clark, the city’s deputy chief of police.
The thought of blind reliance on statistics like these is
what keeps Mayer-Schönberger awake at night. “By
providing correlations, big data does not fit the concept of
cause and effect, yet it is often abused to explain causal
relations.” Prior to big data, individuals would expect their
insurance premiums to rise only in the aftermath of
accidents for which they had claimed compensation. Now,
the price may go up before the accident occurs.
“In the US, drivers with better high-school
grades pay less for car insurance because
better grades correlate with a lower risk of
accidents. But do we really want to penalize
people for something they have not done and
may never do?”
While PredPol only uses information about
Viktor Mayerthe type of crime, its time and location, Clark is
Schönberger and
keenly aware of the risk involved in numbers.
Kenneth Cukier
analyze how
“Any evidence from Santa Cruz that PredPol
big data could
works is anecdotal,” he argues. If anything, the
transform our lives.
program helped officers deter crime more
Allianz • 31
Focus
Focus
often, Clark believes. And he prefers to
add gut feeling to his judgment.
“The best sign of success for me is if
I see a woman walking down the street
with a stroller.” The number of arrests
is clearly the wrong benchmark to
measure the success of crime programs, warns George
Mohler, PredPol’s chief scientist and an assistant professor
at Santa Clara University’s Department of Mathematics and
Computer Science.
To measure the program’s success accurately, the
amount of patrol time per hotspot needs to be related to
changes in the crime rate, Mohler suggests. Randomized
controls should be added to establish a causal relation
between the crime rate and PredPol. “However, this is an
academic interest. Most police departments using the
software do not conduct randomized controls.” And that’s
fine, Mohler says, but “you just won’t be able to say for sure
what caused the crime rate reduction.”
PredPol and
programs like
it are used in
cities across the
US, including
New York Cit y.
ERRORS WILL BE MADE
As a safeguard against big data’s dark sides, MayerSchönberger calls for a use-by date as well as legal
procedures for consumers to disprove the data-based
probabilities calculated by the software’s algorithms, if
necessary. In contrast to current strategies such as ‘notice
and consent,’ the onus of handling such algorithms and
probabilities responsibly should be placed on data users.
Based on a code of conduct, such users would have to assess
the impact on individuals described by the data. Breaches
would be liable to fines and maybe even criminal
prosecution. “These reforms need to be implemented as
soon as possible. Otherwise, the use and abuse of data
establishes facts which will be difficult to reverse.” Also,
private-sector firms such as insurers could create a niche by
emphasizing their responsible approach towards big data.
Fred H. Cate, professor of law at Indiana University (see
‘If … Then,’ page 18), supports the call for an appeals process.
“In the meantime, however, a relatively small number of
people will likely suffer from incorrect correlations drawn
from big data, for example by being denied access to a plane
or by paying a higher insurance premium,” he says. With big
data’s use in law enforcement and elsewhere likely to increase
in the future, the debate about the National Security Agency
(NSA) triggered by Edward Snowden is crucial for democratic
societies. “As police officers, our use of big data is a reflection
of the society we are serving,” Clark notes.
Whether society will heed the warnings of MayerSchönberger and Cukier remains to be seen. “I tend to be
optimistic on days with even dates,” Mayer-Schönberger
says. The interview was conducted on an uneven date. 32
•
Allianz
Allianz • 33
Video
Bonus content in
the PROJECT M app
Focus
Automating Advice
The rise of digitally delivered, managed accounts offers
convenience, but the quality of investment advice
underpinning them must be paramount.
Technology
can help when
planning for
retirement,
but one must
stay vigilant
regarding
goals.
34
•
Allianz
Focus
By Stacy Schaus
T
he ultimate responsibility for
retirement investing and planning
increasingly rests on the shoulders of
individuals. Workers must count on defined
contribution (DC) programs to meet their
retirement savings needs, as few today have the
defined benefit pension that traditionally
offered financial security in their golden years.
To help ensure they reach their retirement
income goals, they often look for expert advice.
DC participants are often offered one or more
sources of advice, either delivered within an
investment structure or a separate offering.
The primary question being addressed for
participants is this: “How should I invest my
money?” Target-date strategies and managed
accounts both aim to answer this question
for participants and, better yet, shift an
individual’s asset allocation over time.
Placing trust in sponsor or employer
For the mass population, these packaged,
technology-delivered advice solutions fill an
important need in the retirement market.
Unlike target-date strategies, managed
accounts give participants the opportunity
to view retirement income projections, to add
in outside funding (for example, spousal
retirement savings), as well as the option to
modify risk levels to inform the advice models.
In reality, however, fewer than 20% of
managed account participants add information
into the models. As a result, the advice from the
managed account system may be no more
informed than target-date strategies – that is,
both will tend to default a participant based on
the assumed number of years to their retirement
date or the expected time horizon for
investment.
Despite the fact that few participants engage
with their managed accounts in this way, both
target-date strategies and managed accounts
offer a big advantage over static balanced
portfolios or participant self-selection from a
fund line-up. By at least managing assets with
a participant’s anticipated time horizon in
mind and offering professional oversight,
they are likely to serve workers better.
The most important role these offerings
must play is their ability to evaluate
the underlying advice and confirm its
appropriateness for plan participants. This is
important because workers defaulted into
these programs are highly likely to remain
invested in them over many years – and even
throughout their retirement years when they
retain assets in the DC plan.
In many cases, participants blindly trust
their plan sponsors or employers to put them
on the right path toward reaching their goals
and trust that they are receiving reasoned and
appropriate guidance. In essence, the tendency
for schemes to default participants, combined
with the participants’ own inertia, determines
early on whether participants are likely to
succeed or fail in meeting their income goals.
Given their weighty responsibility here, it’s all
the more important for plan sponsors to
evaluate the plan’s default investments
carefully – whether target-date strategies,
managed accounts or other types of investment.
It is absolutely critical, then, that
fiduciaries are able to evaluate the risks.
They need to ask the right questions, receive
guidance on selecting sound advice and be
helped to evaluate advice providers.
» T echnology
helps workers
see and
understand how
their retirement
plans are
progressing.
«
Don’t be dazzled by technology
Technology helps workers see and understand
how their retirement plans are progressing –
people like to see the balance of their DC
accounts on their phones and how they are
allocated. It makes the planning process so
much clearer and easier for the individuals.
But it’s important not to be dazzled by
technology. The plan sponsor must not lose
sight of the end goal: to help people build
purchasing power in inflation-adjusted dollars
with investment plans that minimize risk and
perform regardless of the kind of economic
environment they operate in. Advice made
easy through digital tools is a step forward,
but it has to be sound advice. Yo u n g a n d o l d ta k e adv i c e t h ro u g h n e w t e c h n o l o g y
In the US, the take-up of managed account and advice solutions delivered to
end users through technology, rather than face-to-face advice, seems to differ
by age cohort. Those most interested tend to be either very young or much
older people. The interest among those closest to retirement is surprising. It’s
not yet clear why this is so, and further research needs to be done.
Allianz • 35
Focus
Focus
How we view and
conduct each aspect of
our lives is changing –
and faster than ever.
fast-forward
A new Allianz-owned company, the Digital Accelerator, is racing ahead of current digital
developments in order to serve insurance customers better – now and far into the future.
By Bernd Scharrer
G
adgets that give us constant feedback (such as
cars that tell us our braking efficiency), giant
data sets that help authorities warn of the next
flu outbreak, websites where people can swap goods and
services instead of buying them – it’s an understatement
to say that modern technology is changing the way we live
and conduct business. The question is actually, “How can
technology help people live the lives they want and meet
fundamental needs, such as the need to feel secure and be
connected with others?”
Business ideas that focus on the smart home,
telematics, e-health or wearable computing may make a
contribution in this area. In the end, each business model
fits into a larger technological trend, such as the move to
interlink devices (the Internet of Things), predictive
analytics, the shared economy or the ‘quantifiable self.’
And it is often small, creative businesses – start-ups – that
are bridging the gap between technology and human
needs. They’re competing in a race to solve problems in
the fastest, most creative way.
In the entrepreneurial sector, start-ups use a ‘lean’
approach: a young company begins testing a product
on the market once it has a ‘minimum viable’ version
available, with little up-front investment. In large
companies, where established brands are at stake, the
approach is the opposite. In the corporate world, people
take days, months and even years to create and validate a
product concept. Then a large portion of the budget is
spent building the product. Finally, in a third phase, the
company gathers real customer feedback, which is also
about the time the budget is exhausted. Some large
companies, however, are taking cues from the start-up
world and turning this corporate product development
cycle on its head.
proactive customer care
At the Allianz Digital Accelerator (an independent Allianzowned company) we’re exploring new business models as
part of our effort to shape the digital insurance world.
We’re using lean start-up ideas to take business concepts
and fast-forward them to the customer-feedback stage.
We are acting instead of reacting to find out what people
really want. These business ideas stand to benefit Allianz
in any number of ways by helping the company interact
more frequently and naturally with customers and
potential customers, or sell additional services.
Imagine insurance products that act similarly to
shared-economy business models, such as car sharing or
Airbnb.* This is not a fiction. There are already tech
companies and start-ups venturing into this field.
Alternatively, what if there were a way to create products
or services based on the vast data many companies
already possess – for instance, by developing anonymous
consumer profiles that could be used to provide individual
or customized insurance and service offerings?
There’s also potential in the smart home because
people want to understand and manage their lives better.
There are already apps that inform absent users what’s
happening in their homes. Pulling data from a variety of
sources and sensors, the app informs working parents
when their children arrived home and if they forgot to lock
the door on the way back out. It could also alert absent
homeowners if the smoke or water alarm goes off so that
they can react quickly to limit damage and loss.
the quantifiable self
The Accelerator is also focusing on vehicle telematics and
data analytics. To this end, the company is testing a nonAllianz branded app for young drivers that allows them to
collect ‘credit miles’ for their driving and redeem them for
awards, such as gift certificates or coffee. The project
allows the Accelerator to test how open young people are
to apps like these that could potentially help them gain
driving experience and improve their skills.
This can also allow companies to provide them with
better insurance benefits in the future and enable
services to be more tailored for individual needs. While
drivers today can gain credits when they brake and drive
in an energy-efficient way, tomorrow’s motorists are more
likely to demand a ‘pay-as-you-drive’ rate for insurance
premiums. Would an app that enables pay-as-youdrive, in conjunction with data recorded in vehicle
telematics, function?
Two final areas of interest are e-health and wearable
computing. Online health and activity marketplaces that
bring people together, much like a sports club does in the
physical world, could make a positive difference. Such a
site could help like-minded people gather for sports and
leisure activities – for instance, to set a meeting point for a
Saturday morning jog.
When people do meet, they often have a number of
computers attached to their clothing or worn as
accessories. A watch or sensor sewn into a jogging outfit
may double as a fitness tracker, measuring the kilometers
run and calories burned.
Similarly, wearable computers could be used to keep
workers safer at a dangerous construction site or to monitor
and prevent certain medical conditions. Such new
possibilities – often referred to as ‘the quantifiable self’ –
are all part of the interesting data trends that are shaping
lives – and our business. *A website f or seeking and of fering inf ormal and unconventional accommodation around the world
36
•
Allianz
Allianz • 37
Focus
From the
cradle to the
grave: data
collection
today begins
at the
earliest
stages of
modern life.
my creative juices flowing. And then
[Yahoo CEO] Marissa Mayer mentioned
big data to me. I told her, “I’m a
photographer. I don’t really think that
sounds like something for me.” Then she
said you could compare it to the planet
developing a nervous system. That got
my attention.
It’s still quite an abstract topic, though.
Smolan: We spent 18 months trying to
figure out how to tell the story, to see if
we could capture this transformation in
the form of photographic essays. A lot
of publishers were very dubious, so we
decided to self-publish the book.
How do you explain big data?
Smolan: Thanks to my 10-year-old son, at
some point I hit upon an analogy. One
night he asked me why I was always
talking about big data whenever I was on
the phone – what did it mean? I struggled
to come up with something that would
make sense to him and then said,
“Imagine if, for your whole life, you had
only been looking through one eye, and
then scientists allow you to open up a
second eye. All of a sudden you’re not
just getting more vision, you’re getting
a different dimension, a whole new
perspective.” He told me how cool that
was and asked whether we could also
open up a third or fourth eye, or even a
thousand eyes. And that’s exactly what’s
happening now.
»
From the beginning of recorded
time until 2003, we created
5 exabytes (5 billion gigabytes)
of data. In 2011, the same amount
was created every two days.
By 2013, it’s expected that the
time will shrink to 10 minutes.
Rick Smolan
«
WATCHING THE WORLD
DEVELOP A NERVOUS SYSTEM
You thought the Internet was big.
But it’s not as big as big data, the global information network
that is transforming the world. Photographer
Rick Smolan tells PROJECT M how he captured the rapidly
changing face of the data revolution.
W
here did you get the idea to put together a
book on big data*?
Rick Smolan: I had some experience in putting
together large-scale projects with the “Day in the Life”
series of books. I found it fascinating to gather a group of
journalists from around the world to really explore a place
in as much detail as possible. After exploring different
countries, I set up my own production company with my
wife, and we started to focus on more technological themes.
A couple of years ago, I found myself looking for a new
subject. I was going to TED conferences and seeing some
interesting stuff, but there wasn’t anything that really got
Which areas of our lives do you think
will be most affected?
Smolan: For me, the medical and healthcare aspect was
particularly interesting. By the time we become ill, our
body has often been giving off signs that something isn’t
quite right for some time. Until recently, we just haven’t
had the means of measuring ourselves and creating a
baseline for own body. But things are changing. When
Steve Jobs had his DNA sequenced five years ago, it cost
$100,000. Today, it’s $3,000. In five years’ time, it might
well be $50 at your local pharmacy. And then you’ve got
wearable devices, such as the UP wristband, that you can
use to track your own exercise, diet and sleep patterns.
It’s the ‘gamification’ of health.
The projec t “ The Human Face of Big Data” is editoriall y independent and is made possible through the generous suppor t
of EMC Corporation, which ser ves as it s primar y sponsor. Suppor ting sponsor ship comes f rom Cisco Sy stems , SAP and FedE x .
38
•
Allianz
Allianz • 39
Focus
As
technology
continues its
advances, big
data is
increasingly
entering the
public
agenda.
Are you worried about what happens with all this data?
Smolan: I am worried that, for the most part, it seems to be
governments and large companies who are realizing the
value of it. I don’t think the average person should say that
they don’t really care about their personal information. It’s
naïve to think there’s no value to it, and I think we should
have more of a say in what happens with our data.
the Internet. Now we need the Internet, its worldwide
network, to form the basis of big data. All these devices are
now talking to each other, and they change their behavior
based on their interactions.
I think that 2013 will come to be known as a point of
demarcation – before big data and after. It’s going to be
such a huge part of how everything works. There’s almost
no field you can think of where it’s not already having some
sort of impact. Do you think it’s a topic that is properly understood by
the general public?
Smolan: When we started
with this book, a lot of
people weren’t familiar with
The Human Face of Big Data, by Rick Smolan and Jennifer Erwitt
the idea of big data. But
during the last year or two, it
How do you picture something that isn’t concrete – an idea, a method,
movement itself? Big data – the incomprehensible amount of information
has certainly entered the
collected, processed and deployed second by second – can be neither depicted
public agenda. It’s really
nor comprehended. Yet The Human Face of Big Data sets our imaginations
growing on a daily basis.
in motion with images and graphics that explain why, in the words of British
I must admit that, initially,
data commercialization entrepreneur Clive Humby, “Data is the new oil.”
I thought it was a lot of
In compiling their volume, Smolan and Erwitt took photographs of the people and their work
marketing hype created by
that have transformed global data collection and use – and been transformed by them. We’re
technology companies to
in the thick of “an extraordinary knowledge revolution,” Smolan writes in his foreword, “that’s
suit their own needs. Now
sweeping almost invisibly through business, academia, government, healthcare and everyday
life … big data may well turn out to be the most powerful toolset the human race has ever had
there’s no doubt in my
to address the widespread challenges facing our species and our plane ... [and it] carries the
mind that this is going to
potential for unintended consequences.”
be a thousand times more
influential on our species
than the Internet has been –
Rick Smolan
and the Internet has been
pretty damn dramatic. It’s
i s a former Time, Life, and National Geographic photographer. Now, as CEO of
an evolution. We needed
Against All Odds Productions, Smolan producers large-scale global photography
projects which combine storytelling with state-of-the-art technology.
to have microprocessors to
Against All Odds Productions was named one of the “25 Coolest Companies
build computers. Then we
in America” by Fortune Magazine,and its projects have been featured on the
covers of Fortune, Time, Newsweek, and U.S. News & World Report.
needed computers to build
40
•
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Focus
STRENGTH IN NUMBERS
We live in the age of information, where the sheer volume,
velocity and variety of data being created necessitate their being
processed in a new way. The data and its related technology
offer more than just health insights – they could even save lives.
N
» They needed
a computer
platform to take
all the different
signals from
lots of different
babies and
environments.
Dr. Carolyn
McGregor
«
othing is quite as vulnerable
as a premature baby fighting for
its existence, alone in a neonatal
intensive care unit. That tiny body lies tethered
to numerous monitoring devices that provide a
continuous feed of vital signs – such as heart
rate, breathing and blood pressure – at a rate of
a thousand readings per second. The exhaustive
volume of data is too much for physicians and
nurses to absorb. After 24 hours, it is discarded.
Such data, however, could provide vital signals
about a premature baby’s fragile condition.
Computer scientist Dr. Carolyn McGregor,
whose first child died after an early birth, hopes
to provide premature babies with an extra
chance. She has devised an online health
analytics platform called Artemis, named after
the Greek goddess of childbearing. As Canada
Research Chair in health informatics at the
University of Ontario Institute of Technology
(UOIT), McGregor and her team of researchers
are collaborating with IBM at a number of
hospitals to test software that tracks vital
signals in premature babies.
McGregor’s work follows research showing
that babies who develop infections display
changes in their heart rate, or heart-rate
variability, 24 hours before the infection sets in.
“People had already identified this trend but
didn’t have a way to watch it in real time,” she
explains. “They needed a computer platform to
take all the different signals from lots of
different babies and environments to continue
research on infection, but also use the same
platform to research many other conditions.”
The software processes the newborns’ vital
signs in real time, tracking 16 different data
streams – such as heart rate, breathing, blood
oxygen levels and blood pressure – which
together amount to 1,260 data points per
second per baby. It also seeks patterns in the
data, then stores the information. The hope is
that Artemis will allow doctors to identify
subtle changes in a baby's condition that
may signal the onset of infection or another
medical condition. Taking over from a doctor's
‘intuition,’ the software provides signals that
the naked eye would miss, and allows clinicians
to administer medical treatment before
symptoms deteriorate. “We monitor premature
babies’ heart rate and respiration,” McGregor
continues, “and can delineate whether heart
rate variability happens shortly before the
onset of an infection or because the baby is
being given certain drugs, which can also
trigger heart-rate variability.”
LOOKING BEYOND INFECTION
Artemis was first introduced at the Hospital for
Sick Children in Toronto in 2009. In 2010, a
cloud-computing version went live at the
neonatal unit of the Women & Infants Hospital
in Providence, Rhode Island, where readings are
fed to the UOIT. The project was extended in
December 2012 to China’s Children’s Hospital of
Fudan University in Shanghai. “In China, they
don’t use morphine,” McGregor explains,
“allowing us to carry out cross-cultural studies
and see the different heart-rate variability
changes without the use of morphine.”
McGregor and her team have now moved beyond
looking only at infection to examine various
other conditions, such as retinopathy of
prematurity (an eye disease that causes some
premature babies to lose their sight, notably
afflicting blind pop star Stevie Wonder), or
premature babies who forget to breathe, as their
brain stems aren’t yet fully developed.
Allianz • 41
Focus
Focus
»
There is a human
factor in trying to
keep an eye on
250 people. You can’t
continuously
monitor each one
for every second.
Professor Dr. Timothy
Buchman
«
McGregor is also trialing an algorithm that
classifies different types of conditions, such
as low oxygen levels or gaps in breathing.
Other plans include a study on adults. She also
intends to continue testing with the Apollo
project, which provides home-based monitoring.
“When these premature babies go home,” she says,
“the Apollo platform would alert a medical person
if there is a change in the babies’ condition.”
While McGregor is still in the process of
publishing and confirming the findings from
the project, she is hopeful that Artemis will be
introduced in neonatal intensive care units
(NICUs) worldwide. She is equally confident
about the beneficial effects of big data in the
medical arena. “Big data has the potential to
be the next disruptive technology after
genomics. We are at the cusp of a whole new
wave in clinical research.”
WHOSE INFORMATION IS IT?
With the vast amounts of personal data collected,
the question of moral responsibility urgently
needs to be addressed. Who has the right to collate
and publish all this information about a person’s
body and its functioning? How does it affect the
individual’s right to privacy? McGregor concedes,
“We still need a framework for this. It needs to be
on the mandate for public policy.” Opinion surveys
so far are positive. While people have concerns
about health insurers’ use of big data, most are in
favor of its use if it can provide insights that might
mean the difference between life and death for
premature babies.
As Dr. Timothy Buchman, professor of
surgery and anesthesiology at Emory
University in Atlanta, Georgia, and director of
the Emory Critical Care Center, points out, the
data involved in such projects are hardly
sensitive or high-risk. “We’re talking straight
physiology values, such as your blood pressure,”
he says, “which most reasonable humans aren’t
going to get sensitive about. Can you remember
what your blood pressure reading was two
years ago even, and are you bothered about it?”
He adds, “There is a human factor in trying
to keep an eye on 250 people. You can’t
continuously monitor each one every second.”
Fortunately, computers lend a hand where
humans could fail. Buchman and colleagues
have been using software from IBM and Excel
42
•
Allianz
Medical Electronics since early 2013 to monitor
intensive care patients using real-time
streaming analytics. The system can analyze
more than 1,000 real-time data points per
patient per second and identify patterns
that could indicate serious complications,
such as atrial fibrillation, an abnormal heart
rhythm triggered by a lack of blood oxygen or
drugs. Buchman is certain that the research
project will be deployed quickly at the hospital.
“Instead of looking at single, six-second
snapshots of ICU patient data, this system lets
us see new views and trends of data that are
being processed in real time.”
In his opinion, big data technology and
real-time analytics will ultimately transform
the world of critical-care medicine. “Big data
will not make a diagnosis for us but will act
as an early warning for caregivers to show us
who is heading in the wrong direction.” He
envisages a future where the same predictive
capabilities possible in weather forecasting, for
example, will also be employed in medicine.
This new world of healthcare will include
better preventative care. “We are going to look
after patients by keeping an eye on them not
just in the ICU but also in their daily lives via
tracking devices,” says Buchman. “There is a
lot of information we need to know. If you are
old, infirm and forgetful, we need to know that
you are taking your medicine. Or if you get lost
frequently, we need to know if you are straying
off your usual routes.”
The next generation of caregivers will need
a broad skill set, including being adept at
technology. With ground-breaking devices to
monitor, collect and assess data, the ability to
manage these tools will be vital in assisting
healthcare practitioners to allow all of us to
live longer, high-quality lives.
Big data and disease detection
Dr. Craig Feied, professor of emergency medicine at
Georgetown University, believes big data will transform
medicine for the better. The inventor of a system known
as Azyxxi, which provides real-time access to patients’
medical history at the touch of a button, is convinced
big data will help identify patterns that can help in
the early detection of diseases, such as cancer. Read this
exclusive interview at www.projectm-online.com
Allianz • 43
Micro
Picture Galler y
Bonus content in
the PROJECT M app
Loc al k now le dge
Blurred
picture
those who are at the start of a crisis, rather than leaving
them to be eventually rescued from a factory or become a
victim of human trafficking.”
Using education as a weapon in the fight against child
labor would also help children who are being exploited by
their families to work long hours on various domestic
chores, and those who are treated harshly. Globally, says
Edmonds, primary school numbers have increased
dramatically over the last 15 years, but secondary-school
enrollment remains at a low level in many developing
nations.
Children in many parts of the world
spend far more time at work
than in the classroom. But until
countries offer truly universal
education, we should be slow to pass
judgment on all forms of child labor.
In many countries,
child labor is a thing of
the past.
A
distressing examples, such as Uzbekistan – where the
t the turn of the 20th century, child labor was
government has introduced a forced-labor system to get
commonplace in the West. Children from poor
backgrounds could be found working in mines,
under-age workers to harvest cotton – the majority of child
factories and mills, and on street corners, selling
labor is not a product of coercion. Nor does it involve
children working in dark, dangerous 19th-century-like
newspapers or cleaning shoes. Sometimes working at night,
conditions, separated from their families, says Eric V.
minors – with their ability to handle small parts and tools –
were an attractive commodity for employees who only paid
Edmonds, professor of economics at Dartmouth College in
them low wages for their labor.
New Hampshire, US.
Deprived of an education and a carefree childhood,
many working children also developed serious health
Educational investments
problems, such as stunted growth and lung diseases.
“Those horrific images of children stuck in a Bangladeshi
Others suffered horrific injuries following accidents
factory fire [November 2012] – that’s not what most working
involving machinery.
children are doing. Most children who are working are
But thanks in part to the social activism of campaigners
doing so in the family business or farm, beside their parents
or other family members,” says Edmonds.
such as photographer Lewis Hine, the prevalence of child
labor died out, with several governments eventually
The US academic, who has served as an advisor on child
passing laws to prohibit minors from working – such as the
labor for the ILO and the US government, says that in India,
Fair Labor Standards Act of 1938 in the US. As a
for example, many parents feel that their
children should develop skills in the home,
reporter for the National Child Labor
M ost children
who are working
Committee, Hine stirred consciences in the US
farm or business that they are eventually going
are doing so in
and beyond with his images, which depicted
to step into and run themselves. “Parents are
the family
children as young as six working under
struggling to weigh up the sense that the child
business or farm,
hazardous conditions. His photography is a
should be learning life skills versus the sense
beside their
reminder of a bygone age in much of the
that the child should be in general education
parents or other
developed world, but child labor remains
and accumulating those sorts of skills,” he says.
widespread in many countries, and even in
family members.
The reverse is also true. Edmonds explains
pockets of Europe and the US.
that there is compelling evidence from Brazil
The International Labour Organization (ILO) estimates
that shows that parents face problems in preventing their
that there are some 168 million children whose primary
offspring from leaving school to enter the labor market.
activity is work. Asia and the Pacific have the largest
“Kids tend to be more myopic and not understand the value
population of child laborers (78 million), followed by Subof educational investments when young, so parents face
Saharan Africa (59 million). Latin America, the Caribbean,
this same problem throughout much of the world. How do
the Middle East and North Africa also have high populations
you stop children from trying to assert their independence
of under-age workers. Apart from some notable and
at such an early age?” he asks.
» «
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•
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Micro
For less developed
countries, children remain
a vital source of labor.
Although many children are willing workers, particularly if
they come from an impoverished background, the ILO and
similar organizations remain concerned for their welfare.
Even though they may be working in agriculture alongside
their family members, as many are, they run the risk of
being exposed to chemicals or machinery without
adequate protective gear or training.
Preventing children from being exposed to such risks,
however, is difficult. Every country in the world, bar
Somalia, has laws prohibiting minors from entering the
labor market, but the public and the authorities in child
labor hotspots either ignore them or are powerless to
implement them.
In fact, most countries have, for varying reasons, chosen
to overlook elements of their own laws. The US government
is one such culprit. It has decided not to enforce the laws of
child employment in family farms, precipitating a bizarre
situation in which 14-year-olds in Wisconsin can operate
combine harvesters but still be two years away from taking
their driving tests.
But as Edmonds says, a laissez-faire attitude to
enforcement of minimum working-age regulations is
actually a practical one to take. Although keen policing
would provide a useful extra tool to identify and tackle
abuse, most countries simply do not have the capacity to
enforce their existing minimum employment regulations.
And in other cases, the cost of upholding such laws far
outweighs the benefits.
Instead, Edmonds argues, governments should
concentrate on extending education and implementing
compulsory schooling laws.
“This is an under-used tool,” he says. “We have widescale primary school enrollment around the world, and it
can be used as a way of monitoring children and identifying
Compulsory schooling is more effective
“I expect enrollment to grow, and we should also see a
decline in child labor associated with secondary school
growth,” he explains. And there is a historical precedent
illustrating the power of education to discourage child
labor. More than a century ago, Western countries shocked
into action by the likes of Hine demanded action. The
introduction of compulsory schooling laws arguably had a
better effect than any laws forbidding the employment of
children.
Edmonds warns, however, that until education becomes
more common and there is a clear black-or-white choice for
families, simply taking children out of a freely chosen work
environment can only be justified if there is a better
alternative for them. “I always ask myself what a child who
is working in a particular job would be doing if they didn’t
have that job. And I’ll tell you right now, it’s not going to be
enrolling in elite private schools around the world,”
Edmonds says.
“Where there are free and functioning labor markets,”
he continues, “and a child in a particular job, then most of
the time that child is doing that job because either the child
or the parent believes the job the best possible opportunity
available to the child. Sitting in my office in the US, am I in
any position to know better?” c h i l d l a b o r fac t s
•9 8 million children around the world work; 54 million of them in
services and 12 million in industry.
•S ince 2000, labor among girls has fallen by 40%; among boys, by
25%.
•T he International Labour Organization wants to eliminate the
worst forms of child labor by 2016. These include work in
dangerous environments (underground, in water or at dangerous
heights); work with dangerous machinery only suitable for
trained adults; and long hours of factory work.
Source: Marking progress against child labour – Global estimates and
trends 20 0 0 -2012 (ILO - IPEC , 2013).
Allianz • 45
Micro
The government introduced reforms in order
for private pensions to become simpler,
cheaper and more accessible. It’s also running
a nationwide communications program to
educate the public, featuring ads on the main
television channels. These measures are
making pensions a mass-market financial
product, like car insurance and bank accounts.
Many experts
believe that
auto-enrollment in
UK pensions has
been a success.
AUTOENROLLMENT
SHAKES UP
UK PENSIONS
Minimum
Contributions
Employer
Total minimum
contribution
1 %
A new UK initiative to get greater
numbers of people saving more
for their pensions aims to avert
the imminent financial crisis
posed by an aging population
I
n October 2013, Prince Charles gave a
speech to the National Association of
Pension Funds in which he suggested
the UK’s pension industry should turn away
from quarterly capitalism and instead address
sustainability issues.
The event coincided with the first
anniversary of the UK’s auto-enrollment
initiative for pensions, which stipulates that
the employers must automatically enroll
46
•
Allianz
workers in a pension scheme if they fit certain
criteria. By 2018, most of the working
population should be saving in a private-sector
pension scheme.
The new law was introduced because of
government fears that the growing number of
pensioners will eventually create too much of a
burden on state pensions. The Department for
Work & Pensions warns that by 2050 there will
only be two workers per pensioner, compared
with three in 2010 and ten in 1901. The government
aims to increase the number of individuals saving
in a workplace pension plan by around 8 million,
funneling an estimated extra £11 billion
($17.6 billion) a year into pension schemes. So far,
1.6 million people have been enrolled.
Auto-enrollment is also the biggest shakeup in the UK’s pension industry for decades.
Employer staging
date to 30 Sept 2017
2 %
2 %
1 Oct 2017 to
30 Sept 2018
5 %
3 %
1 Oct 2018
onwards
8 %
Source:
The Pension Regulator
Setting up a NEST egg
In order to shake up the pensions market and
ensure that there is always a provider of last
resort, the government launched the National
Employment Savings Trust (NEST), a notfor-profit organization with a number of
innovations, including retirement date funds.
Its asset allocation changes according to
economic conditions and how far an individual
is from retirement.
“Auto-enrollment is having a beneficial
impact. It is creating lower-cost pensions,” says
David Pitt-Watson, a spokesperson for the
Royal Society for the Encouragement of Arts,
Manufactures and Commerce. “NEST has been
particularly good in leading the way.” Savers
can take their NEST accounts with them as they
change employers, and some companies offer
NEST pensions alongside other alternatives.
Additionally, a major UK pension provider has
thrown down the gauntlet by cutting its fees
and even challenged the government to lower
its 0.75% fee cap to 0.5%.
Industry experts such as Henry Tapper,
director of First Actuarial and a founding editor
of Pension PlayPen, see NEST as a good default
pension scheme for small businesses, given its
simplicity and ease of use. Graham Vidler,
director of communications and engagement
with NEST, says the organization has
deliberately developed tools to make the
process easier for small employers. “The big
challenge is ensuring employers and
intermediaries know what they need to do,” he
says. He advises smaller firms to start preparing
at least six months before implementation. But
one year on, has it worked?
OUTSTANDING SUCCESS
The government expected one-third of
employees to quit; instead, only 9% have left the
scheme. “So far it has been an outstanding
success,” says Tapper, whose website Pension
PlayPen is dedicated to helping small
businesses with auto-enrollment. He notes
that employee acceptance has been good, and
that the government and employers have done
a good job explaining the scheme. The Trades
Union Congress, which represents
54 unions, also hails it as a success.
“Auto-enrollment plays on people’s
tendency towards inertia,” says Neal Blackshire,
benefits and compensation manager with
restaurant chain McDonald’s UK. “Besides,
people know that they should be saving for
their old age.” McDonald’s employs 37,000
people in the UK, with 35,000 of them paid
hourly. There are another 57,000 working in
franchised restaurants. To date, the fast-food
chain has auto-enrolled over 1,150 salaried
employees and 11,500 on hourly pay. The optout rate has been 3.48% and 2.15% respectively.
Drawbacks and difficulties
Implementing the scheme has been difficult
for companies with large workforces.
Blackshire says that several years of
preparation and close cross-departmental
cooperation were required, and McDonald’s
brought in outside consultants to help
communicate auto-enrollment to its workers
to make sure they understood it.
There is some concern that opt-out rates
will rise once small companies have to
implement the scheme. Firstly, they may be less
financially able to bear the burden of partly
funding employee pension plans. Secondly,
they often have very little in-house knowledge
about running pension schemes. “There’s been
a lot of scaremongering about the costs of autoenrollment, particularly for small businesses,”
says Tapper. “But I think it’s overdone. It is not
that difficult to set up.” He notes the increasing
numbers of providers launching products to
make implementation easier.
The scheme may even have caught the
mood of the nation: “I think the financial crisis
has changed many consumers’ priorities from
being in debt towards wanting to save,” says
Vidler. “People aren’t spending so freely.”
Nonetheless, there is some expectation in the
industry that opt-out rates will probably
increase over time. But so far, so good. Allianz • 47
MICRO
MICRO
CAN ELDERLY
WELL-BEING BE
MEASURED – AND
MAINTAINED?
Global Age projections
P r o p o r t i o n o f t h e w o r l d ’s p o p u l a t i o n
aged 60 years or more:
22%
16%
Aging populations in both industrialized and
emerging countries are posing a challenge to
policy-makers all over the world. Research can
assist in coming up with effective solutions.
11%
2012
T
POLICY DILEMMAS
The long-term sustainability of public finances was a core
issue of many policy measures in developed countries in
recent times and – as pensions, health and care account for
the lion’s share of public expenditure – they have been the
48
•
Allianz
2050
Sources: UNDE SA Population Division, Population
Ageing and Development 2012, Wall Char t, 2012;
UNDE SA Population Division, World Population
Prospec t s: The 2012 Revision, 2013.
By Renate Finke, senior researcher
he pressure that mass aging is placing on
pension systems is a worldwide phenomenon
that affects industrialized and emerging
countries alike. It is driven by rising life expectancy in
combination with decreasing birthrates. As a result, the
number of elderly in society is growing, while the
proportion of younger people is shrinking. The reasons
lie in the interplay between better healthcare, improved
nutrition and higher standards of living.
The consequences affect different economic and societal
areas and are complex. Although nearly all countries have
been experiencing aging-related pressure, solutions are
running at different speeds and start from different markers.
As a result, policy-makers have differing perspectives on the
impact of aging in their respective countries.
In addition, policy approaches tend to tackle particular
issues independently. Research can contribute to widening
the approach and analyzing interactions between different
areas of life and living conditions. The recently launched
Global AgeWatch Index from HelpAge International, an
organization that advocates the rights of the elderly,
provides one such approach by combining aspects that
contribute to a satisfactory life in old age. The index includes
indicators for the four areas “income security,” “health
status,” “employment and education” and “enabling
environment.” A country’s ranking shows how well it is
doing in supporting the well-being of its aging population
and focuses attention on individuals.
2030
most affected areas. In an effort to ease pressure on public
finances, most countries commenced pension reforms at
the turn of the century, which saw benefit levels reduced
and more responsibility placed on the shoulders of
individuals to provide for their own retirement.
While improving the sustainability of the system, these
reforms have often left future retirees with the prospect of a
lower replacement level from first-pillar pensions than
today’s retirees. This has placed the question of the
adequacy of retirement income on the political agenda.
While it is no surprise that wealthier countries top the list of
the Global AgeWatch Index, this may change in the future.
Australia and New Zealand both rank high on the Allianz
Pension Sustainability Index (PSI), which analyzes the
Nearly all
countries are
feeling the
pressure of
aging, but
their
approaches
and solutions
vary greatly.
sustainability of first-pillar pensions. It is interesting,
however, to see that both have low rankings in the income
security sub-index of the Global AgeWatch Index. This may
point to the fact that sustainable pension systems struggle
to deliver adequate levels of retirement income.
On the other hand, Brazil ranks low on the PSI but has a
relatively good ranking in the Global AgeWatch Index.
Obviously, a more generous pension system together with a
basic pension scheme for the elderly there protects people
from old-age poverty, but this ranking could change. A young
nation, Brazil’s population is bound to age rapidly in the near
future, putting the country under pressure to overhaul its
pension system and possibly cut back on pension levels.
CHALLENGES OF PENSION REFORM
It might seem odd to compare countries with such variation
in economic development, but this approach can open the
discussion on potential policy options and reform paths.
The challenges in emerging economies are different from
those of developed countries. When providing for old age,
the challenge has been – and still is – to establish wellfunctioning public pension systems and broaden the
coverage of existing ones to cope with the needs of a rapidly
aging society. These are typical consequences of
industrialization, rapid economic growth and urbanization.
The experiences of other countries, either developed or
emerging, might provide insights and ideas for setting up
new systems. Emerging countries have to deal with drastic
socio-economic changes that are placing traditional family
support systems under pressure, increasing the need for
organized retirement systems and basic income security
systems. It is a challenge to set up an index with such a wide
variation of countries and their different concepts of and
prerequisites for living in old age. But the comparison can
deliver surprising results, as the positions of Sri Lanka and
Bolivia (ranked 36 and 46 respectively) show. We know from
the setup of the PSI that it is very difficult to find data that
are comparable across countries and detailed enough to
come up with suitable insights and effective conclusions.
But it can indeed initiate and foster the discussion of what is
required to live a decent life in old age.
For an intuitive understanding of aging, scan the
code and view the interactive graph
“Demographic Insights.”
An updated version of the PSI is to be published in
March. It will be extended to cover 50 countries,
including Brazil, Chile, Mexico, Indonesia, Malaysia
and South Africa.
Allianz • 49
Video
Bonus content in
the PROJECT M app
Global oppor tunities
WIRED ON
ECONOMICS
Drama can provide a graphic
illustration of economic analysis.
Economist Peter Antonioni argues that
the hit TV show The Wire contains
more truth than many a dry formula.
MACRO
W
ith the world facing many very real
financial problems, you might
wonder why any economist would
turn his professional attention to TV drama.
Although, given the damage some economists
have wreaked in recent years, many people
would perhaps be happier if more of them
spent time engrossed in alternative worlds.
Peter Antonioni, an economist from the
department of management science and
innovation at University College London,
surprisingly agrees. “In a sense, all economists
are fantasy writers, but not all fantasy writers
are economists,” he quips, sitting wrapped up
in the chilly courtyard of the Set Theatre in
Kilkenny, Ireland.
Victor Hugo, to name a few examples,” he says,
pausing to sip from the pint of Guinness in
front of him. “But at the moment, what really
expresses our world is not the novel but
the long-form television program.”
He sees The Wire as a near-perfect
dramatization of many key themes economists
study, particularly all that can go wrong with
a city’s ecosystem. It starts with cops and
dealers, then spirals out to include the decline
of the working class, political institutions, the
school system, judiciary and media. Along
the way, it illustrates such standard economic
fare as the prisoners’ dilemma (why two
individuals might not cooperate, although it
is in their best interests to do so), as well as
offering a twist on Nash’s Equilibrium (where
two individuals stick to a chosen strategy
because each strategy supposes knowledge of
the other and a unilateral change brings no
advantage).
Central to understanding The Wire, argues
Antonioni, is the tragic figure of Frank Sobotka,
a union official who takes bribes to keep his
struggling chapter alive. At one point, Sobotka
says to a lobbyist, “You know what the trouble
is, Brucey? We used to make s*** in this
country. Build s***. Now we just put our hand in
the next guy’s pocket.”
The series is set at a time when Baltimore
was a strong contender for murder capital of
the US, with homicides numbering nearly
Economic theory & stand-up comedy
The evening before, at the 2013 Kilkenomics
Festival, he delivered a talk on economics as it
relates to The Wire. His sold-out performance
mixes economic theory with stand-up comedy.
Set in Baltimore, Maryland, The Wire is a
television drama depicting a city on its knees,
as seen from the perspective of the police,
politicians, junkies, gangs, street kids and
scared citizens. Antonioni explains that
economic insight can come from anywhere,
and it can sometimes be better expressed by
artists than economists or analysts.
“Throughout history, a lot of insights have
come from literature – Sophocles, Dickens,
» ALL ECONOMISTS
ARE FANTASY
WRITERS, BUT
NOT ALL FANTASY
WRITERS ARE
ECONOMISTS.
«
The price of cocaine
D r a m at i c d e c l i n e i n d o m e s t i c c o c a i n e p r i c e s d e s p i t e i n c r e a s i n g s p e n d i n g f o r o v e r s e a s
d r u g s u p p r e s s i o n ef f o r t s b y t h e U n i t e d St at e s
Note: Cocaine prices are purit y- and inf lation- adjusted and spending is inf lation- adjusted. All Prices e x pressed in 2011 USD.
US i n t e r n a t i o n a l d r u g c o n t r o l s p e n d i n g (b i l l i o n s USD)
80 0
8
70 0
7
60 0
6
50 0
5
40 0
4
30 0
3
20 09
20 07
20 08
20 05
20 06
20 03
20 04
20 01
20 02
1999
20 0 0
1997
1998
1995
1996
1993
1994
1991
1992
1989
1990
1987
1988
1985
1986
0
1983
0
1984
1
1981
2
10 0
1982
20 0
US spending on international drug
control (billions)
P r i c e p e r g r a m (USD)
Retail price per gram (USD)
TV series The Wire
depicts Baltimore
as seen through the
eyes of the police
and the gangs,
street kids and
scared citizens.
Source: US Of f ice of National Dr ug Polic y
50
•
Allianz
Allianz • 51
Macro
The police
combated the
emergence
of drug gangs
with limited
success.
» THERE’S
ALWAYS A
BALTIMORE
SOMEWHERE,
WHETHER it’s
CALLED MEDELLÍN,
CIUDAD JUÁREZ
OR DETROIT.
«
For more multimedia
content featuring
Peter Antonioni,
please visit
projectm-online.com/
new-perspectives/
wired-on-economics
52
•
Allianz
50 per 100,000 residents annually. That rate is
more than double the 20 per 100,000 recorded
in 13th-century England, an era known for
political instability, mayhem and bloodshed.
Baltimore, both in fiction and reality, was
then at the tail end of a period of industrial
change that saw the percentage of people
employed in manufacturing in the US decline
dramatically from the 1960s onwards. While
more is now being produced by fewer people to
create greater general wealth, Antonioni
argues that this transition comes at a
significant cost.
Economics is ‘gangster’ science
With his bushy beard, thick-rimmed glasses,
tattoos (a portrait of Austrian economist
Joseph Schumpeter is inked on his inner right
arm and an X-Men montage on his shoulder)
and skull-hugging beanie, Antonioni
resembles a minor character in his favorite
television program. Perhaps one of the scruffier
undercover cops or a shaggy docker watching
helplessly as his job gradually disappears.
In the chilly light of day, Antonioni is more
earnest than he was the evening before.
“Economics is ‘gangster’ science,” he says. “Not
so much in the way, say, that Nobel Prize
winners carry gold-plated Berettas, but rather
in the way economists look at the world with a
cold, hard eye, as if people don’t matter.”
Antonioni says economists are poor
at accounting for the transitional costs
of industrial transformations. There are
unemployment statistics, but intangibles like
the costs borne by families and communities
(such as rising rates of delinquency or declining
mental health) cannot be easily assessed until
the data comes out later. “This is where
something like The Wire is challenging, because
it dramatizes the social consequences and
forces us to change cost-accounting models.”
Unpacking the consequences
With his position compromised, Sobotka let
the rot set in. In real life, containerization – the
packaging of cargo into large standard
containers – had made it easier and cheaper to
ship goods (including what the dealers call
‘product’) around the globe. Antonioni notes
that, despite the billions spent and ‘successes’
achieved since Richard Nixon first
spearheaded the war on drugs in 1971, the
price for cocaine over the decades has been
steadily falling (see graph on page 51).
The consequence for Baltimore was
the emergence of drug gangs. The police
responded, sparking a local version of
mathematician Lewis Fry Richardson’s Arms
Race model, as both sides sought to counter
the threat of the other, resulting in a heavy
body count and corrupt leaders. The middle
class fled, which drained the tax base. Parts
of the city then fell into disrepair – with high
local unemployment, fragmented families,
crime and abandoned buildings creating a
desolate, inhospitable city landscape.
At the end of The Wire, despite a few minor
personal victories achieved by some of the
more likeable characters, there is a hopeless
feeling of déjà vu: major institutions further
corrupted; a greasy, venal officer in charge
of the police; and a psychopath controlling
the drug trade. “Baltimore in The Wire seems
to be a microcosm of US governance at the
beginning at the 21st century,” Antonioni
reflects. “Maybe this is only a temporary
period. But in another sense, there is always a
Baltimore somewhere in the world, whether
it’s called Medellín, Ciudad Juárez or Detroit.
“Should we be depressed about it?” he
asks, but doesn’t wait for an answer. “We
should be angry about it! We should look for
alternatives and realize the damage that is
being caused by the war on drugs. As one of
the police in the series says, it can’t even be
called a war, because wars end.” MAcro
From the Labs
Dwindling prices on data storage, explosive growth in mobile data
output and a continued battle against cybercrime – digitalization is
changing all facets of business as we know it.
Explosive Data Growth from Mobile Devices: The accumulated amount of data generated exclusively by mobile devices (phones,
tablets, phablets) is expected to reach 11 exabytes (billions of gigabytes) by 2016. Source: OECD, Exploring Data-Driven Innovation as a New Source of Growth,2013
11,000,000,000,000,000,000 B
Value in numbers
Full use of big data in Europe’s 23 largest governments
might reduce administrative costs by 15-20%, creating the
equivalent of $206 billion to $412 billion in new value.
Similar studies from the United Kingdom show that the
public sector could save $3.3 billion in fraud detection and
generate $6.7 billion through better performance
management by using big data analytics.
Source: OECD, E x ploring D ata- Dri ven Innovation
as a Ne w Source of Grow th, 2013
Data intensity
on file
Data intensity (measured as the
average amount of data per
organization) is highest in financial
services, communication and
media, utilities, government,
and discrete manufacturing.
In these sectors, each organization
typically stored over 1,000 terabytes
(1 petabyte) of data in 2009.
S ource: OECD, E x plor ing D ataD r i ven Innovat ion as a N e w Source
of Gr ow t h, 2013
What's in a name?
Fear of losing reputation through social media is one of the
biggest growing concerns among businesses, according to
Allianz experts. On the 2014 index of Changes in overall risk
perception, fear of losing brand value through digital activity
jumped four spots from 10th to 6th.
Source: Allianz Risk Barometer on Business Risk s , 2014
Decline in Data Storage Costs
The average cost per gigabyte on consumer hard
disk drives has dropped from $56 in 1998 to $0.05
in 2012 – an average decline of almost 40% a year.
Source: OECD, E x ploring D ata- Dri ven Innovation as a
Ne w Source of Grow th, 2013
Growing challenges
A severe data breach is
estimated to cost a US
company $5.4 million
on average, the highest
in the world, according
to Allianz Global
Corporate & Specialty.
US organizations experience
an average of 122 successful
attacks per week, up from
102 per week in 2012.
The average time it takes to solve a cyber-attack
is 32 days. In 2012 it was 24 days.
More than 1 million people worldwide
become victims of cybercrime every day
Source: Ponemon Research Institute:
Cost of Cy ber Crime 2013 Stud y
Cyber-security
Staying safe
Businesses in the United States spend the most
on cybercrime (on average, $8.9 million annually
per business), followed by Germany ($6.0 million).
Cybercrime costs were much lower in Australia
($3.4 million) and the United Kingdom ($3.3 million).
Source: w w w.inf ormationweek .com/at tack s/
c y bercrime- at tack s- cost s- escalating/d/d-id/1106719?
Allianz • 53
Video
Bonus content in
the PROJECT M app
MACRO
CHINA’S CURRENCY
STEPS ONTO THE
WORLD STAGE
China is determined to make its
currency, the renminbi, a major
force in the global market. But the
country’s path to internationalization
has left many foreign investors
unsure of what its next step will be.
54
•
Allianz
A
s China moves increasingly to cement its
role as an international economic power, the
internationalization of its currency, the renminbi
(RMB), plays a key role. Little used as a means of trade and
investment outside China, the RMB is slowly but insistently
promoted by Chinese authorities around the globe.
The use of the RMB outside China has grown steadily
since the project was launched in 2009. But Paola Subacchi,
research director of international economics at Chatham
House, says the development of the RMB into a truly
global currency is held back by the tight grip policy-makers
in Beijing still have on it, by foreign investors’ uncertainty
where the process of internationalization is heading and by
China’s inability so far to assuage doubts about the future
of its monetary policy.
The current two-pronged push to expand foreign use of
the RMB promotes the use of renminbi in cross-border
trade while creating an offshore RMB market. But Subacchi
cautions that this internationalization process is
essentially a temporary measure. “It’s a way to overcome
the lack of convertibility,” she says, “a process to increase
the use of the renminbi while China is preparing the
ground for the renminbi to become a ‘normal’ currency.”
Subacchi views the outward push as “one step in a long
and complex process of developing the currency,” which
fits alongside wider moves to reform interest rates and the
financial sector, and even improve corporate governance.
The center of the expanding RMB offshore market is Hong
Kong, the traditional trade conduit to mainland China,
which currently handles over 60% of China’s foreign direct
investment and more than 80% of all RMB payments.
In 2011, China moved to boost the use of the renminbi in
Europe by choosing London as a second RMB offshore
center, albeit reliant on Hong Kong for its liquidity. The
European market shows great potential, accounting for 47%
of the total value of RMB payments in the first quarter of
2012, more than the entire Asia-Pacific region. But in terms
of investment in RMB-denominated financial products, the
European market is held back by doubts over the currency.
London less keen than Hong Kong
“If you talk to people in Hong Kong,” says Subacchi, “lots of
investors are happy to hold renminbi in their portfolios
because of the proximity to China, because they
understand China and its policies and political dynamics.
But if you talk to people in London, they are considerably
less keen to hold renminbi in their portfolios, because they
see it as a non-convertible currency.”
The government’s control over the renminbi is viewed
by many as a major liability, with the currency potentially
subject to the whims of Beijing policy-makers.
The task of building this necessary trust with Western
investors is “really very difficult,” Subacchi says. “There
isn’t a series of policies they can implement. People need to
trust the government, that the government will apply the
rule of law and not do anything to completely change the
policy or undermine the currency.”
The internationalization of China’s currency marked
another milestone in September, with the launch of the
MACRO
Shanghai Free Trade Zone (FTZ). China’s State Council
declared that the zone would play host to a “pilot and test”
of a convertible renminbi capital account, making the zone
China’s first onshore RMB market center. In the weeks
following the official opening of the FTZ, however, foreign
investors still have only a murky sense of what exactly the
zone is and how Chinese authorities intend to pursue their
stated goals within its boundaries.
Potential of the Shanghai Free Trade Zone
Foreign banks in particular have been hesitant to set up
branches in the Shanghai FTZ. So far, six foreign banks
have applied for and received approval to open branches in
the free trade zone, with others preferring to wait until
more concrete regulations are unveiled.
Subacchi sees little cause for concern in this official
opacity, a standard approach to new and potentially risky
projects that has been seen many times before. “In 2009,
when the pilot scheme for RMB trade settlement was
launched, nobody really knew what it was, and not even the
authorities had a clear idea,” she recalls. “In a very Chinese
fashion, there was a case of moving step by step, ‘crossing
the river by touching the stones,’” explains Subacchi, using
a phrase commonly used to describe Deng Xiaoping’s
cautious approach to introducing China’s first post-Mao
market reforms. “They literally created a policy, tested the
market reaction, and moved on.”
Those familiar with China’s strategy are well aware of
the potential of the Shanghai Free Trade Zone. “There is a
lot of concern in Hong Kong that Shanghai might overtake
them and become the key financial center,” Subacchi notes.
“At the moment, the authorities have been very careful to
reassure Hong Kong that this is not going to happen.”
Given the pivotal position Hong Kong holds in the
offshore RMB market and the ambiguity surrounding
Shanghai’s nascent role, a shift in the balance of power is
unlikely anytime soon. Subacchi stresses, however, that
while the expansion of offshore RMB centers is key to China
becoming a major presence in global financial markets,
Chinese authorities are building a system to last. “We have
to be clear,” she cautions. “Eventually the renminbi will be a
fully conversable currency. Therefore there will be no need
for this kind of construction, and Hong Kong in particular
will be less relevant as an offshore center.”
Similarly, the importance of London and other cities
hand-picked by Chinese officials as RMB trading hubs will
also diminish once control of the currency eventually
leaves the official domain for that of the market. Allianz • 55
MAcro
Inter view
Bonus content in
the PROJECT M app
MAcro
INEQUALITY FOR ALL
Political economist and commentator Robert B. Reich is out to expose the heart
of our economic problems. For over 30 years inequality has been worsening.
R
obert B. Reich dissects the state of the
American economy with his writings
and movies. In an interview with
PROJECT M he delivers a clear message: the gap
between rich and poor needs to close for the
good of society.
The book Aftershock and the film Inequality
for All discuss widening inequality in the
United States. How dramatic is the situation?
Robert Reich: Well, 95% of all the economic
gains since the start of the recovery in 2009
have gone to the top 1%. The rest of America
has shared the remaining 5%. The medium
household income continues to drop, adjusted
for inflation. This means even families with
two wage earners are doing worse than they
did before the recession. In other words, we
haven’t seen this degree of inequality
in a century.
contributed towards widening prosperity in
these ways. In other periods – the 1890s, 1920s
and more recent years – the pendulum swung
in the opposite direction.
unequal recovery
Are you saying that the democratic system
has been corrupted by the rich?
Reich: I am stating it unequivocally! You have
never seen this amount of money in power, at
least in living memory. You have to go back to
the 1890s – when the lackeys of the robber
barons would literally put sacks of money on
the desks of legislators – to find anything
similar. The Supreme Court in 2010, in a
shameful decision called “Citizens United
against the Federal Election Commission,”
opened the floodgates to money and politics. It
is now literally possible to purchase a president
or a governor.
Going back to before the Great Crash of
1929?
Reich: Actually, if you look at wealth as well as
income, we haven’t seen something like that
since the days of the robber barons in
the 1890s.
RO B E R T B . R E I C H
Chancellor’s professor of
Public Policy at the
University of California at
Berkeley. He served in
the administrations of US
Presidents Gerald Ford
and Jimmy Carter and
was secretary of labor
under President Bill
Clinton (1993-1997). He
has written 13 books,
including the best-sellers
Aftershock and The Work
of Nations.
56
•
Allianz
What are the mechanisms whereby society
becomes more equal?
Reich: The times in which the United States
moved towards equality and more widespread
prosperity were periods in which higherquality education was more widely accessible,
when the nation made substantial investments
in infrastructure, the top tax rate was much
higher, financial regulations were stricter, the
right to unionize was observed and companies
were required to bargain in good faith with
unions. And when money did not reach an
overwhelming influence on the political
process. Reforms between 1901 and 1916, 1933
and 1940, and also 1963 and 1969 all
So what makes it swing back?
Reich: Well, when the moneyed interests get a
greater foothold in politics and begin to
entrench themselves, we reach a point where
capitalism goes so far off track that the public
demands changes. In this country those
changes have primarily been in the direction
of reform rather than major political upheavals
towards fascism, socialism or communism.
Our preference, deeply ingrained, is to save
capitalism from itself, from its own excesses.
A
B
Not all Americans
b e n ef i t e q u a l l y f r o m
e c o n o m i c r e c o v e r y.
Si n c e 20 0 9, 95% of
gains have gone to
t h e t o p 1% (A), w h i l e
t h e r e s t of t h e
p o p u l at i o n h a v e h a d
to settle for the
r e m a i n i n g 5% (B).
America is not the only country where
inequality is growing. Australia, Canada,
the United Kingdom and others are
experiencing growing inequality.
Reich: The causes are similar. Among rich
countries, the United States has witnessed the
greatest lurch towards inequality, though others
are close behind. The underlying dynamic has to
do with globalization and technological
displacement of workers. But other nations have
developed political and institutional
Allianz • 57
MACRO
bulwarks against as much inequality as the
United States has. Now, I am not suggesting the
US move towards European-style social
democracies. In my book and movie, I make a
more modest proposal: that the US simply
moves back to the society we had in the 1950s to
early 1970s, when we had institutions and laws
that dramatically reduced inequality and
spread prosperity more widely.
their lives. This is a higher percentage than in
any other rich nation, higher even than the UK
with its history of class consciousness.
Widening inequality would be far less of a
problem if we had ease of upward mobility.
Even though many US citizens have become
poorer, they still cling tightly to the American
Dream. That seems a triumph of fantasy over
reality and is difficult to understand.
Reich: It is quite simple actually. When
Americans are afraid and frustrated, when they
are anxious about their economic status even
though they are working harder than ever, then
they are vulnerable to demagogues on the right
or left who seek scapegoats. Some of the
scapegoating is directed at government, some
at the rich and big corporations, some at
immigrants and the poor, some at labor unions.
In reality, the system has gone awry. The
wealthy would do better with a smaller share of
a rapidly growing economy than they are doing
now with the large share of an economy barely
growing. The reason why the economy has
stopped is that the vast middle class doesn’t
have enough purchasing power to keep it
growing. And the reason it doesn’t have the
purchasing power is that almost all economic
gains are going to the top. Even Bill Gross, head
of PIMCO*, the bond trading firm, in November
(see online article “Scrooge McDucks”) called
upon the wealthy to recognize the dangers from
this kind of inequality.
After the Great Crash of 1929, the GlassSteagall Act was introduced. This is credited
with ensuring stability in the financial
system for decades, so it seems surprising
that there is little agitation to have it
re-introduced.
Reich: As I speak to different community groups,
labor groups, Democratic groups and
occasionally even Republican groups, all I have
to do is just mention Glass-Steagall and I get a
round of applause. This is quite remarkable as,
five or six years ago, no one even knew what
Glass-Steagall was. The Clinton administration
in 1999 made the mistake of joining Republicans
and repealing Glass-Steagall. To ensure Wall
Street won’t melt down once again, we need two
things: not just to resurrect Glass-Steagall, but
also to cap the size of the biggest banks. Unless
we do both, we risk a repeat of 2008.
Your net worth puts you in the top 1%. Does
anyone question your credentials in
speaking for the 99%?
Reich: If you look back in US history, some of our
greatest reformers have been wealthy: Franklin
D. Roosevelt, Teddy Roosevelt, John F. Kennedy –
all were from exceedingly wealthy families.
Warren Buffett is in favor of much higher income
tax on the wealthy. Bill Gates Sr. has led a charge
for closing tax loopholes for the wealthy. There is
no inconsistency in being in the top 1% and at
the same time arguing that the organization of
our economy is out of whack.
In the book The Spirit Level, there is a line that
says, “If you believe in the American dream,
move to Denmark” – because upward
mobility is no longer a feature of US society.
Reich: Well, mobility has slowed considerably.
Some 42% of children born into poverty in the
United States will remain in poverty throughout
* PIMCO is an autonomous subsidiar y of Allianz.
58
•
Allianz
Reich’s work includes
Inequality for All,
which won the Special
Jury Prize at the 2013
Sundance Film Festival.
I n ter v ie w
To listen to an audio
version of the interview,
please go to
projectm-online.com/
leading-thoughts/
inequality-for-all
Do you think equality is recoverable in the
United States?
Reich: We have done it three times over the last
century. It is the matter of political will. The socalled free market doesn’t exist in the state of
nature. The market is based on rules, and those
rules emerge from legislators, courts and
agencies. There is nothing that dictates the
inevitability of widening inequality. If we
wanted to, if our political system was not
engulfed in money, if Americans understood
the problem we face, we would change those
rules towards more widespread prosperity. We
have done it before and we will do it again. The
alternative is an economy that no longer
functions and a democracy incapable of
reflecting the public will. Picture Galler y
Bonus content in
the PROJECT M app
macro
POPULATION AGING
CREATES CAPITAL
REPAYMENT RISK FOR
GOVERNMENT BONDS
Good news for all of us as individuals is now potentially bad news for those
who invest in government bonds. The reason is the dramatic rise
in the percentage of people in the ‘New Old’ 55+ generation.
By Paul Hodges
T
he good news is that life expectancy has increased
by 50% since 1950, to around 70 years. Thus today
there are already 1 billion ‘New Olders,’ compared
with just 300 million in 1950. And the UN Population
Division forecasts they will number 1.8 billion by 2030.
The bad news is that fertility rates have also fallen by
50%, with each woman now having an average of just 2.5
children. Until 2000, the post-World War II baby boom
disguised the problem this created for investors, as the
proportion of New Old in the adult population remained
constant at around one in five. But since then, it has been
rising very rapidly, such that the proportion of New Old will
be almost one in three people by 2030.
“Where’s the problem with this?” you might well
respond. Life expectancy 200 years ago, after all, was only
around 36 years old in the developed world and 24 elsewhere.
And even when Otto von Bismarck and David Lloyd George
introduced the world’s first state pension schemes in 1888
and 1909 respectively, Western life expectancy was less
than 50 years. Yet today, US residents aged 65 still have on
average a quarter of their lives ahead of them.
rethinking pensions
The problem is that our thinking about work and pensions
has not caught yet up with these developments. Bismarck
and Lloyd George saw pensions as being means-tested
social insurance and set pension age at 20 years above life
expectancy. A pension was meant to be a small amount of
money paid to a small number of people for a small period
of time. Thus only 600,000 of the UK’s 40 million population
were initially eligible to receive a pension in 1909.
Lively for much longer: the New-Old adult population
Yet today, pensions are a universal entitlement, with
13 million receiving a UK pension. And instead of pension
age being 20 years above life expectancy (or around 100), it
is instead now below the 1909 level.
Until recently, this paradigm shift created a benign
environment for bond investors, as people realized they
needed to increase their savings and spend less, in order to
finance their unexpectedly long life. They naturally favored
‘safe’ Western government bonds, given stock market
uncertainties. In addition, of course, the shift from
spending to saving helped to reduce inflation and created a
more deflationary environment.
Japan is the obvious model for this shift. Its baby boom
took place earlier than in the rest of the G7, meaning that its
Allianz • 59
macro
the development of a global Aging population
N e w O l d 55 + p o p u l at i o n , & p e r c e nt a g e of a d u l t s
w o r l d w i d e , 195 0 -20 30 (F )
N e w O l d 55 + M i l l i o n s
New Old % of Adults
2,0 0 0
32%
1, 80 0
30
1,60 0
1,40 0
24%
1, 20 0
1,0 0 0
35
22%
21%
25
22%
80 0
20
60 0
40 0
15
20 0
2030 (F)
2020 (F)
2010
20 0 0
1990
1980
1970
1960
10
1950
0
Source: Unite d Nations Population Di v ision
society’s proportion of New Old rose from a benign 20% of
the adult population in 1970 to 32% by 1990, and 47% today.
In turn, its government bond yields fell from 8% in 1990 to
current levels of 1%. Other G7 countries have seen the same
phenomenon in more recent years, as Germany and Italy’s
New Old percentage has risen to 43%, and the US and UK’s to
36%.
» m odern genetics has not yet found a
way of turning 55-year-olds back into
wealth-creating 35-year-olds.
«
By 2030, almost one
in three of the global
population will be
‘New Olders,’
creating problems
for governments
previously in denial.
But this virtuous cycle is now in danger of turning vicious,
as doubts increase about governments’ ability to repay
today’s historically high levels of borrowing when growth
remains anemic at best.
The problem is twofold: first, aging populations
inevitably reduce economic growth. Official data for
household spending confirms the common-sense
conclusion that spending peaks by the age of 55 once the kids
leave home. Older people essentially represent a replacement
economy, as they already own most of what they need, while
their incomes reduce as they approach retirement. And,
given that household consumption is 60% of GDP, this means
the economy will slow as the New-Old percentage rises.
Second, policy-makers ignore this issue at their peril.
They have been too cowardly to propose meaningful
increases in pension age, or even to warn that the
‘demographic dividend’ had turned to ‘demographic
deficit.’ Instead they have tried to restore growth by
following the failed Japanese playbook of major stimulus
spending and massive increases in government debt.
Ignored warnings
They have thus chosen to ignore last year’s warning by
former Bank of Japan governor Masaaki Shirakawa: “most
Japanese people, along with economists, did not grasp the
gravity of population aging coupled with a low birth rate for
Japan’s economy.” China has made the same mistake: its
one-child policy, in force since 1978, will cause its New-Old
population, currently at a moderate 20%, to double by 2030.
Today, therefore, the main question now facing
government bond investors is when to jump ship. They have
profited hugely over the past two decades from the increase
in saving and low inflation rates caused by the rise of the
New-Old generation. But now they face the risk of a ‘Custer’s
Last Stand,’ with policy-makers continuing to believe they
can somehow kick-start growth by adding yet more debt.
Contrary to expectations, this debt will not be inflated
away as in the 1970s. Back then, the rapid rise of the
boomers created a vast increase in demand at a time when
the small interwar generation was totally unable to provide
the necessary supply. But today, the supply-demand
balance is instead moving steadily in the opposite
direction. Rising proportions of New Old inevitably create a
deflationary rather than inflationary environment, as the
various consumer price indices are increasingly
confirming.
Thus the old adage of ‘don’t fight the Fed’ will
progressively face the reality that modern genetics has not
yet found a way of turning 55-year-olds back into wealthcreating 35-year-olds. Western government bonds will
carry increasing capital repayment risk until policymakers finally agree to recognize the true economic
consequences of today’s aging populations. Pau l H o d g e s
Paul Hodges is the chairman of advisory group
International eChem (IeC) and the author of Boom,
Gloom and the New Normal: How the Western
BabyBoomers are Changing Demand Patterns, Again
www.new-normal.com
Allianz • 61
Meta
The out sider’s v iew
THE OLD MAN AND THE Cs
“ W hen did I f ir st k i ss a girl? ” a sk s 102-year- old Lionel Ferbos ,
repeat ing the quest ion. “I don’t k now. There were so many of them .”
C
Name
Lionel Ferbos
Born
17 July 1911
Awa r d s
2003 Big Easy Lifetime
Achievement Award
See the Century Club
interview with Lionel at
www.projectm-online.
com/demographics/
the-old-manand-the-cs
62
•
Allianz
reole singer and trumpeter Lionel
Ferbos is the oldest actively working
musician in New Orleans, the jazz
capital of the world. He first picked up a cornet
at a French Quarter pawn shop at age 15 after
seeing an all-girl band playing horns.
Most Saturday nights he still leads the
band at the packed Palm Court Jazz Cafe, the
venue where he has had a standing booking for
more than two decades. He occasionally has
gigs with younger, renowned musicians, such
as Troy “Trombone Shorty” Andrews, Irvin
Mayfield and Jason Marsalis. He has also
played every year at the New Orleans Jazz &
Heritage Festival since its inception in 1970.
Born on 17 July 1911, Lionel used to make
about a dollar a night in the early 1930s with
bands such as the Starlight Serenaders at
society events and the famed Pelican Club. It
wasn’t much money, but they had a good time.
Back then, Jim Crow still ruled the South.
Black bands could play to white audiences, but
there was no mixing, not even with white
musicians. “But white musicians wanted to
play with us, because we were the best,” recalls
Ferbos. “Segregation, it was absurd.” Lionel is
surprised he’s still alive. “I never thought I
would make it much past 50,” he confides. “I
was a sickly child with asthma.”
Music has been good to Lionel. He played
with the greats of his day, including Captain
John Handy, Walter “Fats” Pichon and blues
singer Mamie Smith. He also performed with
saxophonist Harold Dejan and trumpeters
Herbert Leary and Gene Ware and toured
Europe eight times.
With his dapper clothing style and
crooning voice, Ferbos proved a hit with
women. For a while, he was known as the
“Sheik,” at least until he met Marguerite Gilyot,
who became his wife in the 1930s. She died in
January 2009 after 75 years of marriage. The
pain of his loss is still evident when he talks
about her.
Lionel has had 15 operations in recent
years. He is now cared for by his daughter
Sylvia in a house that was ravaged by
Hurricane Katrina in 2005 and subsequently
rebuilt. When asked about the secret of his
longevity, he replies with a line echoing his
guest appearance on the hit HBO television
series Treme. Looking the interviewer straight
in the eyes he says, “There is a lot to be said for
doing just one thing right.”