Microfinance Services in Indonesia

Transcription

Microfinance Services in Indonesia :
A Survey of Institutions in 6 Provinces
2
TABLE OF CONTENTS
List of Tables
Abbreviations
Forward
4
9
11
I. INTRODUCTION
Background
Research Methodology
Research Sample
13
15
16
18
II. PROFILE OF THE RESEARCH AREAS
Variation between Regions
Available Figures
Conditions of Regencies/Cities
23
25
26
26
III. PROFILE OF MICROFINANCE INSTITUTIONS
Scope of the Financial Institution Sample
Deposits of Surplus Funds
Competition
Marketing
Profitability and Sustainability
33
35
38
40
45
49
IV. SERVICES PROVIDED
Types of Services
Savings and Loans
Geographical Coverage
Target Groups
51
53
54
66
69
V. OPERATIONS, SYSTEMS, AND PROCEDURES OF MFIs
Employees
Systems and Procedures
Internal Supervision
79
81
89
101
VI. RELATIONS WITH OTHER INSTITUTIONS
Types of Institutions
Forms of Cooperation
External Supervision
103
106
109
112
VII. SUMMARY OF FINDINGS
115
APPENDIX
THE DATA : WHAT THEY REPRESENT AND THEIR LIMITATIONS
Research Design
Limitations to Reports from Government Officials
Limitations in the MFI Survey Data
| Microfinance Services in Indonesia | INTRODUCTION
125
127
127
134
3
LIST OF TABLES
TABLE
NO
4
TITLE
1-1
Research Locations
1-2a
Numbers of Bank and Non-Bank Respondents
by Regency / City in West Java and East Java
1-2b
Numbers of Bank and Non-Bank Respondents
by Regency / City in West Kalimantan and East Kalimantan
1-2c
Numbers of Bank and Non-Bank Respondent
by Regency / City in North Sulawesi and Papua
2-1
Background Data on Research Locations, 2001 / 2002
2-2
Values of Deposits and Loans of Bank and BPRs
in Research Locations, 2002 (Billion Rupiah)
2-3
Economic and Social Indicators in Research Locations, 2001 / 2002
2-4
Numbers of Financial Institutions
(Bank and Non-Bank) in Sample by Regency/City, 2002
3-1
Value of Loans from Commercial Banks (Including BRI Village Unit)
by Research Location, 2002 (Billion Rupiah)
3-2
Places of Deposit for Surplus Funds Mentioned by Non-Bank MFIs
by Type of Institution (%)
3-3
Places of Deposit for Surplus Funds Mentioned by Non-Bank MFIs
by Regency / City (%)
3-4a
Institutions Mentioned by Non-Bank MFIs as Competitors in Granting
Loans, by Type of Institution and Location (%)
3-4b
Institutions Mentioned by Bank MFIs as Competitors in Granting
Loans, by Type of Institution and Location (%)
3-5a
Institutions Mentioned by Non-Bank MFIs as Competitor in
Mobilizing Deposits by Type of Institution and Location (%)
3-5b
Institutions Mentioned by Bank MFIs as Competitors in
Mobilizing Deposits, by Type of Institution and Location (%)
3-6
Marketing Methods Mentioned by Non-Bank MFIs for Saving and for
Loans by Type of Institution (%)
3-7
Non-Bank MFIs Stating Potential Exists for Saving by Regency / City (%)
3-8
Non-Bank MFIs Stating Potential Exists for Loans by Regency / City (%)
TABLE
NO
3-9
TITLE
Financial Performance Ratios of the Sample Banks, 2000-2002
3- 10
Ratio of Profit / Loss to Credit Portfolio of Non-Bank MFIs
by Type of Institution, 2000-2002 (%)
4-1a
Number of Accounts and Value of Deposits and Loans at
Bank MFIs by Type of Bank, May 2002
4-1b
Number of Accounts and Value of Deposits and Loans at
Non-Bank MFIs by Type of Institution, May 2002
4-2
Number of Accounts and Value of Deposits and Loans in
Non-Bank MFIs by Regency/City, May 2002
4-3a
Banks MFI and Group Lending, by Type of Bank
4-3b
Types of Customers of Non-Banks MFIs by Type of Institution (%)
4-4a
Minimum, Maximum, and Median Values of Annualized Bank Saving
Interest Rates and Cost of Funds by Type of Bank (%)
4-4b
Minimum, Maximum, and Median Values of Annualized
Non-Bank MFI Savings Interest Rates and Cost of Funds by
Type of Institution (%)
4-5
Interest Rates for Bank Micro Loans by Type of Loan and
Type of Bank (%)
4-6
Interest Rates for Non-Bank MFIs Micro Loans by Type of
Loans and Type of Institution (%)
4-7
Minimum, Maximum, Values of Annualized Interest
Rates of Non-Bank MFIs by Type of Loan and Region (%)
4-8a
Non-Bank MFIs that Specify Requirements for Loans by
4-8b
Bank MFIs that Specify Requirements for Loans by
Type of Bank (%)
4-9
Median Savings Interest Rates, Loan Interest Rates, and Net Interest
Margins of Bank and Non-Bank MFIs by Type of Bank and Institution (%)
4-10a
Repayment Rate of Micro Loans at Bank MFIs by
Type of Bank and Region (%)
4-10b
Repayment Rate of Micro Loans at Non-Bank MFIs by
Type of Institution and Region (%)
4-11
Distribution of Non-Bank MFIs by Operational Area (%)
4-12
Non-Bank MFIs Target Group by Regency / City (%)
5
TABLE
NO
6
TITLE
4-13
Outstanding Loans and Accounts held by Women by Type of MFI (%)
4-14a
Bank MFIs Mentioning Advantages of Female Customers over Males (%)
4-14b
Non-Bank MFIs Mentioning Advantages
of Female Customers over Males (%)
4-15a
Non-Bank MFI Market Segments by
Type of Institution and Location (%)
4-15b
Bank MFIs Market Segments by Type of Bank and Location (%)
4-16a
Micro Loans Accounts from Non-Bank MFIs
by Economic Sector (%)
4-16b
Micro Loans Accounts from Bank MFIs by Economic Sector (%)
5-1
Average Number of Employees of Sample Banks by
Type of Bank and Location
5-2
Average Number of Bank Employees Involved with Micro Loans by
Type of Bank and Location
5-3
Time Allocated to Micro Loans by Bank AOs Who Perform Other Duties,
by Type of Bank (%)
5-4
Average Number of Non-Bank MFIs Employees by
Type of Institution and Location
5-5
Average Number of Non-Bank MFIs Employees Involved
with Micro Loans by Type of Institutions and Location
5-6
Time Allocated to Micro Loans by Non-Bank MFIs AOs
Who Perform Other Duties by Type of Institution (%)
5-7
Bank MFIs Stating Training is Adequate,
by Type of Bank and Location (%)
5-8
Bank MFIs that Provide Training Budget,
by Type of Bank and Location (%)
5-9
Non-Bank MFIs Whose Staff Receive Training,
by Type of Institution and Location (%)
5-10
Non-Bank MFIs Stating Training is Adequate,
5-11
Non-Bank MFIs that Pay for Staff Training Themselves,
5-12
MFIs Stating They Provide Incentives for Staff
by Type of Bank and Type of Institution (%)
TABLE
NO
TITLE
5-13
Bank MFIs Using Computers by Level of Use and Type of Bank (%)
5-14
Non-Bank MFIs Using Computers by Level of Use and
5-15
Non-Bank MFIs Using Certain Financial Records by
5-16
Cooperatives whose Management and Supervision Are Separate,
by Regency / City (%)
5-17
Non-Bank MFIs that State They Have Certain Manuals by
5-18
MFIs Stating Certain Requirements for Loans by
Type of Bank and Type of Institution (%)
5-19a
Bank MFIs that Require Certain Guarantees by
Type of Bank (%)
5-19b
Non-Bank MFIs that Require Certain Guarantees by
5-20
Minimum Age of Business Requirements by
Type of Bank and Type of Institutions (%)
5-21a
Factors Given for Rejecting Loan Applications by Type of Bank (%)
5-21b
Factors Given for Rejecting Loan Applications by
Non-Bank MFIs by Regency / City (%)
5-22a
Bank MFIs Methods of Handling Bad Loans by Type of Bank (%)
5-22b
Non-Bank MFIs Methods of Handling
Bad Loans by Regency / City (%)
5-23
Non-Bank MFIs Regularly Performing
Internal Supervision by Type of Institution (%)
6-1
BPR (Rural Bank) that Cooperated with
Certain Institution by Location (%)
6-2
Non-Bank MFIs that Cooperated with Certain Institution
6-3
BPRs in Various Forms of Cooperation with
Other Institutions by Location (%)
6-4
Non-Banks MFIs in Various Forms of Cooperation
with Other Institution by Type of Institutions and Location (%)
6-5
Non-Bank MFIs Producing Various Types of Report,
by Type of Institution (%)
7
TABLE
NO
8
TITLE
6-6
Non-Bank MFIs that Mention Certain Parties as Providers
of External Supervision, by Type of Institution (%)
6-7
Non-Bank MFIs that are Supervised, by
Frequency of External Supervision and Type of Institution
7-1
Bank Deposits and Credits by Regency/City, 2002
7-2
Values of Credit and Deposits of Non-Banks MFIs in the Survey, 2002
i
Comparison of Numbers of MFIs According to
Reports of District Officials and Number in the Sample, 2002
ii
Numbers of Micro Finance Institutions That Served as
the Sample by Type of Institution and Province, 2002
iii
Overview of Proportion of Numbers of Research
Regions Compared with Numbers of Regions in
Indonesia and in the Unit Sample, January 2002
iv
Comparison of Actual Amounts in the Sample and Hypothetical Amounts
of Loans of Non-Bank MFIs, by Regency/City
ABBREVIATIONS
BI
Bank Indonesia (Central Bank of Indonesia)
BKD
Badan Kredit Desa (Village Credit Board)
BKK
Badan Kredit Kecamatan (Sub-district Credit Board)
BPD
Bank Pembangunan Daerah (Regional Development Bank)
BPR
Bank Perkreditan Rakyat (People’s Credit Bank)
BPR-LDKP
LDKP converted to BPR status
BRI
Bank Rakyat Indonesia
BRI Unit (Desa) BRI (Village) Unit
BMT
Baitul Maal Wat Tamwil (MFI Operate under Islamic principles)
BKKBN
Badan Koordinasi Keluarga Berencana Nasional (National Family
Planning Coordination Agency)
BPKP
Bukti Pemilikan Kendaraan Bermotor (Vehicle owner-ship books)
CU
Credit Union
Depdagri
Departemen Dalam Negri (Ministry of Home Affairs)
GRDP
Gross Regional Domestic Product
IDT
Inpres Desa Tertinggal (Presidential Instruction on Backward Villages)
KSP
Koperasi Simpan Pinjam (Saving and Loan Cooperative)
KUD
Koperasi Village Unit (Village Unit Cooperative)
KUT
Kredit Usaha Tani (Farmer Credit Program)
LDKP
Lembaga Dana Kredit Pedesaan
(Rural Fund and Credit Institution)
LEPMM
Lembaga Ekonomi Produktif Masyarakat Mandiri
(Self-Reliant Community Productive Economic Industries)
MFI
Microfinance Institution
NGO
Non government organization
OJK
Otoritas Jasa Keuangan (Financial Services Authority)
PHBK
Proyek Hubungan Bank dengan Kelompok Swadaya Masyarakat
(Project Linking Banks and Self-Help Groups)
P2KP
Proyek Penanggulangan Kemiskinan di Perkotaan
(Poverty Alleviation Project in Urban Areas)
PDMDKE
Pemberdayaan Daerah dalam Mengatasi Dampak Krisis Ekonomi
(Local Empowerment by Overcoming the Impact of the Economic Crisis)
PPK
Program Pengembangan Kecamatan (Sub-district Development Program)
PKM
Pengembangan Keuangan Mikro (Micro Finance Development)
PUSKOPIT
Pusat Koperasi Kredit (Center of Credit Cooperative)
SKPG
Surat Keterangan Pemotongan Gaji
TPSP
Tempat Pelayanan Simpan Pinjam (Savings and Credit Service Post)
UED-SP
Usaha Ekonomi Desa - Simpan Pinjam
(Salary Deduction Authorization Letter)
(Village Economic Unit-Saving and Credit)
USP
Unit Simpan Pinjam (Savings and Credit Unit of Cooperative)
9
FOREWORD
In Indonesia, where more than 90% of all businesses are micro and small enterprises, the question of how to encourage growth and job creation is a vital one in
reducing vulnerability to poverty. Micro and small business owners frequently comment that capital constraints limit their ability to grow. Indeed, very few
small businesses obtain credit from formal sources. Extending credit to these
enterprises is a challenging task. Small businesses suffer from high turnover, low
levels of formalization, and borrow relatively small amounts that are expensive
for financial institutions to service. This makes them unattractive to many private
commercial lenders, few of whom target small borrowers. Instead, most small business borrowers in Indonesia obtain credit from a variety of microfinance institutions (MFIs).
Indonesia has developed a vibrant microfinance market, with 30 trillion rupiah
in outstanding loans in 2002. While microfinance is often considered a way of extending financial services to the very poor, MFIs in Indonesia tend to concentrate
instead on consumer credits and working capital for small businesses, particularly
in the trade and service sectors. Indonesian MFIs, such as Bank Rakyat Indonesia,
are internationally recognized for their achievements in extending microcredit on
a commercial basis. These financial markets are well developed on Java and Bali
with a number of government and private lenders competing for the market. Less
is known regarding the coverage and capacity of MFIs outside of Java and Bali and
the research presented here attempts to fill this gap. The Asia Foundation surveyed
nearly 400 MFIs in East and West Java, East and West Kalimantan, North Sulawesi,
and Papua to examine the number, coverage, and capacity of MFIs in these provinces. While the sample is not representative, we hope that it will enrich the debate
on credit services in Indonesia.
It is important not to overstate access to finance as a barrier to SME growth.
Numerous studies by the Foundation and others have found that risk-averse small
business owners often prefer to ask family and business partners for loans rather
than approaching formal lending institutions. Nonetheless, a properly functioning
financial system, capable of extending loans to credit-worthy small business, is an
important part of a conducive business environment. The Asia Foundation’s work
on microcredit is part of its broader effort to support the small business sector to
contribute to job creation and growth.
The Foundation expresses its gratitude to Edy Priyono and the team at Akademika
for their work in analyzing the data presented here and to Dr. Thomas Timberg,
Ms. Agustina Musa, Ms. Wida Johnston, and Mr. Sapprudin for assistance to this
project. This work was made possible with the generous support of the United
States Agency for International Development.
Douglas E. Ramage PhD. – Representative, The Asia Foundation, Indonesia.
Erin Thébault Weiser – Director, Economic Programs, The Asia Foundation, Indonesia.
Siswa Rizali – Program Officer, Economic Programs, The Asia Foundation, Indonesia
11
I. INTRODUCTION
13
BACKGROUND
The Asia Foundation has cooperated with the Center for Business and Government of Harvard University (CBG-Harvard), which works for Bank Rakyat Indonesia, to conduct a survey on access to and services of micro finance institutions
(MFIs) in six provinces: West Java, East Java, West Kalimantan, East Kalimantan,
North Sulawesi and Papua. The Asia Foundation conducted the survey of institutions, consisting of banks and non-bank financial institutions, while the survey of
households was done by CBG-Harvard. Data collection was performed in 2002 and
included 374 MFIs and 1,438 households. This publication covers data related to
the survey of institutions.
Generally, the survey was aimed at looking at the availability of micro finance
services. Specifically, the aims of the survey were:
1. To evaluate the capabilities of MFIs in several regions of Indonesia. For this
purpose, an MFI was defined as an institution (bank or non-bank) that provides loans with a ceiling of Rp 50 million per customer. The meaning of
capability here includes efficiency, sustainability, and ability to develop its
service network.
2. To evaluate the market penetration of MFIs in terms of the gap between
supply and demand, geographical coverage, societal levels, gender, and economic sectors.
3. To evaluate the possibility and capability of MFIs to develop linkages with
larger financial institutions.
4. To identify the problems faced by MFIs, though not to make recommendations to remedy them.
15
RESEARCH METHODOLOGY
Research Locations
The research was done in six provinces, West Java, East Java, West Kalimantan,
North Sulawesi, and Papua, which were chosen on the basis of a comparative analysis of several regions in Indonesia but were not intended to portray average conditions in Indonesia as a whole.
1. Selection of the Sample Locations
• On the basis of data1 obtained from the Central Statistics Bureau (BPS), two
regencies or cities were chosen in each province, based on criteria reflecting
the characteristics of the province. These characteristics reflected the rural
and urban nature and level of family welfare in the province being studied.
• From each of these regencies and cities, three districts were chosen at random, and the combined characteristics of these districts were then compared
with the characteristics of the province.2
• Finally, from each of these districts, two villages or urban subdistricts were
chosen at random, and again reexamined.
2. Research Locations Chosen
Table 1-1 shows the locations of the regencies/cities, districts, and villages/
subdistricts chosen through the steps of sample selection described above.
1 These data were descriptive data from the BPS, focusing primarily on percentages of residents living in rural areas and in cities according to the 2000 national
census, as well as on the percentages of poor residents per regency, city, district, and village/subdistrict as measured against a nationwide scale of public prosperity.
Because accurate estimates of the level of poverty based on the BPS poverty line at administrative levels lower than provinces were not available, the BPS poverty line
could not be used as a criterion for further examination of the selected sample locations.
16
2 In several cases, villages or districts with extreme characteristics were not selected and were randomly replaced so that the sample would better approach or
represent the characteristics of the province being studied.
Table 1-1 Research Locations
Province
West Java
East Java
West Kalimantan
East Kalimantan
North Sulawesi
Papua
Regency (kab.)/
City (kota)
District
Village/Subdistrict
Kab. Bandung
Cililin
Cimaung
Cimahi Tengah
1. Situwangi
1. Pasirhuni
1. Baros
2.Kidang Pananjung
2. Sukamaju
2. Karang Mekar
Kab. Purwakarta
Bojong
Purwakarta
Darangdan
1. Cileunca
1. Babakan Cikao
1. Sirnamanah
2. Pasanggrahan
2. Nagri Kaler
2. Linggamukti
Kota Madiun
Manguharjo
Kartoharjo
Taman
1. Nambangan Lor
1. Klegen
1. Kejuron
2. Sogaten
2. Kanigor
2. Mojorejo
Kab. Malang
Pagak
1. Pandanrejo
2. Pagak
Dampit
1. Bumirejo
2. Pojok
Wajak
1. Dadapan
2. Kidangbang
Kota Pontianak
Pontianak Barat
Pontianak Utara
Pontianak Timur
1. Pal Lima
1. Siantan Hilir
1. Tanjung Hilir
2. Mariana
2. Siantan Tengah
2. Saigon
Kab. Sanggau
Sekayam
Toba
Kembayan
1. Sotok
1. Lumut
1. Sejuah
2. Kenaman
2. Belungai Dalam
2. Tunggal Bhakti
Kota Samarinda
Samarinda Ulu
Samarinda Ilir
Samarinda Utara
1. Teluk Lirong Ilir
1. Pulau Atas
1. Lempake
2. Gunung Kelua
2. Sambutan
2. Sungai Siring
Kab. Kutai
Kertanegara
Tenggarong
Seberang
Kotabangun
Muara Muntai
1. Perjiwa
2. Embalut
1. Kedang Ipil
1. Muara M. Ulu
2. Kotabangun Ulu
2. Muara Leka
Kota Manado
Malalayang
Wanea
Mapanget
1. Malalayang I
1. Karombasam
1. Buha
2. Kleak
2. Wanea
2. Paniki Bawah
Kab. Minahasa
Pineleng
Tompaso Baru
Belang
1. Kalasey I
1. Lowian
1. Soyowan
2. Kalasey II
2. Temboan
2. Watuliney
Kota Jayapura
Abepura
Jayapura Selatan
Jayapura Utara
1. Nafri
1. Entrop
1. Tanjung Ria
2. Asano
2. Hamadi
2. Angkasa Pura
Kab. Manokwari
Babo
Ransiki
Prafi
1. Simuri
1. Iseren
1. Waseki
2. Rarutu III
2. Dembek
2. Waseki Indah
17
RESEARCH SAMPLE
1. Survey Population
The targets or respondents in this study can be grouped into three categories:
a. Banking financial institutions identified as probably providing micro loans
directly for business purposes (direct business microlending). The banks
that served as respondents were government banks and private banks that
might provide micro loans for working capital and that have a national network of branches.3 For practical reasons and to ease comparison, the same
banks were interviewed as respondents: Bank Mandiri, Bank BNI, Bank BRI
(both branch offices and Village Units), Bank BCA, Bank Danamon, and Bank
Bukopin. In addition to these, branch offices of Regional Development Banks
(Bank Pembangunan Daerah, BPD) and several local Public Credit Banks
(Bank Perkreditan Rakyat, BPR) also served as research samples.
b. Non-bank financial institutions that provide micro loans for working capital.
Included in this category are Islamic credit unions (Baitul Maal wa Tamwil¸
BMT), Savings and Loan Cooperatives (Koperasi Simpan-Pinjam, KSP), Credit Unions, Savings and Loan Units/ Savings and Loan Facilities (Unit Simpan-Pinjam/ Tempat Pelayanan Simpan-Pinjam, USP/TPSP), Micro Finance
Institutions/ MFI (Lembaga Keuangan Mikro, LKM), and others (such as Village Credit Agencies (Badan Kredit Desa, BKD), Common People’s Business
Credit Institutions (Lembaga Kredit Usaha Rakyat Kecil, LKURK)4, etc.).
The USP/TPSP mentioned above are the savings and loan units of Village
Unit Cooperatives (Koperasi Village Unit, KUD), Employee Cooperatives
(Koperasi Karyawan, Kopkar), Women’s Cooperatives (Koperasi Wanita, Kopwan), Multi-Purpose Enterprise Cooperatives (Koperasi Serba Usaha, KSU),
and Farmers’ Cooperatives (Koperasi Petani, Koptani). A separate category
was created for the Kopkar (rather than including them in the USP category)
because of their special characteristics that distinguish them from business
cooperatives in general, in order to prevent a significant bias.
18
3 In practice, there were almost no local commercial general banks identified as possibly being involved in providing
micro finance services, though there are some that do provide micro finance services in other regions, especially in Bali.
4 According to the Law on Banking, BKD and LKURK are in fact included in the bank category, but in practice it would be
more appropriate to refer to them as “prospective BPRs”, and so in this study they were placed in the non-bank category
(See: Detlev Holloh, 2001. Microfinance Institution Study. GTZ-Bank of Indonesia-Ministry of Finance).
The MFIs mentioned above are informal community groups that conduct
savings and loan activities, or only provide loans, for the needs of their
own members.
c. Government agencies related to or playing a role in development, whether of financial institutions or of micro, small, and medium-scale enterprises. These respondents included local Bank Indonesia Offices, Offices of the
Cooperatives and SME Service, Industry and Trade Service Offices, the Economic Sections of regional governments at the provincial and regency/city levels,
Provincial/ Regency/ City Development Planning Agencies (Badan Perencana
Pembangunan Propinsi/ Kabupaten/ Kota, Bappeprop/ Bappekab/ Bappeko),
District (Kecamatan) Offices, and Village/ Subdistrict Heads.
2. Stages of Sample Collection
The collection of the sample of financial institutions for this survey was done
in two stages, as follows:
Stage I :
Identifying the types of financial institutions present in the
research location. This was done by seeking data on the types and numbers
of financial institutions, both banks (especially BPRs) and non-banks. Data
on types and numbers of banks were obtained from the local Bank Indonesia
offices, or those whose operational areas covered the research regions/locations. Data on numbers and types of cooperatives (including some BMTs and
MFIs), were obtained from the Cooperative and SME Service offices at the
regency/city level. Aside from these official sources, the researchers also
obtained data and carried out inspections in the field.
Stage II : Determining the quotas for each type of financial institution to
be studied. From the research population described above, we determined
a quota for each type of financial institution that was to serve as a research
respondent. The determination of these quotas was based on considerations
including the following:
19
• To try to obtain as many respondents as possible from all types of financial institutions found in the research locations, both bank and non-bank,
so as to be able to represent the characteristics of each type of financial
institution.
• The methodology had to be able to accommodate the limitations of time
allowed for the research and of other resources.
Based on these aspects, the quotas determined were as follows:
• For banking financial institutions:
Because the number of banks was lower than that of non-bank financial
institutions, the ones chosen as respondents were all branch offices of
the government banks (including BRI Units) and private banks that were
mentioned above, plus three to four BPR offices in each research location. If there were more than four BPRs in a given research location, the
respondents were chosen at random.
• For non-bank financial institutions:
The overall number of non-bank financial institutions was far greater
than that of banks, and often the data on types and numbers of these
institutions were not very accurate. The quotas were determined in the
following way: three to four offices per type of non-bank financial institution present in the regency capital or city; two to three offices per type of
such institution located in the districts; and two to three offices per type
of such institution located in the research location villages/subdistricts.
The selection of these samples was also done randomly. In several cases, when
there were one or two types of non-bank financial institution that were not
present in a given research location, the proportion of respondents of the other
types in that research location was increased.
20
3. Sample Size
Altogether, in this study 374 microfinance institutions were interviewed, consisting of 114 bank microfinance institutions and 260 non-bank microfinance
institutions. Looking at the distribution of the financial institutions sampled in
this research, the largest samples were found in West Java and East Java: 83 and
81 financial institutions, respectively. The smallest sample was found in West
Kalimantan: only 34 microfinance institutions, comprised of 17 banks and 17
non-bank institutions. The entire research sample of financial institutions, both
banks and non-banks, for the various provinces is shown in Tables 1-2a, 1-2b
and 1-2c below.
Table 1-2a. Numbers of Bank and Non-Bank Respondents by
Regency/City in West Java and East Java
Type of Institution
West Java
BANDUNG
East Java
PURWAKARTA
Total
MALANG
MADIUN
Total
BANK
Government banks
BPD
Private banks
BPR
BRI UNIT
TOTAL BANK
2
1
.
7
3
13
2
1
1
2
6
12
4
2
1
9
9
25
3
1
2
6
3
15
3
1
1
2
3
10
6
2
3
8
6
25
NON BANK
BMT
KOPKAR
KSP
Other MFIs
PROGRAMs
USP
TOTAL NON-BANK
5
4
3
.
7
9
28
3
2
3
2
2
18
30
8
6
6
2
9
27
58
.
3
5
1
.
9
18
2
2
18
.
1
15
38
2
5
23
1
1
24
56
41
42
83
33
48
81
TOTAL ALL
21
Table 1-2b. Numbers of Bank and Non-Bank Respondents by
Regency/City in West Kalimantan and East Kalimantan
Type of Institution
West Kalimantan
East Kalimantan
SANGGAU
PONTIANAK
BANK
Government banks
BPD
Private banks
BPR
BRI UNIT
TOTAL BANK
2
2
.
.
1
5
4
1
3
2
2
12
6
3
3
2
3
17
1
2
.
1
2
6
3
1
2
.
3
9
4
3
2
1
5
15
NON BANK
BMT
KOPKAR
KSP
Other MFIs
PROGRAMs
USP
TOTAL NON-BANK
1
.
5
.
.
2
8
5
.
2
2
.
.
9
6
.
7
2
.
2
17
1
4
5
1
2
4
17
5
1
4
3
.
8
21
6
5
9
4
2
12
38
13
21
34
23
30
53
TOTAL ALL
Total
KUTAI
SAMARINDA
Total
Table 1-2c. Numbers of Bank and Non-Bank Respondents by
Regency/City in North Sulawesi and Papua
Type of Institution
22
North Sulawesi
MINAHASA
PAPUA
MANADO
Total
MANOKWARI
JAYAPURA
Total
BANK
Government banks
BPD
Private banks
BPR
BRI UNIT
TOTAL BANK
1
.
.
2
2
5
3
.
1
.
3
7
4
.
1
2
5
12
3
2
1
.
3
9
3
1
1
2
4
11
6
3
2
2
7
20
NON BANK
BMT
KOPKAR
KSP
Other MFIs
PROGRAM
USP
TOTAL NON-BANK
.
.
7
20
1
5
33
2
1
4
22
1
6
36
2
1
11
42
2
11
69
.
.
3
2
.
9
14
.
2
2
1
.
3
8
.
2
5
3
.
12
22
TOTAL ALL
38
43
81
23
19
42
II. PROFILE OF THE
RESEARCH AREAS
23
| Microfinance Services in Indonesia
| PROFILE OF THE RESEARCH AREAS
In this section, brief profiles of the research areas are presented, particularly in
terms of demography, social and economic aspects, and commercial activity. The
data are presented in Tables 2-1 through 2-4. The profiles are presented at two levels: the provincial level and the regency/city level. This information is intended
provide a context for the later discussion.
VARIATION BETWEEN REGIONS
It is evident from the available data that the regencies/cities that served as the
research locations differ widely in terms of numbers of residents and levels of
development. The regency with the largest population has more than two million
people, while most of the other regions have fewer than 600,000 people. Physically, too, the research areas differ; very few urban regions were selected for this
study, but the regencies, of a more rural nature, differed in terms of area and of
population density. The factors of area and population density strongly affect the
costs of financial institutions, as well as the transportation costs of businesses. It is
therefore not surprising that very clear differences were found between research
areas in terms of economic level, quality of infrastructure, educational levels, and
levels of community incomes. All of these factors have a strong impact on the market for financial services, and especially on their ability to achieve a certain level of
economic viability. Thus it is no coincidence that the regions in Java and the urban
areas with higher population densities show a greater degree of development of
microfinance institutions. Of course, the regencies have varying economic levels: several of them are agricultural areas (though in fact not very many), while
other regions are dominated by natural resource extraction industries (oil, gas, and
mining), and several of the urban regions serve as administrative and service
centers for the surrounding areas and have little industry.
As it happens, the sample of microfinance institutions in this study is evenly
distributed, and so there is a tendency toward an excess of samples in smaller and
less-developed regions.
25
AVAILABE FIGURES
The figures presented in this section come from official sources and have varying
levels of reliability. The data on populations and areas are very sound. The data
on educational levels are nearly as good as the data on populations and areas. The
data on GRDP of regencies/cities are generally recognized as having some weaknesses, but are used nevertheless because no alternative data are available. The data
on length of road networks are somewhat more complex in terms of data quality,
because of differences in quality and differing definitions about roads. The use of
water transport in island regions also affects the relevance of these data.
The issue of data accuracy also applies for bank loans, which often include a large
number of companies, such that they do not reflect accumulation among local
residents. In reality, the issue of where GRDP and loans are recorded is essentially
a matter of ease for a number of large companies.
CONDITIONS OF REGENCIES/CITIES
East Java is a very large province, covering most of the eastern part of the island of
Java. Together, East Java and West Java contain nearly a third of Indonesia’s entire
population (Table 2.1). The two regencies/cities selected as research areas in this
province have only a small population compared with East Java’s total population.
Malang and Madiun are both located near the center of the province of East Java.
Both regions have a high level of financial development, which is on the whole a
characteristic of regions in East Java.
26
Table 2-1 Background Data on Research Locations, 2001/2002
PROVINCE/
REGENCY/CITY
West Java
AREA
Population
Population
Density
(KM2)
(Million)
(PER KM2)
GRDP
GRDP/
CAPITA
(Million Rupiah)
Number of Jurisdictions
Regencies/
Cities
Districts
Villages/
Subdistricts
30,517
36.9
1,210
187,090,585
5.07
24
545
5,758
2,452
4.3
1,768
17,314,502
3.99
1
43
436
723
0.7
1,002
5,226,905
7.21
1
17
192
37,578
35.1
935
195,443,880
5.59
38
641
8,465
Malang
2,865
2.4
852
8,987,437
3.68
1
33
388
Madiun
33
0.2
4,883
788,417
4.85
1
3
27
120,488
4.2
35
19,737,236
4.74
10
134
1,439
Bandung
Purwakarta
East Java
West Kalimantan
Pontianak
110
0.5
4,380
4,849,839
10.04
1
4
23
18,276
0.6
32
2,232,811
3.79
1
22
241
211,440
2.6
11
86,242,138
33.61
13
101
1,299
2,101
0.5
259
6,606,119
12.15
1
6
42
Kutai
10,875
0.4
41
20,182,111
45.34
1
18
195
North Sulawesi
15,027
2.0
136
11,720,046
4.98
6
94
1,196
198
0.4
1,960
2,374,328
6.12
1
9
87
4,397
0.8
183
3,454,183
4.30
1
38
527
287,242
2.2
8
23,877,110
10.75
14
181
3,507
Sanggau
East Kalimantan
Samarinda
Manado
Minahasa
Papua
Jayapura
Manokwari
Indonesia
433
0.2
407
1,096,092
6.21
1
4
31
23,155
0.2
9
878,664
4.08
1
17
569
1,472,014
203.4
138
1,433,970,000
7.05
376
4,838
68,816
Source: BPS and Edi Sigar (2003), Buku Pintar Indonesia ( Indonesian Almanac)
Note: Data on Gross Regional Domestic Product (GRDP) are for 2001, while data on Indonesia’s population are for 2002.
Figures for population have been rounded.
27
Table 2-2 Values of Deposits and Loans of Banks and BPRs in Research Locations, 2002 (Billion Rupiah)
Province/Regency/City
Bank Deposits
Bank Loans
Small Loans
BPR Loans 2
West Java
80,182
71,645
11,988
1,048
895
Bandung
1,900
5,807
107
N/A
N/A
Purwakarta
614
5,530
388
N/A
N/A
East Java
78,827
34,022
10,398
836
990
Malang
7,296
3,025
1,555
N/A
N/A
Madiun
1,395
435
193
N/A
N/A
6,357
2,822
793
38
34
4,390
1,280
433
N/A
N/A
196
374
92
N/A
N/A
11,825
5,094
1,004
11
14
4,870
1,647
368
N/A
N/A
N/A
627
N/A
N/A
N/A
3,642
2,641
1,411
26
42
2,590
1,146
N/A
N/A
N/A
West Kalimantan
Pontianak
Sanggau
East Kalimantan
Samarinda
Kutai Kutainagara
North Sulawesi
Manado
Minahasa
Papua
Jayapura
Manokwari
Total Regencies
N/A
502
N/A
N/A
N/A
4,455
657
434
N/A
N/A
N/A
196
164
N/A
N/A
N/A
73
43
N/A
N/A
23,251
20,642
3,343
N/A
N/A
Source : Bank Indonesia
Note: N/A: No data Available
All data are for April 2002, except for West Kalimantan, January 2002
28
BPR Deposits
Table 2-3 Economic and Social Indicators in Research Locations 2001/2002
Regencies
Contribution
of Agric
ultural Sector
to GRDP (%)
Contribution
of Industrial
Sector to
GDRP (%)
Contribution
of Trade, Hotel
and Restaurant
Sector to
GRDP(%)
Population
Elementary
School
Graduates or
Lower (%)
Population
Junior/Senior
High School
Graduates (%)
Population
Diploma
Holders or
Higher (%)
Population
Aged 15/
Older
Road
Coverage
(KM)
West Java
Bandung
8.3
56.6
16.8
68.1
28.0
3.9
2,982,593
654,301
10.6
45.9
25.0
76.9
21.3
1.8
504,145
730,712
Malang
34.0
15.0
22.9
76.5
21.1
2.4
1,793,441
64,025
Madiun
2.5
27.8
19.2
46.5
43.8
9.7
126,308
82,250
Purwakarta
East Java
West Kalimantan
Pontianak
0.6
4.3
21.1
55.8
34.0
10.2
347,022
742,670
Sanggau
39.7
27.8
17.1
78.9
20.5
0.7
405,112
13,373
East Kalimantan
Samarinda
Kutai K.
2.4
31.9
29.4
54.1
37.1
8.8
383,877
78,265
10.8
2.5
3.1
67.6
28.8
3.6
303,278
90,855
3.3
7.1
26.3
38.6
49.1
12.3
298,594
560,345
32.0
7.8
10.5
61.4
34.7
3.9
599,831
23,075
9.1
6.8
13.9
43.2
46.6
10.2
118,732
N/A
57.0
6.7
7.0
83.8
14.5
1.7
129,456
18,061
North Sulawesi
Manado
Minahasa
Papua
Jayapura
Manokwari
Source : BPS
Note: Data on Gross Regional Domestic Product (GRDP) are for 2001, while data on Indonesia’s population are 2002
29
Table 2-4 Numbers of Financial Institutions (Bank and Non-Bank) in Sample by Regency/City, 2002
T
Sample Data
Province/
Regency/City
Banks
National Banks
Non-BRI Unit
BRI Unit
Total
Banks
BPR
Non
Banks
West Java
Bandung
3
3
7
13
28
Purwakarta
4
6
2
12
30
Malang
6
3
6
15
18
Madiun
5
3
2
10
38
Pontianak
8
2
2
12
9
Sanggau
4
1
0
5
8
Samarinda
6
3
0
9
21
Kutai K.
3
2
1
6
17
Manado
4
3
0
7
36
Minahasa
1
2
2
5
33
5
4
2
11
8
East Java
West Kalimantan
East Kalimantan
North Sulawesi
Papua
Jayapura
Manokwari
Total
6
3
0
9
14
55
35
24
114
260
Source: field survey (processed)
West Java’s population is nearly as large as that of East Java, even though several
of its second-level administrative regions (but not our two research locations) have
recently become a separate province. West Java occupies the western part of the
island of Java and has several second-level administrative districts bordering on
Jakarta. In 2002, West Java was officially split into two provinces with the establishment of the new province of Banten, comprised of second-level administrative
regions previously part of West Java. The two selected regencies represent only a
small proportion of West Java’s total population, and are located toward the center
of the island. The city of Purwakarta (capital of the regency) is a small city, while
Bandung regency is the territory that surrounds the city of Bandung and contains
the population overflow from the city. These two regions show a very strong contrast in terms of their local economies. Development of the financial sector in West
Java is somewhat behind that of East Java, but financial services in West Java are
30
better than in the other four research location provinces.
In comparison, the remaining four provinces in this study represent smaller populations and many of them have very low population densities. However, low population density is not a characteristic of the urban regions in the research sample
(the cities of Manado, Pontianak, Samarinda and Jayapura). West Kalimantan and
East Kalimantan, located on the western and eastern sides of the island of Kalimantan, have very large areas but very sparse populations. The island of Kalimantan
is in fact shared with two other countries: Malaysia and Brunei. Sanggau regency
borders on Malaysia, and therefore much of its economic activity is related to this
fact, including non-recording of economic flows and a certain amount of smuggling. Aside from having certain highly attractive industries, overall Kalimantan is
somewhat behind Java in terms of economy, infrastructure, and education. Kutai
Kertanegara has several large foreign companies, while Pontianak and Samarinda
are important commercial centers and the centers of government of their respective provinces. In the rural regions of Kalimantan, the level of financial development is generally low, although West Kalimantan has a Credit Union movement
that is quite influential among the Dayak community. Generally, the cities that
served as samples in this study have high proportions of economic activity in the
construction, services, and transportation sectors.
North Sulawesi, bordering on the southern Philippines and located on the northernmost tip of the island of Sulawesi, is a relatively wealthy region with a well-educated population. However, North Sulawesi’s infrastructure is rather poor, and its
financial sector is underdeveloped. The city of Manado is the gateway to trade with
the Philippines and a popular tourism center, as well as the center of government
and regional trade.
Papua has an enormous territory but a tiny population. The easternmost province of Indonesia, Papua shares the island with the nation of Papua New Guinea.
Papua’s economy is dominated by several natural-resource-based industries, which
are the main attraction for investors and are foreign-owned. The central part of
Papua has poor transportation facilities and its people are generally poorly educated. The second-level administrative regions serving as samples in Papua are
both coastal regions. Development of financial institutions in this region is quite
limited. Conditions in Papua are also widely affected by security disturbances.
31
III. PROFILE OF MICRO
FINANCE INSTITUTIONS
33
| PROFILE OF MICRO FINANCE INSTITUTIONS
SCOPE OF THE FINANCIAL INSTITUTION SAMPLE
1. Overview of Micro Finance Institutions
A wide variety of microfinance institutions (MFIs) provide financial intermediation for small-scale borrowers in Indonesia, and this is also so in the locations studied in this research. Some of these MFIs are banks, which are regulated through
the Banking Law and supervised by Bank Indonesia (BI). These bank MFIs include
branches of commercial banks, consisting of private banks and government banks.
In rural regions the functions of these two types differ, in addition to performing
commercial functions, government banks also serve as agents of development,
particularly in channeling government program credits.
Although some of these bank branches have substantial resources, they do not
concentrate on small businesses, especially micro borrowers (which in this study
are defined as loans of up to 50 million Rupiah). The commercial bank branches’
major role is in saving services, and micro finance is only a small part of their
activities.
The two types of banks that are the major exceptions are BRI Village Units (BRI Village Unit) and Regional Development Banks (Bank Pembangunan Daerah, BPD).
These two types of banks provide many micro loans, especially the BRI Village
Units. As of March 2003, BPDs had provided loans of Rp 18 trillion to some 1.8 million clients. The amounts of credit from commercial banks in the twelve research
location regencies/ cities are shown in Table 3-1.
There are, in addition, People’s Credit Banks (Bank Perkreditan Rakyat, BPR). BPRs
are small-scale banks that do not have access to a payment system, with credit outstanding of around Rp 7 trillion (all of which is in the micro loan category).
An even smaller category of banks, found only in Java, consists of the Village
Credit Agencies (Badan Kredit Desa, BKD), which BI has put under BRI’s supervision, and the Village Credit Fund Institutions (Lembaga Dana Kredit Pedesaan,
LDKP) owned by the regional governments. Consideration is currently being given
to transferring these two types into the non-bank MFI category.
35
Table 3-1.
Province
Value of Loans from Commercial Banks (Including BRI Village Unit)
by Research Location, 2002 (Billion Rupiah)
Regency(Kab.)/City(Kota)
West Java
Loans
Small Loans
71,645
11,988
Kab Bandung
5,807
107
Kab Purwakarta
5,530
388
East Java
34,022
10,398
Kab Malang
3,025
1,555
Kota Madiun
435
193
2,822
793
1,280
433
West Kalimantan
Kota Pontianak
Kab Sanggau
East Kalimantan
Kota Samarinda
374
92
5,094
1,004
1,647
368
627
N/A
2,641
1,411
1,146
N/A
502
N/A
657
434
Kota Jayapura
196
164
Kab Manokwari
73
43
Kab Kutai Kartenagara
North Sulawesi
Kota Manado
Kab Minahasa
Papua
Source: Monthly statistics of various branches of Bank Indonesia
Note: All data are from April 2002, except that West Kalimantan is for January
Non-bank financial institutions are often in the form of cooperatives, but sometimes also in the form of Programs, that is, government entities, which are usually sponsored by non-governmental organizations (NGOs) and the government.
In the field, cooperatives and Programs often have the same function and role,
though they differ in form and in their institutional rationale. In addition to the
categories of MFIs mentioned above, there are many informal financial activities
– moneylenders (loan sharks), rotating savings clubs (arisan), and so on – that are
not within the scope of this study. Nearly all the microfinance institutions in this
study provide consumption loans to their clients.
Most cooperatives are registered in various forms with the Cooperatives Department, and this is also evident for the institutions that served as the sample for this
study. However, there are also many cooperatives and pre-cooperatives that are
not registered. Institutions registered as cooperatives may take the form of Savings
and Loan Units (Unit Simpan Pinjam, USP) that are parts of multi-purpose busi36
ness cooperatives. USPs are required to maintain separate financial records from
those of the cooperatives as a whole, but this provision is often ignored. For the
purposes of this study, the analysis of USPs separates multi-purpose business
cooperatives (Koperasi Serba Usaha, KSU), from those serving employees of
specific institutions (Koperasi Karyawan, Kopkar). This was done because of the
significant differences between them in terms of behavior, although their legal
status is the same.
No precise figures are available about the activities of cooperative MFIs. Cooperatives’ lending activities are estimated to amount to over Rp 5 trillion throughout
Indonesia, slightly lower than the value of their deposits. Among the forms of
non-registered cooperatives are Credit Unions, pre-cooperatives such as Self-Reliant Community Productive Economic Institutions (Lembaga Ekonomi Produtif
Masyarakat Mandiri, LEPMM), Savings and Loan Facilities (Tempat Pelayanan
Simpan Pinjam, TPSP), and Islamic credit unions (Baitul Maal wa Tamwil, BMT).
There are quite a few MFIs of these types in the research sample. There are also
cooperatives related to NGOs, but this type appears only in the sample for the
North Sulawesi research area, and not in the other five provinces.
Village Savings and Loan Economic Units (Unit Ekonomi Desa Simpan Pinjam,
UED-SP) established by the Ministry of Home Affairs also appear in this study’s
sample. In their operations, these UED–SP resemble cooperatives. The study also
includes District Development Programs (Program Pengembangan Kecamatan,
PPK) and Regional Development to Overcome the Impact of the Economic Crisis (Pemberdayaan Daerah dalam Mengatasi Dampak Krisis Ekonomi, PDMDKE);
these two are national programs related to poverty eradication programs.
The District Development Programs (PPK) are highly underrepresented in the research sample. It is difficult to discuss other forms of MFIs with any certainty, because these types of MFIs tend to be concentrated in certain regions, and may not
have been captured in the villages and districts that were the locations of this study.
37
2. MFIs in the Research Sample
The data in the following discussion are based on a stratified sample in six
provinces: West Java, East Java, West Kalimantan, East Kalimantan, North Sulawesi
and Papua. In each province, two second-level administrative regions were selected, and from each of these, three districts were selected. In each of these districts,
two villages/subdistricts were selected; however, in the field this was not carried
out completely. A more detailed discussion of the sample selection process is presented in Chapter 1 and Appendix.
3. Legal Status of MFIs
MFIs vary in their legal forms; this is related, among other matters, to the question
of ownership. Some MFIs are owned by individuals, while most banks are in the
form of limited-liability companies (Perseroan Terbatas, PT), which may, in fact,
also be owned by individuals. For BPRs, the existing regulations require that the
owner of a BPR be an Indonesian citizen or Indonesian legal entity (not foreign).
Some MFIs take the form of foundations, and have therefore recently faced certain
problems as a result of the enactment of the Foundations Law of 2001.
DEPOSITS OF SURPLUS FUNDS
MFIs must deposit their surplus funds; they generally do this by depositing in
banks. Table 3-2 shows where they deposit their surplus funds, broken down by
type of MFI. The table shows clearly that general banks are the most popular place
for non-bank MFIs to deposit their surplus funds. This is one form of interdependence between non-bank MFIs and banks. Through this mechanism, the MFIs also
benefit from the differential between the banks’ interest rates and the interest rates
the MFIs pay their clients.
38
In terms of type of institution, the use of banks as places to deposit surplus funds
is most evident in the Kopkar category (84.2%). Even so, it should also be noted
that Kopkar also use many other institutions (42.1%), as do BMTs, Programs, and
Other MFIs1.
It is interesting to see that the same table also shows that the most popular place
overall to deposit surplus funds is “other”. The meaning of depositing in “other”
places most often is that the surplus funds are in fact kept at the MFI’s own office.
Table 3-2. Places of Deposit for Surplus Funds Mentioned
by Non-Bank MFIs by Type of Institution (%)
Type of Institution
BMT
Kopkar
KSP
Other MFIs
Programs
USP
All Non-Banks
Place of Deposit
Higher Office
General Bank
4.2
0.0
16.4
0.0
0.0
4.6
6.2
62.5
84.2
57.4
41.5
28.6
56.8
54.6
BPR
Other
4.2
0.0
3.3
0.0
14.3
4.6
3.5
45.8
42.1
21.3
50.9
42.9
30.7
35.4
Source: Field survey (processed)
The variation in place of deposit of surplus funds occurs not only by type of institution, but also between regencies/cities. Table 3-3 shows that in Sanggau regency,
half of the non-bank MFIs deposit their surplus funds at a higher office. This means
that most of the surplus funds of the MFIs in Sanggau regency circulate only within
their own milieu, without involving other institutions such as banks. In Sanggau
regency, only around 13 percent of the non-bank MFIs deposit their surplus funds
in general banks.
It is also interesting to examine the situation in the city of Madiun. In this city, the
percentage of non-bank MFIs that deposit their surplus funds in banks is relatively
low (40%). Unlike in Sanggau, where surplus funds are mostly deposited to higher
offices, in Madiun only “other” is mentioned as a significant place for deposit of
surplus funds. Quite possibly this is because the non-bank MFIs in Madiun do not
in fact have surplus funds to deposit.
1 Many tables in the report feature multiple responses question. For this reason, total responses can be over 100 percent.
39
Table 3-3. Places of Deposit for Surplus Funds Mentioned by Non-Bank MFIs by Regency/City (%)
Regency(Kab.)/
City(Kota)
Kab Bandung
Kab Purwakarta
Kab Malang
Kota Madiun
Kab Sanggau
Kota Pontianak
Kab Kutai
Kota Samarinda
Kab Minahasa
Kota Manado
Kab Manokwari
Kota Jayapura
Higher Office
0.0
0.0
5.6
5.3
50.0
0.0
11.8
9.5
3.0
2.8
2.4
0.0
Place Deposit
General Bank
BPR
Bank Indonesia
50.0
17.9
7.1
66.7
3.3
0.0
66.7
0.0
11.1
39.5
2.6
2.6
12.5
0.0
0.0
77.8
11.1
0.0
70.6
5.9
0.0
76.2
0.0
4.8
45.5
0.0
0.0
47.2
0.0
0.0
42.9
0.0
0.0
87.5
0.0
0.0
Other
46.4
43.3
11.1
34.2
37.5
55.6
29.4
23.8
45.5
38.9
21.4
12.5
COMPETITION
It is not easy to assess the level of competition in the microfinance sector in
Indonesia, either in terms of deposits or of loans. Generally, it can be said that the
relatively high interest rates and net interest margins reflect a low level of competition. Nevertheless, this survey indicates that competition is reported by the
respondent MFIs.
1. MFIs’ Perceptions of Their Competitors
Generally, this survey shows that three types of institutions are competitors for
non-bank institutions in granting micro loans: informal moneylenders (loan
sharks), Savings and Loan Cooperatives (KSP), and BRI Village Units (BRI Village
Unit). Surprisingly, BPRs are not considered a significant competitor to non-bank
MFIs in micro loans. The survey results for BPRs show that 50 percent of BPR
respondents state that their competitors in granting loans are KSPs, while around
40
25 percent state that the BPRs’ competitors are Village Unit Cooperatives (KUD).
In other words, BPRs consider cooperatives to be their competitors in loaning,
whereas Table 3-4 shows that only a minority of cooperatives mention BPRs as
their competitors. Here we find a kind of asymmetry in perception regarding competition between non-bank MFIs, specifically cooperatives, and BPRs.
Loan sharks are competitors because they usually provide loans using a very quick
and easy procedure, but with extremely high interest rates. KSPs and BRI Village
Units are also competitors, as they are relatively numerous and can reach clients
down to (at least) the district level. As BRI is a state-owned bank, BRI Village Units
usually also offer relatively lower interest rates than do non-bank MFIs.
Table 3-4a. Institutions Mentioned by Non-Bank MFIs as Competitors
in Granting Loans, by Type of Institution and Location (%)
Competitor Institutions
Type of
Institution
BMT:
• All Cities
• All Regencies
• All Locations
Kopkar:
• All Cities
• All Regencies
• All Locations
KSP:
• All Cities
• All Regencies
• All Locations
Other MFIs:
• All Cities
• All Regencies
• All Locations
Programs:
• All Cities
• All Regencies
• All Locations
USP:
• All Cities
• All Regencies
• All Locations
All Non-Bank:
• All Cities
• All Regencies
• All Locations
BKD
USP/
TPSP/
KUD
BRI
Units
Private
BPRs
Regional
Govt
BPRs
BPR
Syariah
General
Banks
0.0
0.0
0.0
0.0
0.0
0.0
28.6
30.0
29.2
7.1
10.0
8.3
75.7
40.0
37.5
7.1
20.0
12.5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
7.7
5.3
0.0
7.7
5.3
0.0
7.7
6.3
16.7
7.7
10.5
16.7
16.4
15.8
16.7
23.1
21.1
0.0
0.0
0.0
0.0
7.7
5.3
0.0
0.0
0.0
0.0
15.4
10.5
3.3
3.2
3.3
3.3
6.5
4.9
13.3
19.4
16.4
10.0
3.2
6.6
26.7
12.9
19.7
3.3
12.9
8.2
6.7
12.9
9.8
0.0
3.2
1.6
0.0
0.0
0.0
0.0
3.2
1.6
3.6
0.0
1.9
0.0
8.0
3.8
25.0
28.0
26.4
14.3
44.0
28.3
26.0
8.0
17.0
3.6
4.0
3.8
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
3.6
0.0
1.9
0.0
0.0
0.0
0.0
0.0
0.0
0.0
16.7
14.3
0.0
0.0
0.0
0.0
50.0
42.9
0.0
16.7
14.3
0.0
0.0
0.0
0.0
8.3
7.1
0.0
0.0
0.0
0.0
0.0
0.0
6.3
0.0
2.3
0.0
5.4
3.4
15.6
21.4
19.3
3.1
1.8
2.3
34.4
23.2
27.3
6.3
19.6
14.8
3.1
1.8
2.3
0.0
5.4
3.4
0.0
0.0
0.0
0.0
3.6
2.3
3.6
1.4
2.3
0.9
5.4
3.5
17.9
20.9
19.6
8.9
10.1
9.6
26.6
20.9
24.2
6.4
16.2
11.5
2.7
3.4
3.1
0.0
4.1
2.3
0.0
0.0
0.0
0.9
3.4
2.3
KSP
Other
MFIs
Loan
Sharks
41
Table 3-4b. Institutions Mentioned by Bank MFIs as Competitors
in Granting Loans, by Type of Institution and Location (%)
Type of
Institution
Government Bank:
• All Cities
• All Regencies
• All Locations
BPD:
• All Cities
• All Regencies
• All Locations
Private Banks:
• All Cities
• All Regencies
• All Locations
BPR:
• All Cities
• All Regencies
• All Locations
BRI Village units:
• All Cities
• All Regencies
• All Locations
All Bank:
• All Cities
• All Regencies
• All Locations
Competitor Institutions
BRI
Branches
BRI
Units
Bank
Mandiri
BPD
BCA
Private
BPRs
BPR
Syariah
BKD
KUD
47.4
45.5
46.7
31.6
27.3
30.0
36.8
36.4
36.7
52.6
81.8
63.3
42.1
9.1
30.0
21.1
27.3
23.3
0.0
0.0
0.0
0.0
0.0
0.0
5.3
0.0
3.3
15.8
0.0
10.0
40.0
62.5
53.8
60.0
37.5
46.2
20.0
25.0
23.1
0.0
0.0
0.0
0.0
12.5
7.7
20.0
12.5
15.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
20.0
12.5
15.4
88.9
66.7
83.3
44.4
0.0
33.3
33.3
66.7
41.7
33.3
33.3
33.3
11.1
0.0
8.3
33.3
33.3
33.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
11.1
0.0
8.3
33.3
11.1
6.7
83.3
83.3
83.3
33.3
0.0
8.3
66.7
22.2
33.3
16.7
16.7
16.7
50.0
77.8
70.8
0.0
5.6
4.2
16.7
5.6
8.3
16.7
27.8
25.0
16.7
61.1
50.0
13.3
5.0
8.6
6.7
0.0
2.9
13.3
15.0
14.3
86.7
35.0
57.1
13.3
20.0
17.1
33.3
35.0
34.3
0.0
0.0
0.0
0.0
0.0
0.0
13.3
30.0
22.9
26.7
50.0
40.0
42.6
25.0
33.3
35.2
35.0
35.1
27.8
18.3
22.8
55.6
35.0
44.7
22.2
15.0
18.4
29.6
43.3
36.8
0.0
1.7
0.9
1.9
1.7
1.8
7.4
18.3
13.2
18.5
36.7
28.1
KSP
Meanwhile, in mobilization of public savings, the significant competitors to nonbank institutions are BRI Village Units, general banks, and KSPs. It must be remembered that BRI Village Units and KSPs are also competitors in granting loans,
and so it is suspected that the reason for this situation is the same: the relatively
extensive reach of BRI Village Units and KSPs. Loan sharks do not provide saving
services, and so it is logical that their existence is not considered competition for
non-bank MFIs in the matter of savings.
Competition between non-bank MFIs and BRI Village Units in granting loans is
also seen from the survey results for bank respondents. Around 23 percent of BRI
Village Unit respondents state that their competitors in granting loans are KSPs,
and 20 percent state that their competitors are other types of cooperatives.
42
Table 3-5a. Institutions Mentioned by Non-Bank MFIs as Competitor
in Mobilizing Deposits by Type of Institution and Location (%)
USP/
TPSP/
KUD
BMT:
• All Cities
• All Regencies
• All Locations
0.0
0.0
0.0
0.0
0.0
0.0
14.3
10.0
12.5
7.1
10.0
8.3
35.7
20.0
29.2
0.0
50.0
20.8
0.0
0.0
0.0
Kopkar:
• All Cities
• All Regencies
• All Locations
0.0
7.7
5.3
0.0
7.7
5.3
16.7
7.7
10.5
0.0
7.7
5.3
0.0
0.0
0.0
0.0
38.5
26.3
KSP:
• All Cities
• All Regencies
• All Locations
3.3
0.0
1.6
0.0
6.5
3.3
6.7
19.4
13.1
3.3
0.0
1.6
6.7
6.5
6.6
Other MFIs:
• All Cities
• All Regencies
• All Locations
3.6
0.0
1.9
0.0
4.0
1.9
3.6
16.0
9.4
17.9
16.0
17.0
Programs:
• All Cities
• All Regencies
• All Locations
0.0
0.0
0.0
0.0
0.0
0.0
0.0
8.3
7.1
USP:
• All Cities
• All Regencies
• All Locations
3.1
0.0
1.1
0.0
3.6
2.3
All Non-Bank:
• All Cities
• All Regencies
• All Locations
2.7
0.7
1.5
0.0
4.1
2.3
Type of Institution
KSP
Competitor Institution
Other
Loan
BRI
Private Regional
MFIs Sharks Units
BPRs
Govt.
BPRs
BKD
BPR
Syariah
General
Banks
0.0
0.0
0.0
0.0
0.0
0.0
21.4
0.0
12.5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
33.3
23.1
26.3
10.0
22.6
16.4
3.3
3.2
3.3
0.0
3.2
1.6
0.0
0.0
0.0
23.3
9.7
16.4
0.0
0.0
0.0
14.3
32.0
22.6
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
7.1
8.0
7.5
0.0
0.0
0.0
0.0
8.3
7.1
0.0
33.3
28.6
0.0
0.0
0.0
0.0
16.7
14.3
0.0
0.0
0.0
0.0
0.0
0.0
3.1
17.9
12.5
0.0
1.8
1.1
15.5
10.7
12.5
15.5
26.8
22.7
0.0
0.0
0.0
0.0
1.8
1.1
0.0
0.0
0.0
21.9
10.7
14.8
6.3
15.5
11.5
6.3
4.7
5.4
10.7
7.4
8.8
10.7
30.4
21.9
0.9
0.7
0.8
0.0
2.7
1.5
0.0
0.0
0.0
18.8
9.5
13.5
As with savings, there is an asymmetry in perceptions about competition between
non-bank MFIs and BPRs. Relatively few non-bank MFIs consider BPRs as their
competitors in loans, while around 37 percent of the BPR respondents stated that
their competitors are KSPs, which are one form of non-bank MFIs. Because this
asymmetry appears consistently, it needs to be examined more closely to see
whether the BPRs are overestimating the level of competition, or the non-bank
MFIs are insensitive to the existence of BPRs as competitors.
43
Table 3-5b. Institutions Mentioned by Bank MFIs as Competitors in
Mobilizing Deposits, by Type of Institution and Location (%)
Competitor Institution
Type of Institution
BRI
Branches
BRI
Units
Bank
Mandiri
BPD
BCA
Private
BPRs
BPR
Syariah
BKD
KUD
KSP
Government banks:
• All Cities
• All Regencies
• All Locations
36.8
36.4
36.7
5.3
36.4
16.7
52.6
54.5
53.3
21.1
72.7
40.0
63.2
27.3
50.0
15.8
18.2
16.7
0.0
0.0
0.0
0.0
0.0
0.0
5.2
0.0
3.3
5.3
0.0
3.3
BPD:
• All Cities
• All Regencies
• All Locations
40.0
75.0
61.5
40.0
37.5
38.5
60.0
37.5
46.2
0.0
0.0
0.0
80.0
25.0
46.2
0.0
12.5
7.7
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Private banks:
• All Cities
• All Regencies
• All Locations
55.6
33.3
50.0
0.0
0.0
0.0
100.0
66.7
91.7
22.2
66.7
33.3
44.4
0.0
33.3
11.1
33.3
16.7
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
11.1
0.0
8.3
BPR:
• All Cities
• All Regencies
• All Locations
33.3
11.1
16.7
66.7
77.8
75.0
16.7
0.0
4.2
50.0
22.2
29.2
33.3
50.0
45.8
16.7
66.7
54.2
16.7
11.1
12.5
0.0
5.6
4.2
16.7
16.7
16.7
16.7
44.4
37.5
BRI Village Unit:
• All Cities
• All Regencies
• All Locations
20.0
10.0
14.3
0.0
0.0
0.0
33.3
15.0
22.9
66.7
35.0
48.6
40.0
30.0
34.3
26.7
30.0
28.6
0.0
0.0
0.0
0.0
0.0
0.0
6.7
30.0
20.0
6.7
35.0
22.9
All Bank:
• All Cities
• All Regencies
• All Locations
35.2
25.0
29.8
13.0
35.0
24.0
51.9
23.3
36.8
35.2
35.0
35.1
51.9
33.3
42.1
16.7
36.7
27.2
1.9
3.3
2.6
0.0
1.7
0.9
5.6
15.0
10.5
7.4
25.0
16.7
Another difference between competition in savings versus lending is the appearance of general banks (mentioned by around 14% of respondents). General banks
usually succeed in attracting deposits through various types of prizes and relatively
high interest rates. On the other hand, general banks do not provide much credit
at the local level, and so they compete with non-bank microfinance institutions in
terms of deposits, but not in terms of loans.
44
It should also be noted that if a certain type of institution is mentioned by nonbank institutions as a competitor but with only a very low percentage (for example,
BPR Syariah), there are two possible explanations: first, this type of institution is
present but is not in fact a competitor, or second, that this type of institution is in
fact not present in the respondent’s area, and thus it is logical that it would not be
a competitor to the non-bank institutions.
2. Forms of Competition
There are very few data in this study on forms of competition. However, some
indications regarding forms of competition can be seen indirectly in the section
on marketing. For those interested in competition as reflected in “price,” Chapter
4 presents data on the interest rates charged and received by MFIs. Of course, the
interest rates for savings and for loans differ; the data on interest rates are therefore presented in the form of a range.
MARKETING
1. Marketing Methods
Incentives for staff to engage in marketing will be discussed in Chapter 5. Meanwhile, Table 3-6 below shows the various marketing methods employed by nonbank MFIs, both for savings and for loans. The table shows that there are two categories of marketing methods: through price mechanisms and through the media.
Table 3-6 shows that in general, non-bank MFIs mostly market savings through
their customers (word of mouth). This method is mentioned as being used by
around 68 percent of all non-bank respondents. This implies that non-bank MFIs
do not employ any specific methods to market their savings facilities. Most likely,
this means is chosen because it is considered the most efficient, as the geographic
area of operation of non-bank MFIs is usually not very large.
45
Marketing methods for loans do not differ greatly from those for savings. Non-bank
MFIs continue to rely on marketing through their customers and direct marketing. In terms of type of institution, BMTs can be seen to be slightly different from
other institutions in their use of media, even though the medium used is relatively
simple (leaflets). For both savings and loans, BMTs are the non-bank MFIs that use
leaflets the most in their marketing.
Table 3-6. Marketing Methods Mentioned
by Non-Bank MFIs for Savings and for Loans, by Type of Institution (%)
Type of
Institution
Marketing Methods
Leaflets
Direct
Radio
Print
Media
Customers
Prizes
Other
For Savings:
BMT
50.0
54.2
16.7
8.3
91.7
16.7
33.3
Kopkar
10.5
31.6
0.0
5.3
68.4
5.3
26.3
KSP
9.8
50.8
3.3
4.9
82.0
8.2
16.4
Other MFIs
1.9
56.6
0.0
1.9
36.5
1.9
15.4
Programs
0.0
35.7
0.0
0.0
57.1
0.0
21.4
USP
16.5
38.8
0.0
2.3
72.9
5.8
14.3
All Non-Bank
14.1
46.3
2.3
3.5
68.4
6.6
18.0
BMT
41.7
50.0
12.5
4.2
95.8
8.3
29.2
Kopkar
10.5
31.6
0.0
5.3
68.4
5.3
21.1
KSP
For Loans:
16.4
59.0
3.3
4.9
91.8
8.2
16.4
Other MFIs
0.0
71.7
0.0
1.9
48.1
1.9
26.9
Programs
7.1
50.0
0.0
7.1
71.4
0.0
28.6
USP
19.8
45.4
1.2
2.3
82.6
7.1
19.1
All Non-Bank
15.6
53.5
2.3
3.5
77.4
5.9
21.8
46
2. Views Regarding Market Potential
Overall, Table 3-7 shows that around 74 percent of non-bank MFI respondents state
that there is still a potential market for savings in their region. However, significant
variations can be seen between regions. This survey at the financial institution
level found that the city of Jayapura was considered the survey location with the
lowest potential for savings (only 25% of respondents though there was potential
to expand deposits). Several other regions can be categorized as having low savings
potential, though not as low as Jayapura: Bandung regency (53%), Manado (60%),
and Kutai Kertanegara regency (65%).
Institutions that stated that potential for savings still exists were asked in which
market segment such potential remained. The same table shows that the lowermiddle to lowest income brackets were the market segments most often mentioned
by respondents. This is because non-bank MFIs are generally aimed at this market
segment. This pattern is seen in all regions, although in differing proportions.
Table 3-7.
Non-Bank MFIs Stating Potential Exists for Savings, by Regency/City (%)
Socio-economic Group (%)
Stating
Potential
Exists (%)
Highest
Upper
Kab Bandung
53.4
20.0
20.0
20.0
Kab Purwakarta
83.3
4.0
8.0
Kab Malang
88.9
6.0
6.0
Kota Madiun
79.0
16.7
Kab Sanggau
75.0
50.0
Kota Pontianak
88.9
Kab Kutai
Kota Samarinda
Regency(Kab.)/
City(Kota)
Upper
Middle
Lower
Middle
Lower
Lowest
33.3
80.0
86.7
16.0
48.0
76.0
48.0
35.4
35.4
47.2
29.5
20.1
30.1
56.7
83.4
73.4
50.0
50.0
83.3
100.0
100.0
37.5
50.0
50.0
75.0
100.0
100.0
64.7
18.2
18.2
27.3
63.6
72.7
81.8
81.0
5.7
11.2
44.6
38.9
61.2
55.7
Kab Minahasa
90.9
40.0
46.7
56.7
60.0
75.9
51.7
Kota Manado
60.0
4.3
8.3
12.3
44.3
68.2
75.2
Kab Manokwari
84.6
8.5
16.8
8.5
25.2
72.7
66.8
Kota Jayapura
25.0
50.0
50.0
50.0
100.0
50.0
50.0
All Locations
74.4
17.2
21.2
31.2
49.8
73.7
64.5
47
However, it should also be noted that around 17 percent of respondents considered
that there is still savings potential in the highest segment. This indicates that MFIs
are also targeting this segment as potential savers.
Table 3-8 contains similar information, but for loans. This table shows that around
91 percent of non-bank respondents in this study stated that there is still potential
for lending in their regions. There is still variation between regions, but not as
great as the variations in savings potential. In several regions (Malang regency,
city of Pontianak, Kutai Kertanegara regency, Minahasa regency, and Manokwari
regency), all respondents stated that such potential exists. This reflects the high
level of demand for micro loans in several regions.
The lowest figure was found in Bandung regency, where only 79 percent of
respondents stated that there is still a potential market for loans. It must be
remembered that Bandung regency is also the lowest in market potential for
savings. According to these perceptions, Bandung has the lowest potential for
expansion of MFI services.
Table 3-8.
Regency(Kab.)/
City(Kota)
Non-Bank MFIs Stating Potential Exists for Loans, by Regency/City (%)
Stating
Potential
Exists %
Kab Bandung
78.6
71.4
46.4
Small
Industries
56.6
56.6
Civil
Servants
30.5
Kab Purwakarta
86.7
83.3
33.3
73.1
46.2
57.7
23.1
Kab Malang
100.0
88.9
77.8
55.6
61.1
33.3
5.6
Kota Madiun
84.2
73.7
57.9
87.5
53.1
65.6
6.5
Kab Sanggau
Agriculture
Trade
Services
Other
4.4
87.5
75.0
75.0
57.1
28.6
42.9
0.0
Kota Pontianak
100.0
100.0
66.7
100.0
77.8
66.7
0.0
Kab Kutai
100.0
64.7
64.7
76.5
47.1
41.2
17.6
Kota Samarinda
90.5
81.0
42.9
68.4
68.4
36.8
15.8
Kab Minahasa
100.0
97.0
75.8
60.6
50.0
40.6
0.0
Kota Manado
91.4
80.6
47.2
63.7
54.6
45.5
12.2
Kab Manokwari
100.0
85.7
78.6
61.5
38.5
46.2
60.0
Kota Jayapura
87.5
75.0
37.5
57.1
42.9
14.3
14.3
All Locations
91.1
81.2
56.5
68.4
53.0
45.4
10.6
48
Socio-economic Group (%)
PROFITABILITY AND SUSTAINABILITY
1. Indicators of Banks’ Financial Performance
Return on Equity (ROE), the ratio between profit and capital, which is the measure
generally used to measure a bank’s financial performance, may be inappropriate
for many cases in this study. This is because nearly all the bank respondents in
this survey were single branches from among the numerous branches of the banks
concerned. Further, it is difficult to distinguish between the capital of the bank’s
owners and the capital derived from the bank’s depositors, especially for BPRS.
The Loan to Deposit Ratio (LDR) is one indicator of the performance of microfinance institutions that can be used specifically to see whether certain institutions
tend to mobilize their funds or not. Table 3-9 shows that in December 2000 and
in May 2003, the value of LDR was less than one. This indicates that in these two
periods, banks were granting loans with a lower value than the amount of deposits
in the banks. The developments in banks’ LDR in this survey show that the figure
tended to remain stable between 2000 and 2002, in the 0.4 to 0.5 range.
Table 3-9.
Financial Performance Ratios of the Sample Banks, 2000-2002
Ratio
December 2000
December 2001
May 2002
Loan Deposit Ratio (LDR)
0.42
0.49
0.52
Expenditure to Income
0.77
0.85
0.82
2. Performance Indicators for Non-Banks
Because of various limitations to the data as explained in the Appendix, the performance ratios used for banks cannot be applied to non-bank financial institutions. The
indicator that is appropriate, and comparable to ROA, is the ratio of profit to credits
granted. The results of the calculation of this ratio can be seen in Table 3-10.
Table 3-10 provides a picture of the profitability of non-bank financial institutions
during the period 2000-2002. The table shows that the institutions with relatively
high and stable levels of profitability were Other MFIs and USPs. The profitability
49
of Other MFIs was 22 percent, 24 percent, and 19 percent respectively for 2000,
2001, and 2002, while for USPs it was 23 percent, 26 percent, and 30 percent. In
2001, BMTs achieved profitability of 35 percent but in the other years observed
(2000 and 2002) never reached 10 percent.
Quite interesting is the change in profitability of Programs (which usually manage government sponsored revolving funds), which was very high in 2000 but
fell sharply in the following years. Most likely, this is related to the performance
pattern of Programs, which are typically excellent during the start of their operation, but then deteriorate. In a number of cases, the rate of repayment of revolving funds declined when the borrowers learned that the funds were derived from
grants. In other words, the factor of moral hazard strongly influences the financial
performance of Programs.
Table 3-10. Ratio of Profit/Loss to Credit Portfolio
of Non-Bank MFIs, by Type of Institution, 2000-2002 (%)
Type of Institution
BMT
December 2001
December 2002
8.5
34.5
9.5
Kopkar
11.7
16.1
13.6
KSP
10.5
10.5
8.7
Other MFIs
22.4
24.4
19.1
Programs
44.1
8.2
3.2
USP
22.9
26.1
29.7
All Non-Bank
17.9
20.6
17.3
50
December 2000
IV. SERVICES
PROVIDED
51
| SERVICES PROVIDED
This section is a discussion of exactly what services are provided by microfinance
institutions, both banks and non-banks, the distribution of services by several criteria, and the requirements related to these microfinance services.
TYPES OF SERVICES
The banking sector provides many types of financial services to small and micro
customers, which fall generally into the categories of loans/credits of various types
and savings facilities. The banking sector also provides services for payments and
fund transfers. Although they are included in the banking category, BPRs are not
allowed to provide payment and fund transfer services; however, some of them
do provide these services, typically in cooperation with general banks or other financial institutions. In Indonesia, banks often provide these services, even though
they have issued credit cards and debit cards, which are also in fact a facility for
payments and fund transfers. Banks also provide services of a non-routine nature,
such as replacing damaged banknotes.
This study focuses on lending and saving services. The discussion on savings will
be much briefer than that on loans, as in this study microfinance institutions are
considered in the context of development of micro enterprises. In this context, attention will be focused mainly on the micro loans granted by the various financial
institutions that served as the sample of the study.
For the sake of simplicity, the discussion in this study will refer only to “savings”
and “loans,” but in reality there is a tremendous variety of products in each of these
categories. Many microfinance institutions offer various loan programs, primarily
programs whose funds come from external investors as opposed to deposits. In this
situation, the requirements and procedures for such loans are usually determined
by the owner (source) of the funds.
As with loans, savings also consist of many product schemes, often accompanied
by prizes or the like. No less important is the difference in requirements for differ53
| SERVICES PROVIDED
ent types of savings, especially between time deposits and regular saving accounts,
which can be withdrawn at any time. Aside from these, there are also giros, and
the situation becomes even more complex with the existence of Islamic financial
institutions, which offer specific types of products.
Non-bank MFIs typically provide a limited range of services, particularly with regard to payments and fund transfers, but even in the matter of loans and savings,
which are the focus of this study, differences are seen. This is especially true for
cooperatives, which are quite numerous in the study sample. Cooperatives usually
have various types of compulsory contribution requirements related to membership, as well as voluntary deposits, for which various incentives are provided.
As with banks, in practice it is not easy to differentiate between mandatory savings and voluntary savings, because the counter-deposit requirements (savings required at the time of borrowing) are often implicit. Many micro loan schemes,
whether operated by cooperatives, banks, or other institutions, also require savings
in connection with loans.
SAVINGS AND LOANS
There is a great variation in the savings products provided by the MFIs in the
study sample. Banks mostly provide time deposits and savings accounts, although
in practice time deposits seldom apply for small/ micro depositors. Other financial
institutions often provide services that are essentially adaptations of the services
provided by banks. For example, cooperatives, in addition to deposits that are in
principle a form of capital participation, also have “regular” savings accounts (like
those at banks).
Loans also vary, though the variation is not as great. Generally, loans can be classified into two categories: standard loans (like those normally granted by banks) and
loans of the government program type.
54
1. Numbers and Values of Savings Accounts and Loans
Table 4-1 shows the numbers of accounts and values of savings and loans in various institutions. Of course, a depositor may have more than one account. This is
particularly true with Programs, in which participants are required to maintain a
balance between their deposits and their loans.
The table shows that the balance between value of loans and that of savings varies
by type of institution, indirectly reflecting their differing orientations. Some institutions have a lower tendency to grant loans than to accept deposits, such as BMTs
and Kopkar. Even so, the fund gap (or surplus) is not very great. What MFIs do with
their surplus funds has been discussed previously in Chapter 3.
In contrast, certain other institutions (KSPs, Programs, and USPs) grant loans in
amounts greater than their deposits. For Programs, this is very easy to understand,
as they are usually focused on providing loans to the public.
Table 4-1a. Number of Accounts and Value of Deposits
and Loans at Bank MFIs by Type of Bank, May 2002
Savings
Type of Bank
Accounts
(000)
Loans
(Rp.000.000)
Value/
Account
Accounts
Value
(Rp.000)
(000)
Value
(Rp.000.000)
Value/
Account
(Rp.000)
Government
banks
532.5
3,220,529.5
6,047.6
50.5
432,421.8
8,555.4
BPD
285.1
1,492,199.4
5,234.7
38.9
419,037.4
10,765.3
Private banks
20.0
270,751.9
13,534.2
6.2
101,746.7
16,413.4
BPR
58.7
42,888.5
730.2
16.6
55,277.0
3,326.9
214.4
186,655.4
870.6
34.5
142,878.3
4,136.8
BRI Units
55
| SERVICES PROVIDED
Table 4-1b. Number of Accounts and Value of Deposits
and Loans1 at Non-Bank MFIs by Type of Institution, May 2002
Savings
Type of
Bank
BMT
Kopkar
KSP 2
Other MFIs
Program
USP
Accounts
(000)
7.5
9.3
36.8
3.1
1.7
33.4
Loans
(Rp.000.000)
Value/
Account
Accounts
1,864.7
1,957.1
31,626.2
1,432.2
78.2
6,221.2
247.6
210.3
858.3
459.6
47.3
186.3
2.8
3.6
34.1
2.7
2.4
17.6
Value
(000)
(Rp.000)
Value/
Account
Value
(Rp.000.000)
(Rp.000)
1,758.2
1,761.6
35,213.3
1,316.1
3,504.4
9,214.3
624.8
483.2
1,031.6
493.7
1,446.9
522.4
Table 4-2 shows the values of deposits and loans in various institutions in various
regions. There are two sources of data in the questionnaires, which are occasionally not consistent with one another: data from responses to direct questions on
deposits and loans, and data from balance sheets.
Table 4-2. Number of Accounts and Value of Deposits and Loans
in Non-Bank MFIs by Regency / City, May 2002 (%)
Savings
Regency(Kab.)/
City(Kota.)
Kab Bandung
Accounts
(000)
Loans
Value
(Rp.000.000)
Value/
Account
(Rp.000)
Accounts
(000)
Value
(Rp.000.000)
Value/
Account
(Rp.000)
6.6
1,491.3
227.6
4.7
1,913.3
410.9
Kab Purwakarta
10.2
3,400.3
332.9
5.9
4,875.2
827.3
Kab Malang
17.7
947.9
53.7
8.5
1,737.4
203.5
Kota Madiun
13.6
1,459.0
107.6
10.9
4,377.5
403.3
Kab Sanggau
2.0
1,339.5
685.2
0.9
980.4
1,101.6
18.5
27,229.1
1,473.2
17.0
24,668.8
1,455.1
Kab Kutai
Kota Pontianak
4.0
1,248.9
308.8
1.8
1,254.8
681.6
Kota Samarinda
6.6
3,509.5
530.4
4.1
3,391.7
833.3
Kab Minahasa
9.6
238.9
24.9
6.0
4,489.3
745.6
Kota Manado
2.5
716.7
285.8
2.5
2,651.0
1,065.1
Kab Manokwari
0.4
1,549.4
4,376.8
0.8
2,287.5
2,841.6
Kota Jayapura
0.3
49.1
149.7
0.3
141.1
456.6
56
1 In reality, not all non-bank MFIs provide “full” services (savings and loans); some provide only savings,
while others provide only loans.
2 Note that the value for KSP has been skewed by an outlier KSP in Pontianak with around 15,000 members,
Rp 24 billion in savings, and Rp 22 billion in outstanding loans
Analogous to the discussion by type of institution, the research regions can also
be divided into two groups. The first group is regions where the value of loans is
slightly lower than or equal with the value of deposits: Sanggau, Pontianak, Kutai,
and Samarinda. The high ratio is caused by a larger number of credit unions in the
sample which characterize these areas. Credit union apply strict savings requirement on their members before they are allowed to borrow.
The other group is those where the value of loans is greater than that of deposits:
Bandung, Purwakarta, Malang, Madiun, Minahasa, Manado, Manokwari, and Jayapura. Generally, the results of field observations indicate that one characteristic
of non-bank MFIs, especially cooperatives, in North Sulawesi is a tendency to be
oriented toward granting loans. They channel funds derived from the cooperatives’
“owners” to the public, rather than funds from third parties.
2. Acceptance of Group Customers
Some MFIs accept group customers, that is, deposits from institutions, while others
do not. Table 4-3a shows that many government banks and BPDs offer group
lending. On the other hand, only a few private banks and BPRs have group lending,
and no BRI Units have group lending. When a bank has group lending activities,
it is mostly implementing government credit programs such as PKM, PUKK and
KUT. In fact, all BPR group lending activities are government credit programs.
Table 4-3a. Banks MFI and Group Lending, by Type of Bank
Government banks (n=30)
14
47
%
Government
Group
Lending
Program
79
BPD (n=13)
Banks With Group Lending
Type of Bank
Number of
Banks
Proportion
(%)
10
77
60
Private banks (n=12)
3
25
67
BPR (n=24)
6
25
100
BRI Units (n=35)
0
0
0
All Bank (n=114)
33
29
76
57
| SERVICES PROVIDED
Table 4-3b. Type of Customers of Non-Bank MFIs by
Type of Bank
BMT
Type of Customer
Individual
83.2
Group
Total
16.8
100.0
Kopkar
N.A
N.A
N.A
KSP
75.0
25.0
100.0
Other MFIs
55.0
45.0
100.0
Programs
15.0
85.0
100.0
USP
67.6
32.4
100.0
All Non-Bank
70.9
29.1
100.0
Table 4-3 shows that in all around 30 percent of the clients of non-bank institutions are group customers. The most interesting case is that of Programs, where 85
percent of customers are group customers. This is easy to understand, as (at least
when they are first established) government programs usually require borrowers
to form groups. Through this group approach, the administrative costs to serve
customers (relative to the value of the loans) can be reduced. Furthermore, the
group approach allows for internal supervision within the groups, thus reducing
the moral hazard that could lead to non-repayment of loans.
3. Savings Interest Rates and Cost of Funds
Savings interest rates are a central issue for intermediation institutions, because
they strongly influence loan interest rates and, in turn, the demand for credit.
Calculation using currently effective interest rates is difficult, but an attempt was
made in this study by converting interest rates into annual interest rates.
Table 4-4b shows savings interest rates in non-bank financial institutions. Overall,
savings interest rates display a very wide range, from 0 percent to 60 percent per
year. The difference in interest rates between institutions is not easy to interpret,
because savings interest rates depend greatly on the product, or type of savings. If
we compare them with the bank interest rates in Table 4-4a, it can be seen that with
58
the exception of BPRs, the interest rates of non-bank institutions are higher than
bank interest rates. However, it should also be noted that certain non-bank institutions (mainly USPs) may grant loans with extremely low interest. This indicates
that the phenomenon of high loan interest rates in non-bank institutions is not one
that applies generally to all such institutions.
Table 4-4a. Minimum, Maximum, and Median Values of Annualized Bank Savings
Interest Rates and Cost of Funds by Type of Bank (%)
Savings Interest Rates
Type of Institution
Min
Max
Average Cost
of Fund*
Median
Government banks
2.0
14.5
10.5
13.4
BPD
3.0
15.0
9.0
9.2
Private banks
2.8
14.0
9.5
11.5
BPR
3.5
25.9
12.0
15.9
BRI Units
2.0
14.0
9.5
9.0
All Bank
2.0
25.9
10.0
11.9
* Data on cost of funds is average figure from respondents estimates
Table 4-4b. Minimum, Maximum, and Median Values of Annualized Non-Bank MFIs
Savings Interest Rates and Cost of Funds by Type of Institution (%)
Savings Interest Rates
Type of Institution
Min
Max
Median
Average Cost
of Fund*
BMT
0.0
48.0
13.5
11.6
Kopkar
0.0
37.9
15.0
10.1
KSP
0.0
60.0
18.0
16.8
Other MFIs
0.0
60.0
24.0
8.0
Programs
0.0
30.0
9.6
5.9
USP
0.0
60.0
12.0
15.7
All Non-Bank
0.0
60.0
15.0
13.6
* Data on cost of fund is average figure from respondents estimates
59
| SERVICES PROVIDED
4. Loan Interest Rates
As explained above, interest rates are a central issue in discussions on microfinance services. Table 4-5 consistently indicates that BPRs are the type of bank that
charges the highest interest rates. For working capital credits, BPRs charge interest
rates between 24 percent and 60 percent, while for investment credits and other
credits, their interest rates are between 24 percent and 42 percent. By way of comparison, aside from BPRs, the highest interest rates are charged by government
banks, at 26 percent (for working capital credits and investment credits).
Table 4-5.
Type of Bank
Government
banks
BPD
Minimum, Maximum, and Median Values of Annualized Interest Rates
for Bank Micro Loans by Type of Loan and Type of Bank (%)
Working Capital
Min
Max
Investment
Med
Min
Max
Other
Med
Min
Max
Med
6.0
26.0
19.0
16.0
26.0
20.0
12.0
24.0
19.5
6.0
24.0
12.0
12.0
24.0
19.0
6.0
21.0
16.0
Private banks
12.0
23.0
19.0
16.0
23.0
21.0
18.5
25.0
21.0
BPR
24.0
60.0
31.5
24.0
42.0
36.0
10.0
42.0
30.0
BRI Unit
12.0
24.0
24.0
16.0
24.0
24.0
16.0
24.0
24.0
All Bank
6.0
60.0
22.0
12.0
42.0
22.0
6.0
42.0
20.0
For non-banks, the interest rates charged to micro loan customers vary tremendously; they may be extremely high, or extremely low, as shown in Table 4-63. This
table shows that overall, the interest rates of non-bank institutions range from zero
percent to 96 percent. Zero percent interest rates (no interest) are usually provided
by non-bank institutions with a social mission, but they do not usually involve significant amounts of funds.
60
3 Interest rates for investment credit were not provided by most of the non-bank MFIs. Therefore,
the available data on interest rates for investment credit was merged in the group interest rate on working capital credit.
Table 4-6. Minimum, Maximum, and Median Values of Annualized Interest Rates
for Non-Bank MFI Micro Loans by Type of Loan and Type of Institution (%)
Type of Bank
BMT
Working Capital
Min
Max
Other
Med
Min
Max
Med
10.0
60.0
18.0
12.0
60.0
21.0
Kopkar
2.0
60.0
24.0
18.0
30.0
24.0
KSP
1.5
96.0
24.0
5.0
60.0
24.0
Other MFIs
1.0
96.0
36.0
10.0
60.0
21.0
Programs
2.0
60.0
20.0
20.0
24.0
22.2
USP
0.0
96.0
24.0
10.0
96.0
24.0
All Non-Bank
0.0
96.0
24.0
5.0
96.0
24.0
It is also interesting to compare the loan interest rates of non-bank micro
finance institutions by regions. The hypothesis proposed is that loan interest rates in regions outside Java are higher than in Java because of the relatively
higher cost of funds and operating costs. Table 4-7 shows that in this survey, this
hypothesis is not supported by strong evidence in the field. Interest rates in Malang
regency (East Java), for example, are relatively low, but so are those in Pontianak
(West Kalimantan).
Table 4-7. Minimum, Maximum, Values of Annualized Interest Rates
of Non-Bank MFI Loans by Type of Loan and Region (%)
Regency
Working Capital
Min
Max
Other
Med
Min
Max
Med
Kab Bandung
0.0
72.0
24.0
12.0
30.0
21.0
Kab Purwakarta
2.0
72.0
30.0
12.0
72.0
30.0
Kab Malang
5.0
60.0
30.0
5.0
42.0
24.0
Kota Madiun
12.0
78.0
24.0
18.0
60.0
24.0
Kab Sanggau
10.0
24.0
24.0
10.0
24.0
24.0
Kota Pontianak
15.0
30.0
24.0
18.0
24.0
21.0
Kab Kutai
1.5
60.0
27.0
18.0
48.0
30.0
Kota Samarinda
3.3
96.0
24.0
18.0
96.0
24.0
Kab Minahasa
2.0
72.0
24.0
24.0
24.0
24.0
Kota Manado
10.0
96.0
48.0
10.0
60.0
35.0
Kab Manokwari
1.0
60.0
8.0
12.0.
60.0
12.0
Kota Jayapura
2.5
30.0
24.0
n.a
n.a
n.a
61
| SERVICES PROVIDED
5. Loan Administration Fees
Table 4-8 gives a picture of the costs that must be borne by customers when they
borrow money from financial institutions, whether banks or non-banks. In all,
around 58 percent of non-bank institutions charge their customers administration
fees. If we compare by type of institution, the ones that most often charge administration fees are BMTs (74%), while those that least often do so are Other MFIs
(25%). This is because Other MFIs (PDMDKE and the like) are usually instruments
for government loan programs (such as the PPK program). On the other hand, only
two types of non-bank institutions charge notary fees and insurance fees: KSPs and
USPs. Most likely, these charges for notary fees and insurance fees apply only to
loans of high value.
For the institutions that charge them, some of these various loan fees are fixed
rates, while for others, these fees are a percentage of the value of the loan. For fixed
rates, the average administration fee is Rp 8,600, the average insurance fee is Rp
13,000, and the average notary fee is Rp 225,000. When they are a percentage of
the loan, administration fees average 2.2 percent, insurance fees 1.6 percent, and
notary fees 2.0 percent.
Table 4-8a. Non-Bank MFIs that Specify Requirements
for Loans by Type of Institution (%)
Type of Institution
62
Administrative
Fees
Insurance Fees
Notary Fees
Mandatory
Savings
BMT
73.9
0.0
0.0
43.4
Kopkar
50.0
10.0
0.0
35.0
KSP
70.5
13.1
8.2
42.6
Other MFIs
24.5
0.0
0.0
39.6
Programs
42.8
0.0
0.0
35.7
USP
69.3
18.2
10.2
31.8
All Non-Bank
58.0
7.3
5.3
37.6
Meanwhile, for banks, Table 4-8b shows that around 72 percent of the bank
respondents state that they charge their customers loan administration fees.
This percentage is around the same as the percentage of bank respondents that
require notary fees. Without discussing the amounts of these charges, Table 4-8a
and Table 4-8b show that compared with non-bank MFIs, banks tend more often to
charge customers fees in addition to the loan interest. As well as the difference in
standards of administration, this may also be due to the difference in the value of
the loans.
Among the various types of banks, BRI Village Units are the ones that least often
charge administration fees. Only around 34 percent of BRI Village Units state that
they charge their borrowers administration fees. In comparison, around 96 percent
of BPRs state that they charge administration fees. In contrast, with regard to notary fees, the largest percentage of respondents stating that they charge such fees
is BRI Village Units (86%). By way of comparison, only 45 percent of BPRs state
that they charge their borrowers notary fees.
Table 4-8b Bank MFIs that Specify Requirements for Loans by Type of Bank (%)
Type of Bank
Administration
Fees
Insurance Fees
Notary Fees
Mandatory
Savings
Government banks
90.0
60.0
76.7
16.7
BPD
76.9
76.9
53.8
84.6
Private banks
83.3
83.3
83.3
16.7
BPR
95.8
50.0
45.8
50.0
BRI Village Units
34.3
34.3
85.7
48.6
All Bank
71.9
54.4
71.0
41.2
6. Savings Requirements for Loans
In addition to financial requirements, around 38% of non-bank institutions require
borrowers to have a savings account as a condition for extending credit (Table
4-8). In terms of type of institution, the percentages of institutions that impose this
requirement range from 32% (USPs) to around 43% (KSPs and BMTs). The amount
or value of such mandatory deposits was not included in this study.
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A slightly higher percentage of banks require borrowers to open savings accounts.
This once again confirms that banks impose relatively greater burdens on borrowers than do non-bank institutions. In this context, positioning non-bank MFIs as
alternative institutions for micro enterprises to access micro loan facilities is a very
logical step.
7. Net Interest Margin
Net interest margin is the differential between loan interest rates and savings interest rates. For the sake of simplicity, administrative and other fees are not taken
into consideration. Table 4-9 shows that in general, the net interest margin of nonbank institutions is higher than that of banks. It should be noted that the net interest margin cannot automatically be interpreted as a profit earned by the institution, because it could well be that a high margin is caused by high operating costs.
Table 4-9. Median Savings Interest Rates, Loan Interest Rates, and Net Interest Margins
of Bank and Non-Bank MFIs by Type of Bank and Institution (%)
Type of Bank/
Institution
Median Savings
Interest
Median Loan
Interest Rates
Net Interest
Margin
Bank:
• Government banks
• BPD
• Private banks
10.5
19.5
9.0
9.0
16.0
7.0
9.5
20.0
10.5
12.0
30.0
18.0
• BRI Units
9.5
24.0
14.5
• All Bank
10.8
21.0
10.2
• BMT
13.5
23.0
9.5
• Kopkar
15.0
27.0
12.0
• KSP
18.0
29.0
11.0
• Other MFIs
24.0
34.7
10.7
9.6
24.8
15.2
• USP
12.0
30.6
18.6
• All Non-Bank
15.0
29.6
14.6
• BPR
Non Bank:
• Programs
64
8. Total Cost of Loans
It is evident that even ignoring the transaction costs incurred from the complex
procedure of releasing loans and of collateral requirements, both administration
fees and deposit requirements produce an increase in the actual cost of loans.
Even so, most institutions have costs of loans that do not differ greatly from the
nominal interest rates. There are some extreme values, mostly from those that
report extremely low interest rates. All of this comes from the transaction costs
incurred in the process, and from illegal commissions, which are often reported
but are not directly covered in this study.
9. Loan Repayment Rate
The repayment rate of loans is a problem for all financial institutions, though the
degree of problems with micro loans is usually smaller than with larger loans. The
loan repayment rate for banks is presented in Table 4-10a. The table shows that
overall the loan repayment rate to banking institutions is 94.5 percent. The loan
repayment rate at government banks, BPDs and BRI Village Units are higher than
at private banks and BPRs.
Table 4-10a. Repayment Rate of Micro Loans at
Bank MFIs by Type of Bank and Region (%)
Type of Bank
Cities
Government banks
93.9
Regencies
97.6
All Locations
95.6
BPD
97.0
94.9
95.6
Private banks
94.6
95.0
94.7
BPR
92.4
91.2
91.5
BRI Units
97.2
94.6
95.6
All Bank
95.1
94.1
94.5
Table 10b presents information on the loan repayment rate in non-bank financial
institutions. Compared with banks, the level of loan repayment at non-bank institutions is lower, only around 93 percent. Among the non-bank financial institutions, the lowest loan repayment rate is seen in USPs.
65
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Table 4-10b. Repayment Rate of Micro Loans at
Non-Bank MFIs by Type of Institution and Region (%)
Type of Institution
City
Regency
All areas
BMT
95.8
89.0
92.7
Kopkar
94.7
94.3
94.4
KSP
94.2
92.0
93.2
Other MFIs
96.2
90.5
93.5
Programs
98.5
88.7
90.1
USP
87.2
89.2
86.1
All Non-Bank
94.7
91.2
92.7
GEOGRAPHICAL COVERAGE
1. Geographical Coverage of Services
With regard to the geographical extent of MFIs’ service networks, there is a tremendous variation between regencies in terms of numbers of institutions and of customers. Services are generally more intensive in urban regions than in regencies.
Furthermore, services are also more limited in many regions outside Java. Manokwari (Papua) and Sanggau (West Kalimantan) are the regions whose microfinance
institutions have the fewest services.
In fact, variation is even found within districts; more micro financial services are
found in district capitals than in villages far from the district capitals. This is indicated by the fact that in around half of the villages surveyed, there were no microfinance institutions.
66
2. Areas of Operations
It can also be seen that the geographical targets of the MFIs in this study may be
characteristic of MFIs as a whole. Table 4-11 shows the operational areas as defined
by the MFIs themselves. Around 32 percent of the non-bank institutions in the
study have very limited areas of operations, only one village. These institutions fill
a market not yet reached by traditional banking services.
Table 4-11.
Type of Institution
Distribution of Non-Bank MFIs by Operational Area (%)
> 1 Regency/
City
District up to
Regency
Village
up to
District
1 Village
TOTAL
BMT:
• All Cities
• All Regencies
• All Locations
30.8
0.0
17.4
53.8
20.0
39.1
7.7
40.0
21.7
7.7
40.0
21.7
100.0
100.0
100.0
Kopkar:
• All Cities
• All Regencies
• All Locations
40.0
15.4
22.2
40.0
30.5
38.9
0.0
46.2
33.3
20.0
0.0
5.6
100.0
100.0
100.0
KSP:
• All Cities
• All Regencies
• All Locations
50.0
6.5
27.9
30.0
35.5
32.8
8.7
25.8
16.4
13.3
32.3
23.0
100.0
100.0
100.0
Other MFIs:
• All Cities
• All Regencies
• All Locations
11.5
0.0
5.8
15.4
0.0
7.7
19.2
19.2
19.2
53.8
80.8
63.3
100.0
100.0
100.0
Programs:
• All Cities
• All Regencies
• All Locations
50.0
0.0
7.1
0.0
6.3
7.1
0.0
41.7
35.7
50.0
50.0
50.0
100.0
100.0
100.0
USP:
• All Cities
• All Regencies
• All Locations
25.0
8.9
14.8
46.9
19.8
29.5
6.3
48.2
33.0
21.9
23.2
22.7
100.0
100.0
100.0
All Non-Bank:
• All Cities
• All Regencies
• All Locations
30.6
6.1
16.4
34.3
20.3
28.2
9.3
37.2
25.4
25.9
36.5
32.0
100.0
100.0
100.0
67
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Table 4-11 shows a significant difference between institutions located in regency
(rural) areas and those located in cities (urban areas). For all types of institution,
around 31 percent of institutions located in urban regions have a presence in areas
larger than one regency, while for institutions located in regencies, the percentage
is only around six percent. In fact, among the BMTs and Other MFIs in regency
areas, there is not one that has a presence larger than one regency. Thus, it is clear
that non-bank microfinance institutions located in cities have more extensive operational areas than those located in regencies.
Among the various types of institution, the ones that most often have a presence
in only one village are Other MFIs (around 63%). This is understandable, because
several institutions, such as UED, PDMDKE, P2K, and BKD (all of which fall into
the “Other MFIs” category) are in fact designed to work in village regions. But as
things develop, institutions that were originally designed to serve one village may
serve residents of other villages.
In all, for non-bank institutions, Table 4-11 shows that 32 percent have a presence
in only one village. This means that around a third of non-bank MFIs in the research sample are believed to operate on a very small scale.
On the other hand, it is interesting to note that 16 percent of non-bank MFIs have
coverage in more than one regency. This is an indication that although many are
small-scale, non-bank MFIs have started to develop into larger-scale business units.
Therefore, the paradigm that non-bank MFIs are highly local by nature may, in the
years to come, have to be revised.
68
TARGET GROUPS
1. Gender
Two aspects are considered: female target groups or customers, and the views of
MFIs about the behavior of female customers. Table 4-12 provides a picture of the
target customers by gender, as reported by respondents. As might be expected,
most (88%) MFIs stated that they have both male and female target groups, or in
other words, they do not place a priority on any particular gender as their target.
It is not easy to observe the proportion of loans to women, whether in terms of
amounts outstanding or of number of accounts, which would be one key measure
to examine the aspects of gender in the banking sector. Unfortunately, most financial institutions do not specifically record or categorize their customers by gender.
This study therefore only asked for respondents’ estimates, and as a consequence
the answers may well be subjective. Data on percentages of amounts outstanding
and accounts for women based on these estimates are presented in Table 4-13.
Table 4-12.
Non-Bank MFIs Target Group by Regency/City (%)
Target Groups
Regency(kab.)/
City(kota)
Women
Kab Bandung
Both
women
and men
Men
Total
0.0
3.6
96.4
100.0
20.0
3.3
76.7
100.0
Kab Malang
0.0
0.0
100.0
100.0
Kota Madiun
13.2
2.6
84.2
100.0
Kab Sanggau
8.9
1.8
89.3
100.0
Kota Pontianak
0.0
0.0
100.0
100.0
Kab Kutai
0.0
0.0
100.0
100.0
Kota Samarinda
4.8
4.7
90.5
100.0
Kab Minahasa
12.1
6.1
81.8
100.0
Kota Manado
Kab Purwakarta
13.9
2.8
83.3
100.0
Kab Manokwari
0.0
0.0
100.0
100.0
Kota Jayapura
37.5
0.0
62.5
100.0
All Locations
9.2
2.7
88.1
100.0
| SERVICES PROVIDED
69
Table 4-13. Outstanding Loans and Savings Accounts held by Women by Type of MFI (%)
Type of MFIs
Women (%)
Loans
Savings
Bank:
Government banks
47.1
24.8
BPD
32.8
30.9
Private banks
20.4
16.8
BPR
33.8
28.4
BRI Units
25.6
23.2
All Bank
33.1
25.0
BMT
45.3
45.3
Kopkar
37.2
35.3
KSP
46.0
46.9
Other MFIs
66.1
64.3
Programs
43.6
40.0
USP
46.4
51.8
All Non-Bank
48.9
50.5
Non-Bank
Figure 4-1 shows that quite a few bank respondents stated that there is a difference
in character between male and female customers, particularly with regard to their
position as loan customers. When types of banks are compared, it is seen that BPDs
are the type of bank that most often states that there is a difference between male
and female customers, while the lowest figure is for private banks.
70
Figure 4-1. Bank Respondents Stating There Are Differences in
Character between Male and Female Customers (%)
Government Banks
BPD
Private Banks
BPR
BRI Units
All Banks
Table 4-14a shows that in general, in cases when a difference in character is considered to exist between male and female customers, female customers are considered superior to male customers. They are said to be better in promptness of
repayment of loan installments, easier to collect from, and more honest.
Table 4-14a. Bank MFIs Mentioning Advantages of
Female Customers over Males (%)
Prompter
Payers
Type of Bank
Usually have
fixed business
Easier to
collect from
More honest
Government banks
78.6
57.3
78.6
57.3
BPD
66.7
16.7
50.0
100.0
Private banks
25.0
25.0
0.0
50.0
BPR
63.6
36.4
72.7
63.6
BRI Units
66.7
46.7
73.3
60.0
All Bank
66.0
42.0
66.0
66.0
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Non-bank MFIs’ perceptions of differences between male and female customers
do not differ greatly from banks’ perceptions. When we make a comparison among
non-bank institutions, BMTs are the type that most often considers differences to
exist between the two groups of customers, while the lowest figure is for Other
MFIs (Figure 4-2).
Figure 4-2 Non-Bank MFI Respondents Stating There Are Differences
in Character between Male and Female Customers (%)
BMT
Kopkar
KSP
Other MFIs
Program
USP
All Non-Bank
The opinions about advantages of female customers over male customers also do
not differ greatly from those expressed by banks. A majority of non-bank respondents felt that women are better in terms of prompt payment of loan installments,
ease of collection, and honesty (Table 4-14b).
Table 4-14b. Non-Bank MFIs Mentioning Advantages of Female Customers over Males (%)
Type of Bank
72
Prompter
payers
Usually have
fixed business
Easier to
collect from
More honest
BMT
43.9
25.2
50.2
50.2
Kopkar
16.7
16.7
16.7
0.0
KSP
82.1
35.7
82.1
75.0
Other MFIs
80.0
28.6
78.6
78.6
Programs
85.7
71.4
100.0
85.7
USP
59.7
35.4
51.6
51.6
All Non-Bank
65.3
34.4
64.0
60.3
2. By Socioeconomic Strata
It has been mentioned in other sections of this report that non-bank MFIs are an alternative for the poor and/or micro enterprises to obtain financial services. Banks
are considered too bureaucratic by a majority of the poor and/or micro enterprises.
Banks are also unable to provide services to the poorer strata, because the cost of
servicing small loans is prohibitive. This consideration of profitability is believed to
influence banks’ unwillingness to channel micro credits.
Table 4-15a shows that this indication is not far off the reality in the field. Around
86 percent of non-bank MFIs state that their target group is “middle-lower”. The
“lower” group is also an important target group for non-bank MFIs (76%), though
there are also non-bank MFIs that aim at the “upper” and “middle upper” classes as
their target groups. This is because Employee Cooperatives (Koperasi Karyawan,
Kopkar) in institutions such as universities, government offices, and private companies provide services to non-poor customers.
It is interesting to see that around 62 percent of banks state that their target group
is the lower category. In terms of type of bank, BRI Units are the type that most often states that the lower stratum is their target group (80%), while the lowest figure
is for private banks (33%). In fact, among the private banks located in regencies,
not one stated that the lower stratum is their target group.
It should be noted that these data are respondents’ subjective evaluations, and
rather difficult to relate to actual socio-economic data. However, a loan of Rp 50
million (defined in this study as micro loans) is in Indonesia considered quite
large, relative to average income. In this situation, loans of Rp 500,000 or less are
most likely to be loans to extremely poor people.
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Table 4-15a. Non-Bank MFI Market Segments by Type of Institution and Location (%)
Social Stratum
Type of Institution
Upper
Middle
MiddleLower
Lower
BMT:
• All Cities
• All Regencies
• All Locations
7.1
0.0
4.2
0.0
0.0
0.0
64.3
10.0
41.7
100.0
90.0
95.8
78.6
80.0
79.2
Kopkar:
• All Cities
• All Regencies
• All Locations
0.0
23.1
15.8
33.3
30.8
31.6
33.3
69.2
57.9
100.0
69.2
78.9
50.0
38.5
42.1
KSP:
• All Cities
• All Regencies
• All Locations
16.7
9.7
13.1
26.7
12.9
19.7
63.3
48.4
55.7
90.0
83.9
86.9
66.7
83.9
75.4
Other MFIs:
• All Cities
• All Regencies
• All Locations
3.6
3.8
3.7
14.3
11.5
13.0
32.1
38.5
35.2
71.4
88.5
79.6
78.6
88.5
83.3
Program:
• All Cities
• All Regencies
• All Locations
0.0
0.0
0.0
0.0
0.0
0.0
50.0
25.0
28.6
100.0
91.7
92.9
50.0
100.0
92.9
USP:
• All Cities
• All Regencies
• All Locations
6.3
14.3
11.4
21.9
16.1
18.2
59.4
37.5
45.5
90.6
83.9
86.4
87.5
67.9
75.0
All Non-Bank:
• All Cities
• All Regencies
• All Locations
8.0
10.1
9.2
18.8
13.5
15.8
52.7
39.9
45.4
87.5
84.5
85.8
75.9
75.7
75.8
74
MiddleUpper
Table 4-15b. Bank MFI Market Segments by Type of Bank and Location (%)
Social Stratum
Type of Institution
Upper
MiddleUpper
Middle
MiddleLower
Lower
Government banks:
• All Cities
• All Regencies
• All Locations
16.7
27.3
20.7
27.8
27.3
27.6
66.7
63.6
65.5
94.4
90.9
93.1
44.4
63.6
51.7
BPD:
• All Cities
• All Regencies
• All Locations
16.7
0.0
7.1
16.7
0.0
7.1
66.7
50.0
57.1
100.0
87.5
92.9
66.7
75.0
71.4
Private banks:
• All Cities
• All Regencies
• All Locations
11.1
66.7
25.0
11.1
66.7
25.0
77.8
100.0
83.3
77.8
66.7
75.0
44.4
0.0
33.3
BPR:
• All Cities
• All Regencies
• All Locations
0.0
16.7
12.5
66.7
44.4
50.0
83.3
55.6
62.5
100.0
88.9
91.7
50.0
61.1
58.3
BRI Units:
• All Cities
• All Regencies
• All Locations
0.0
25.0
14.3
6.7
20.0
14.3
73.3
65.0
68.6
93.3
85.0
88.6
80.0
80.0
80.0
All Bank:
• All Cities
• All Regencies
• All Locations
9.3
21.7
15.8
22.2
28.3
25.4
72.2
61.7
66.7
92.6
86.7
89.5
57.4
66.7
62.3
75
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3. By Economic Sector
Table 4-16a clearly shows that the trade sector is the primary target of non-bank
MFIs (and also of banks in micro lending). Around 50 percent of all accounts in
non-bank MFIs are accounts from customers in the trade sector. The reasons why
this occurs may be quite complex, but the main reason is that the trade sector is
the largest non-agricultural sector. Among the 16 million micro enterprises (with
fewer than five employees) in the non-agricultural sector, around 60 percent are
micro enterprises in the trading sector. Compared with agriculture, which is the
largest sector, the trading sector is relatively easy to serve, because cash flow is
rapid, and profit margins may be greater.
In second place after the trade sector are the “other” sector (including services)
and industry (15%). Meanwhile, the agriculture sector is the least attractive sector
for non-bank MFIs. In all, only around 10% of micro loan accounts come from the
agriculture sector. In terms of supply, MFIs are not very interested in serving the
agriculture sector because of its seasonal character and relatively long production
cycle (especially when compared with the trade sector). Furthermore, on the demand side, not many farmers are interested in borrowing money from MFIs, probably because the government widely and intensively channels subsidized credits
to the agriculture sector.
If a comparison is made by type of institution, it is seen that BMTs and Kopkar
differ somewhat from the other types of institution. Unlike other institutions, BMTs
have a very low percentage of accounts in the “other” sector (1%). This shows that
BMTs are highly concentrated on financing the productive sector, because the largest part of the “other” sector is consumption. In contrast, Kopkar differ from other
institutions as they are highly concentrated on the “other” sector (53%). As these
are employee cooperatives, this is easy to understand, because cooperatives must be
oriented toward the needs of their members (who want to obtain consumer loans).
76
Table 4-16a.
Micro Loan Accounts from Non-Bank MFIs by Economic Sector (%)
Type of Institution
Economic Sector
Trade
Agriculture
Industry
Services
Other
TOTAL
BMT:
• All Cities
• All Regencies
• All Locations
59.3
39.5
52.7
12.2
1.0
8.5
18.3
17.4
18.0
8.4
42.1
19.6
1.8
0.0
1.2
100.0
100.0
100.0
Kopkar:
• All Cities
• All Regencies
• All Locations
68.8
0.0
34.4
0.0
0.0
0.0
12.5
0.0
6.3
12.5
0.0
6.3
6.3
100.0
53.1
100.0
100.0
100.0
KSP:
• All Cities
• All Regencies
• All Locations
57.1
29.3
45.8
7.7
25.5
15.0
11.6
13.0
12.1
14.5
5.9
11.0
9.7
26.3
16.8
100.0
100.0
100.0
Other MFIs:
• All Cities
• All Regencies
• All Locations
33.7
56.5
45.9
3.1
9.0
6.3
32.1
5.7
18.0
11.1
14.1
12.7
19.9
16.9
18.4
100.0
100.0
100.0
Programs:
• All Cities
• All Regencies
• All Locations
49.0
43.1
44.8
0.8
16.9
12.3
47.3
3.8
16.2
3.0
16.3
12.5
0.0
20.0
14.3
100.0
100.0
100.0
USP:
• All Cities
• All Regencies
• All Locations
69.8
42.9
55.2
4.9
11.8
8.7
15.6
14.0
14.7
5.7
10.2
8.1
4.1
24.9
15.3
100.0
100.0
100.0
All Non-Bank:
• All Cities
• All Regencies
• All Locations
58.6
40.1
49.4
6.1
13.7
9.9
18.1
11.7
14.6
9.8
12.0
10.9
7.7
25.1
16.3
100.0
100.0
100.0
The situation for banks turns out to be consistent with what happens with nonbanks, as can be seen in Table 4-16b. The table shows that the trade sector is the
most attractive sector, along with the “other” sector, which is the consumption sector. Again, the agriculture sector is less attractive than the trade sector. Among
the types of banks, the ones with the greatest attention to the agriculture sector
(although the figures are small) are BPRs and BRI Units.
| SERVICES PROVIDED
77
Table 4-16b. Micro Loan Accounts from Bank MFIs by Economic Sector (%)
Type of Institution
Economic Sector
Trade
Agriculture
Industry
Services
Other
TOTAL
Government banks:
• All Cities
• All Regencies
• All Locations
43.0
32.0
38.2
13.9
0.8
8.1
1.6
0.5
1.1
3.7
6.8
5.1
37.6
60.0
7.5
100.0
100.0
100.0
41.1
7.8
24.4
3.8
0.7
2.3
12.7
0.3
6.5
9.6
0.7
5.1
32.8
90.5
61.7
100.0
100.0
100.0
• All Cities
• All Regencies
• All Locations
26.9
25.0
26.5
4.2
0.0
3.4
5.8
0.0
4.7
1.4
8.3
2.8
61.6
66.7
62.6
100.0
100.0
100.0
BPR :
• All Cities
• All Regencies
• All Locations
43.6
48.7
47.1
12.4
12.0
12.1
6.8
1.6
3.3
8.8
8.4
8.5
28.4
29.5
29.2
100.0
100.0
100.0
39.4
48.7
45.0
8.8
15.3
12.9
2.7
3.2
3.0
19.1
4.4
10.2
33.2
28.4
30.2
100.0
100.0
100.0
39.7
41.8
40.9
9.8
10.3
10.1
4.1
2.1
3.0
10.4
5.6
7.8
37.3
40.3
39.0
100.0
100.0
100.0
BPD:
• All Cities
• All Regencies
• All Locations
Private banks:
BRI Units:
• All Cities
• All Regencies
• All Locations
All Bank:
• All Cities
• All Regencies
• All Locations
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Microfinance Services in Indonesia

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