microfinance services in indonesia: a survey of institutions in six

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Microfi nance Services in Indonesia :A Survey of Institutions in 6 Provinces

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| Microfi nance Services in Indonesia | INTRODUCTION

TABLE OF CONTENTS

List of Tables 4Abbreviations 9Forward 11

I. INTRODUCTION 13Background 15Research Methodology 16Research Sample 18

II. PROFILE OF THE RESEARCH AREAS 23Variation between Regions 25Available Figures 26Conditions of Regencies/Cities 26

III. PROFILE OF MICROFINANCE INSTITUTIONS 33Scope of the Financial Institution Sample 35Deposits of Surplus Funds 38Competition 40Marketing 45Profi tability and Sustainability 49

IV. SERVICES PROVIDED 51Types of Services 53Savings and Loans 54Geographical Coverage 66Target Groups 69

V. OPERATIONS, SYSTEMS, AND PROCEDURES OF MFIs 79Employees 81Systems and Procedures 89Internal Supervision 101

VI. RELATIONS WITH OTHER INSTITUTIONS 103Types of Institutions 106Forms of Cooperation 109External Supervision 112

VII. SUMMARY OF FINDINGS 115

APPENDIX 125THE DATA : WHAT THEY REPRESENT AND THEIR LIMITATIONS

Research Design 127Limitations to Reports from Government Offi cials 127Limitations in the MFI Survey Data 134

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LIST OF TABLES

TABLENO

TITLE

1-1 Research Locations

1-2aNumbers of Bank and Non-Bank Respondents by Regency / City in West Java and East Java

1-2bNumbers of Bank and Non-Bank Respondents by Regency / City in West Kalimantan and East Kalimantan

1-2cNumbers of Bank and Non-Bank Respondent by Regency / City in North Sulawesi and Papua

2-1 Background Data on Research Locations, 2001 / 2002

2-2Values 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

2-4Numbers of Financial Institutions (Bank and Non-Bank) in Sample by Regency/City, 2002

3-1Value of Loans from Commercial Banks (Including BRI Village Unit) by Research Location, 2002 (Billion Rupiah)

3-2Places of Deposit for Surplus Funds Mentioned by Non-Bank MFIs by Type of Institution (%)

3-3Places of Deposit for Surplus Funds Mentioned by Non-Bank MFIs by Regency / City (%)

3-4aInstitutions Mentioned by Non-Bank MFIs as Competitors in Granting Loans, by Type of Institution and Location (%)

3-4bInstitutions Mentioned by Bank MFIs as Competitors in Granting Loans, by Type of Institution and Location (%)

3-5aInstitutions Mentioned by Non-Bank MFIs as Competitor in Mobilizing Deposits by Type of Institution and Location (%)

3-5bInstitutions Mentioned by Bank MFIs as Competitors in Mobilizing Deposits, by Type of Institution and Location (%)

3-6Marketing 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 (%)

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TABLENO

TITLE

3-9 Financial Performance Ratios of the Sample Banks, 2000-2002

3- 10Ratio of Profi t / Loss to Credit Portfolio of Non-Bank MFIs by Type of Institution, 2000-2002 (%)

4-1aNumber of Accounts and Value of Deposits and Loans at Bank MFIs by Type of Bank, May 2002

4-1bNumber of Accounts and Value of Deposits and Loans at Non-Bank MFIs by Type of Institution, May 2002

4-2Number 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 (%)

4-4aMinimum, Maximum, and Median Values of Annualized Bank Saving Interest Rates and Cost of Funds by Type of Bank (%)

4-4bMinimum, Maximum, and Median Values of Annualized Non-Bank MFI Savings Interest Rates and Cost of Funds by Type of Institution (%)

4-5Minimum, Maximum, and Median Values of Annualized Interest Rates for Bank Micro Loans by Type of Loan and Type of Bank (%)

4-6Minimum, Maximum, and Median Values of Annualized Interest Rates for Non-Bank MFIs Micro Loans by Type of Loans and Type of Institution (%)

4-7Minimum, Maximum, Values of Annualized Interest Rates of Non-Bank MFIs by Type of Loan and Region (%)

4-8aNon-Bank MFIs that Specify Requirements for Loans by Type of Institution (%)

4-8bBank MFIs that Specify Requirements for Loans by Type of Bank (%)

4-9Median Savings Interest Rates, Loan Interest Rates, and Net Interest Margins of Bank and Non-Bank MFIs by Type of Bank and Institution (%)

4-10aRepayment Rate of Micro Loans at Bank MFIs by Type of Bank and Region (%)

4-10bRepayment 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 (%)

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TABLE NO

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 (%)

4-14bNon-Bank MFIs Mentioning Advantages of Female Customers over Males (%)

4-15aNon-Bank MFI Market Segments by Type of Institution and Location (%)

4-15b Bank MFIs Market Segments by Type of Bank and Location (%)

4-16aMicro Loans Accounts from Non-Bank MFIs by Economic Sector (%)

4-16b Micro Loans Accounts from Bank MFIs by Economic Sector (%)

5-1Average Number of Employees of Sample Banks by Type of Bank and Location

5-2Average Number of Bank Employees Involved with Micro Loans by Type of Bank and Location

5-3Time Allocated to Micro Loans by Bank AOs Who Perform Other Duties, by Type of Bank (%)

5-4Average Number of Non-Bank MFIs Employees by Type of Institution and Location

5-5Average Number of Non-Bank MFIs Employees Involved with Micro Loans by Type of Institutions and Location

5-6Time Allocated to Micro Loans by Non-Bank MFIs AOs Who Perform Other Duties by Type of Institution (%)

5-7Bank MFIs Stating Training is Adequate, by Type of Bank and Location (%)

5-8Bank MFIs that Provide Training Budget, by Type of Bank and Location (%)

5-9Non-Bank MFIs Whose Staff Receive Training, by Type of Institution and Location (%)

5-10Non-Bank MFIs Stating Training is Adequate, by Type of Institution and Location (%)

5-11Non-Bank MFIs that Pay for Staff Training Themselves, by Type of Institution and Location (%)

5-12MFIs Stating They Provide Incentives for Staff by Type of Bank and Type of Institution (%)

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TABLE NO

TITLE

5-13 Bank MFIs Using Computers by Level of Use and Type of Bank (%)

5-14Non-Bank MFIs Using Computers by Level of Use and Type of Institution (%)

5-15Non-Bank MFIs Using Certain Financial Records by Type of Institution (%)

5-16Cooperatives whose Management and Supervision Are Separate, by Regency / City (%)

5-17Non-Bank MFIs that State They Have Certain Manuals by Type of Institution (%)

5-18MFIs Stating Certain Requirements for Loans by Type of Bank and Type of Institution (%)

5-19aBank MFIs that Require Certain Guarantees by Type of Bank (%)

5-19bNon-Bank MFIs that Require Certain Guarantees by Type of Institution (%)

5-20Minimum Age of Business Requirements by Type of Bank and Type of Institutions (%)

5-21a Factors Given for Rejecting Loan Applications by Type of Bank (%)

5-21bFactors 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 (%)

5-22bNon-Bank MFIs Methods of Handling Bad Loans by Regency / City (%)

5-23Non-Bank MFIs Regularly Performing Internal Supervision by Type of Institution (%)

6-1BPR (Rural Bank) that Cooperated with Certain Institution by Location (%)

6-2Non-Bank MFIs that Cooperated with Certain Institution by Type of Institution and Location (%)

6-3BPRs in Various Forms of Cooperation with Other Institutions by Location (%)

6-4Non-Banks MFIs in Various Forms of Cooperation with Other Institution by Type of Institutions and Location (%)

6-5Non-Bank MFIs Producing Various Types of Report, by Type of Institution (%)

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TABLE NO

TITLE

6-6Non-Bank MFIs that Mention Certain Parties as Providers of External Supervision, by Type of Institution (%)

6-7Non-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

iComparison of Numbers of MFIs According to Reports of District Offi cials and Number in the Sample, 2002

iiNumbers of Micro Finance Institutions That Served as the Sample by Type of Institution and Province, 2002

iiiOverview of Proportion of Numbers of Research Regions Compared with Numbers of Regions in Indonesia and in the Unit Sample, January 2002

ivComparison of Actual Amounts in the Sample and Hypothetical Amounts of Loans of Non-Bank MFIs, by Regency/City

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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 Microfi nance 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

(Salary Deduction Authorization Letter)

TPSP Tempat Pelayanan Simpan Pinjam (Savings and Credit Service Post)

UED-SP Usaha Ekonomi Desa - Simpan Pinjam

(Village Economic Unit-Saving and Credit)

USP Unit Simpan Pinjam (Savings and Credit Unit of Cooperative)

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FOREWORD

In Indonesia, where more than 90% of all businesses are micro and small enter-prises, the question of how to encourage growth and job creation is a vital one in reducing vulnerability to poverty. Micro and small business owners frequent-ly 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 fi nancial institutions to service. This makes them unattractive to many private commercial lenders, few of whom target small borrowers. Instead, most small busi-ness borrowers in Indonesia obtain credit from a variety of microfi nance institu-tions (MFIs).

Indonesia has developed a vibrant microfi nance market, with 30 trillion rupiah in outstanding loans in 2002. While microfi nance is often considered a way of ex-tending fi nancial 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 fi nancial 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 fi ll 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 prov-inces. 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 fi nance 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 fi nancial 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 Offi cer, Economic Programs, The Asia Foundation, Indonesia

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I. INTRODUCTION

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BACKGROUND

The Asia Foundation has cooperated with the Center for Business and Govern-

ment of Harvard University (CBG-Harvard), which works for Bank Rakyat Indo-

nesia, to conduct a survey on access to and services of micro fi nance institutions

(MFIs) in six provinces: West Java, East Java, West Kalimantan, East Kalimantan,

North Sulawesi and Papua. The Asia Foundation conducted the survey of institu-

tions, consisting of banks and non-bank fi nancial 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 fi nance

services. Specifi cally, the aims of the survey were:

1. To evaluate the capabilities of MFIs in several regions of Indonesia. For this

purpose, an MFI was defi ned as an institution (bank or non-bank) that pro-

vides loans with a ceiling of Rp 50 million per customer. The meaning of

capability here includes effi ciency, 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 eco-

nomic sectors.

3. To evaluate the possibility and capability of MFIs to develop linkages with

larger fi nancial institutions.

4. To identify the problems faced by MFIs, though not to make recommenda-

tions to remedy them.

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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 ana-

lysis of several regions in Indonesia but were not intended to portray average con-

ditions 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 refl ecting

the characteristics of the province. These characteristics refl ected 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 ran-

dom, 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.

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.

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Province Regency (kab.)/City (kota)

District Village/Subdistrict

West Java Kab. Bandung Cililin 1. Situwangi 2.Kidang PananjungCimaung 1. Pasirhuni 2. SukamajuCimahi Tengah 1. Baros 2. Karang Mekar

Kab. Purwakarta Bojong 1. Cileunca 2. PasanggrahanPurwakarta 1. Babakan Cikao 2. Nagri KalerDarangdan 1. Sirnamanah 2. Linggamukti

East Java Kota Madiun Manguharjo 1. Nambangan Lor 2. SogatenKartoharjo 1. Klegen 2. KanigorTaman 1. Kejuron 2. Mojorejo

Kab. Malang Pagak 1. Pandanrejo 2. Pagak

Dampit 1. Bumirejo 2. Pojok

Wajak 1. Dadapan 2. Kidangbang

West Kalimantan Kota Pontianak Pontianak Barat 1. Pal Lima 2. MarianaPontianak Utara 1. Siantan Hilir 2. Siantan TengahPontianak Timur 1. Tanjung Hilir 2. Saigon

Kab. Sanggau Sekayam 1. Sotok 2. KenamanToba 1. Lumut 2. Belungai DalamKembayan 1. Sejuah 2. Tunggal Bhakti

East Kalimantan Kota Samarinda Samarinda Ulu 1. Teluk Lirong Ilir 2. Gunung KeluaSamarinda Ilir 1. Pulau Atas 2. SambutanSamarinda Utara 1. Lempake 2. Sungai Siring

Kab. Kutai Kertanegara

Tenggarong Seberang 1. Perjiwa 2. Embalut

Kotabangun 1. Kedang Ipil 2. Kotabangun UluMuara Muntai 1. Muara M. Ulu 2. Muara Leka

North Sulawesi Kota Manado Malalayang 1. Malalayang I 2. KleakWanea 1. Karombasam 2. WaneaMapanget 1. Buha 2. Paniki Bawah

Kab. Minahasa Pineleng 1. Kalasey I 2. Kalasey IITompaso Baru 1. Lowian 2. TemboanBelang 1. Soyowan 2. Watuliney

Papua Kota Jayapura Abepura 1. Nafri 2. AsanoJayapura Selatan 1. Entrop 2. HamadiJayapura Utara 1. Tanjung Ria 2. Angkasa Pura

Kab. Manokwari Babo 1. Simuri 2. Rarutu IIIRansiki 1. Iseren 2. DembekPrafi 1. Waseki 2. Waseki Indah

Table 1-1 Research Locations

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RESEARCH SAMPLE

1. Survey Population

The targets or respondents in this study can be grouped into three categories:

a. Banking fi nancial institutions identifi ed 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 net-

work 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 offi ces and Village Units), Bank BCA, Bank Danamon, and Bank

Bukopin. In addition to these, branch offi ces 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 fi nancial 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), Cre-

dit Unions, Savings and Loan Units/ Savings and Loan Facilities (Unit Sim-

pan-Pinjam/ Tempat Pelayanan Simpan-Pinjam, USP/TPSP), Micro Finance

Institutions/ MFI (Lembaga Keuangan Mikro, LKM), and others (such as Vil-

lage 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, Kop-

wan), 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 signifi cant bias.

3 In practice, there were almost no local commercial general banks identifi ed as possibly being involved in providing micro fi nance services, though there are some that do provide micro fi nance 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. Microfi nance Institution Study. GTZ-Bank of Indonesia-Ministry of Finance).

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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, whet-

her of fi nancial institutions or of micro, small, and medium-scale enter-

prises. These respondents included local Bank Indonesia Offi ces, Offi ces of the

Cooperatives and SME Service, Industry and Trade Service Offi ces, the Econo-

mic 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) Offi ces, and Village/ Subdistrict Heads.

2. Stages of Sample Collection

The collection of the sample of fi nancial institutions for this survey was done

in two stages, as follows:

Stage I : Identifying the types of fi nancial institutions present in the

research location. This was done by seeking data on the types and numbers

of fi nancial institutions, both banks (especially BPRs) and non-banks. Data

on types and numbers of banks were obtained from the local Bank Indonesia

offi ces, or those whose operational areas covered the research regions/loca-

tions. Data on numbers and types of cooperatives (including some BMTs and

MFIs), were obtained from the Cooperative and SME Service offi ces at the

regency/city level. Aside from these offi cial sources, the researchers also

obtained data and carried out inspections in the fi eld.

Stage II : Determining the quotas for each type of fi nancial institution to

be studied. From the research population described above, we determined

a quota for each type of fi nancial institution that was to serve as a research

respondent. The determination of these quotas was based on considerations

including the following:

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• To try to obtain as many respondents as possible from all types of fi nan-

cial institutions found in the research locations, both bank and non-bank,

so as to be able to represent the characteristics of each type of fi nancial

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 fi nancial institutions:

Because the number of banks was lower than that of non-bank fi nancial

institutions, the ones chosen as respondents were all branch offi ces of

the government banks (including BRI Units) and private banks that were

mentioned above, plus three to four BPR offi ces in each research loca-

tion. If there were more than four BPRs in a given research location, the

respondents were chosen at random.

• For non-bank fi nancial institutions:

The overall number of non-bank fi nancial 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 offi ces per type of non-bank fi nancial institu-

tion present in the regency capital or city; two to three offi ces per type of

such institution located in the districts; and two to three offi ces 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 fi nancial institution that were not

present in a given research location, the proportion of respondents of the other

types in that research location was increased.

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Type of InstitutionW e s t J a v a E a s t J a v a

BANDUNG PURWAKARTA Total MALANG MADIUN Total

BANKGovernment banks 2 2 4 3 3 6BPD 1 1 2 1 1 2Private banks . 1 1 2 1 3BPR 7 2 9 6 2 8BRI UNIT 3 6 9 3 3 6TOTAL BANK 13 12 25 15 10 25

NON BANKBMT 5 3 8 . 2 2KOPKAR 4 2 6 3 2 5KSP 3 3 6 5 18 23Other MFIs . 2 2 1 . 1PROGRAMs 7 2 9 . 1 1USP 9 18 27 9 15 24TOTAL NON-BANK 28 30 58 18 38 56

TOTAL ALL 41 42 83 33 48 81

Table 1-2a. Numbers of Bank and Non-Bank Respondents by Regency/City in West Java and East Java

3. Sample Size

Altogether, in this study 374 microfi nance institutions were interviewed, con-

sisting of 114 bank microfi nance institutions and 260 non-bank microfi nance

institutions. Looking at the distribution of the fi nancial institutions sampled in

this research, the largest samples were found in West Java and East Java: 83 and

81 fi nancial institutions, respectively. The smallest sample was found in West

Kalimantan: only 34 microfi nance institutions, comprised of 17 banks and 17

non-bank institutions. The entire research sample of fi nancial institutions, both

banks and non-banks, for the various provinces is shown in Tables 1-2a, 1-2b

and 1-2c below.

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Type of InstitutionNorth Sulawesi PAPUA

MINAHASA MANADO Total MANOKWARI JAYAPURA Total

BANKGovernment banks 1 3 4 3 3 6BPD . . . 2 1 3Private banks . 1 1 1 1 2BPR 2 . 2 . 2 2BRI UNIT 2 3 5 3 4 7TOTAL BANK 5 7 12 9 11 20

NON BANKBMT . 2 2 . . .KOPKAR . 1 1 . 2 2KSP 7 4 11 3 2 5Other MFIs 20 22 42 2 1 3PROGRAM 1 1 2 . . .USP 5 6 11 9 3 12TOTAL NON-BANK 33 36 69 14 8 22

TOTAL ALL 38 43 81 23 19 42

Table 1-2c. Numbers of Bank and Non-Bank Respondents by Regency/City in North Sulawesi and Papua

Table 1-2b. Numbers of Bank and Non-Bank Respondents by Regency/City in West Kalimantan and East Kalimantan

Type of InstitutionWest Kalimantan East Kalimantan

SANGGAU PONTIANAK Total KUTAI SAMARINDA Total

BANKGovernment banks 2 4 6 1 3 4BPD 2 1 3 2 1 3Private banks . 3 3 . 2 2BPR . 2 2 1 . 1BRI UNIT 1 2 3 2 3 5TOTAL BANK 5 12 17 6 9 15

NON BANKBMT 1 5 6 1 5 6KOPKAR . . . 4 1 5KSP 5 2 7 5 4 9Other MFIs . 2 2 1 3 4PROGRAMs . . . 2 . 2USP 2 . 2 4 8 12TOTAL NON-BANK 8 9 17 17 21 38

TOTAL ALL 13 21 34 23 30 53

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| Microfi nance Services in Indonesia | PROFILE OF THE RESEARCH AREAS

II. PROFILE OF THE RESEARCH AREAS

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In this section, brief profi les 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 profi les are presented at two le-

vels: 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. Physi-

cally, 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 fi nancial 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 mar-

ket for fi nancial 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

microfi nance institutions. Of course, the regencies have varying economic lev-

els: 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 microfi nance institutions in this study is evenly

distributed, and so there is a tendency toward an excess of samples in smaller and

less-developed regions.

26

AVAILABE FIGURES

The fi gures presented in this section come from offi cial 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 weak-

nesses, 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 defi nitions 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 refl ect 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 fi nancial development, which is on the whole a

characteristic of regions in East Java.

27


PROVINCE/REGENCY/CITY AREA Population Population

Density GRDP GRDP/CAPITA Number of Jurisdictions

(KM2) (Million) (PER KM2) (Million Rupiah) Regencies/Cities Districts Villages/

Subdistricts

West Java 30,517 36.9 1,210 187,090,585 5.07 24 545 5,758

Bandung 2,452 4.3 1,768 17,314,502 3.99 1 43 436

Purwakarta 723 0.7 1,002 5,226,905 7.21 1 17 192

East Java 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

West Kalimantan 120,488 4.2 35 19,737,236 4.74 10 134 1,439

Pontianak 110 0.5 4,380 4,849,839 10.04 1 4 23

Sanggau 18,276 0.6 32 2,232,811 3.79 1 22 241

East Kalimantan 211,440 2.6 11 86,242,138 33.61 13 101 1,299

Samarinda 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

Manado 198 0.4 1,960 2,374,328 6.12 1 9 87

Minahasa 4,397 0.8 183 3,454,183 4.30 1 38 527

Papua 287,242 2.2 8 23,877,110 10.75 14 181 3,507

Jayapura 433 0.2 407 1,096,092 6.21 1 4 31

Manokwari 23,155 0.2 9 878,664 4.08 1 17 569

Indonesia 1,472,014 203.4 138 1,433,970,000 7.05 376 4,838 68,816

Table 2-1 Background Data on Research Locations, 2001/2002

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.

28

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 Deposits 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

West Kalimantan 6,357 2,822 793 38 34

Pontianak 4,390 1,280 433 N/A N/A

Sanggau 196 374 92 N/A N/A

East Kalimantan 11,825 5,094 1,004 11 14

Samarinda 4,870 1,647 368 N/A N/A

Kutai Kutainagara N/A 627 N/A N/A N/A

North Sulawesi 3,642 2,641 1,411 26 42

Manado 2,590 1,146 N/A N/A N/A

Minahasa N/A 502 N/A N/A N/A

Papua 4,455 657 434 N/A N/A

Jayapura N/A 196 164 N/A N/A

Manokwari N/A 73 43 N/A N/A

Total Regencies 23,251 20,642 3,343 N/A N/A

Source : Bank IndonesiaNote: N/A: No data AvailableAll data are for April 2002, except for West Kalimantan, January 2002

29


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

Purwakarta 10.6 45.9 25.0 76.9 21.3 1.8 504,145 730,712

East Java

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

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 2.4 31.9 29.4 54.1 37.1 8.8 383,877 78,265

Kutai K. 10.8 2.5 3.1 67.6 28.8 3.6 303,278 90,855

North Sulawesi

Manado 3.3 7.1 26.3 38.6 49.1 12.3 298,594 560,345

Minahasa 32.0 7.8 10.5 61.4 34.7 3.9 599,831 23,075

Papua

Jayapura 9.1 6.8 13.9 43.2 46.6 10.2 118,732 N/A

Manokwari 57.0 6.7 7.0 83.8 14.5 1.7 129,456 18,061

Table 2-3 Economic and Social Indicators in Research Locations 2001/2002

Source : BPSNote: Data on Gross Regional Domestic Product (GRDP) are for 2001, while data on Indonesia’s population are 2002

30

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 offi cially split into two provinces with the estab-

lishment 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 overfl ow from the city. These two regions show a very strong con-

trast in terms of their local economies. Development of the fi nancial sector in West

Java is somewhat behind that of East Java, but fi nancial services in West Java are

better than in the other four research location provinces.

Table 2-4 Numbers of Financial Institutions (Bank and Non-Bank) in Sample by Regency/City, 2002Table 2-4 Numbers of Financial Institutions (Bank and Non-Bank) in Sample by Regency/City, 2002T

Source: fi eld survey (processed)

Province/Regency/City

Sample Data

BanksTotal

BanksNon

BanksNational Banks Non-BRI Unit BRI Unit BPR

West Java

Bandung 3 3 7 13 28

Purwakarta 4 6 2 12 30

East Java

Malang 6 3 6 15 18

Madiun 5 3 2 10 38

West Kalimantan

Pontianak 8 2 2 12 9

Sanggau 4 1 0 5 8

East Kalimantan

Samarinda 6 3 0 9 21

Kutai K. 3 2 1 6 17

North Sulawesi

Manado 4 3 0 7 36

Minahasa 1 2 2 5 33

Papua

Jayapura 5 4 2 11 8

Manokwari 6 3 0 9 14

Total 55 35 24 114 260

31


In comparison, the remaining four provinces in this study represent smaller popu-

lations and many of them have very low population densities. However, low popu-

lation 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 Kaliman-

tan, 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 fl ows and a certain amount of smug-

gling. 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 respec-

tive provinces. In the rural regions of Kalimantan, the level of fi nancial develop-

ment is generally low, although West Kalimantan has a Credit Union movement

that is quite infl uential 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 north-

ernmost tip of the island of Sulawesi, is a relatively wealthy region with a well-edu-

cated population. However, North Sulawesi’s infrastructure is rather poor, and its

fi nancial 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 provin-

ce 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 edu-

cated. The second-level administrative regions serving as samples in Papua are

both coastal regions. Development of fi nancial institutions in this region is quite

limited. Conditions in Papua are also widely affected by security disturbances.

33

| Microfi nance Services in Indonesia | PROFILE OF MICRO FINANCE INSTITUTIONS

III. PROFILE OF MICRO FINANCE INSTITUTIONS

35


SCOPE OF THE FINANCIAL INSTITUTION SAMPLE

1. Overview of Micro Finance Institutions

A wide variety of microfi nance institutions (MFIs) provide fi nancial intermedia-

tion for small-scale borrowers in Indonesia, and this is also so in the locations stud-

ied 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 defi ned as loans of up to 50 million Rupiah). The commercial bank branches’

major role is in saving services, and micro fi nance is only a small part of their

activities.

The two types of banks that are the major exceptions are BRI Village Units (BRI Vil-

lage 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 mil-

lion 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 out-

standing 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 supervi-

sion, 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.

36

Non-bank fi nancial institutions are often in the form of cooperatives, but some-

times also in the form of Programs, that is, government entities, which are usu-

ally sponsored by non-governmental organizations (NGOs) and the government.

In the fi eld, 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 fi nancial activities

– moneylenders (loan sharks), rotating savings clubs (arisan), and so on – that are

not within the scope of this study. Nearly all the microfi nance institutions in this

study provide consumption loans to their clients.

Most cooperatives are registered in various forms with the Cooperatives Depart-

ment, 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 busi-

Province Regency(Kab.)/City(Kota) Loans Small Loans

West Java 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

West Kalimantan 2,822 793

Kota Pontianak 1,280 433

Kab Sanggau 374 92

East Kalimantan 5,094 1,004

Kota Samarinda 1,647 368

Kab Kutai Kartenagara 627 N/A

North Sulawesi 2,641 1,411

Kota Manado 1,146 N/A

Kab Minahasa 502 N/A

Papua 657 434

Kota Jayapura 196 164

Kab Manokwari 73 43

Table 3-1. Value of Loans from Commercial Banks (Including BRI Village Unit) by Research Location, 2002 (Billion Rupiah)

Source: Monthly statistics of various branches of Bank IndonesiaNote: All data are from April 2002, except that West Kalimantan is for January

37


ness cooperatives. USPs are required to maintain separate fi nancial 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

specifi c institutions (Koperasi Karyawan, Kopkar). This was done because of the

signifi cant differences between them in terms of behavior, although their legal

status is the same.

No precise fi gures are available about the activities of cooperative MFIs. Coopera-

tives’ 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-Re-

liant 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 fi ve 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 Cri-

sis (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 re-

search sample. It is diffi cult to discuss other forms of MFIs with any certainty, be-

cause 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.

38

2. MFIs in the Research Sample

The data in the following discussion are based on a stratifi ed 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 select-

ed, and from each of these, three districts were selected. In each of these districts,

two villages/subdistricts were selected; however, in the fi eld this was not carried

out completely. A more detailed discussion of the sample selection process is pre-

sented 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 interdepen-

dence between non-bank MFIs and banks. Through this mechanism, the MFIs also

benefi t from the differential between the banks’ interest rates and the interest rates

the MFIs pay their clients.

39


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 offi ce.

Type of InstitutionPlace of Deposit

Higher Offi ce General Bank BPR Other

BMT 4.2 62.5 4.2 45.8Kopkar 0.0 84.2 0.0 42.1KSP 16.4 57.4 3.3 21.3Other MFIs 0.0 41.5 0.0 50.9Programs 0.0 28.6 14.3 42.9USP 4.6 56.8 4.6 30.7All Non-Banks 6.2 54.6 3.5 35.4

Table 3-2. Places of Deposit for Surplus Funds Mentioned by Non-Bank MFIs by Type of Institution (%)

Source: Field survey (processed)

The variation in place of deposit of surplus funds occurs not only by type of institu-

tion, 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 offi ce. 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

offi ces, in Madiun only “other” is mentioned as a signifi cant 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.

40

COMPETITION

It is not easy to assess the level of competition in the microfi nance 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 refl ect a low level of com-

petition. 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 signifi cant 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

25 percent state that the BPRs’ competitors are Village Unit Cooperatives (KUD).

Regency(Kab.)/City(Kota)

Place DepositHigher Offi ce General Bank BPR Bank Indonesia Other

Kab Bandung 0.0 50.0 17.9 7.1 46.4Kab Purwakarta 0.0 66.7 3.3 0.0 43.3Kab Malang 5.6 66.7 0.0 11.1 11.1Kota Madiun 5.3 39.5 2.6 2.6 34.2Kab Sanggau 50.0 12.5 0.0 0.0 37.5Kota Pontianak 0.0 77.8 11.1 0.0 55.6Kab Kutai 11.8 70.6 5.9 0.0 29.4Kota Samarinda 9.5 76.2 0.0 4.8 23.8Kab Minahasa 3.0 45.5 0.0 0.0 45.5Kota Manado 2.8 47.2 0.0 0.0 38.9Kab Manokwari 2.4 42.9 0.0 0.0 21.4Kota Jayapura 0.0 87.5 0.0 0.0 12.5

Table 3-3. Places of Deposit for Surplus Funds Mentioned by Non-Bank MFIs by Regency/City (%)


41


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 fi nd a kind of asymmetry in perception regarding com-

petition between non-bank MFIs, specifi cally 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.

Type of Institution

C o m p e t i t o r I n s t i t u t i o n s

BKDUSP/

TPSP/KUD

KSP Other MFIs

Loan Sharks

BRI Units

Private BPRs

Regional Govt BPRs

BPRSyariah

General Banks

BMT:• All Cities• All Regencies• All Locations

0.00.00.0

0.00.00.0

28.630.029.2

7.110.08.3

75.740.037.5

7.120.012.5

0.00.00.0

0.00.00.0

0.00.00.0

0.00.00.0

Kopkar:• All Cities• All Regencies• All Locations

0.07.75.3

0.07.75.3

0.07.76.3

16.77.7

10.5

16.716.415.8

16.723.121.1

0.00.00.0

0.07.75.3

0.00.00.0

0.015.410.5

KSP:• All Cities• All Regencies• All Locations

3.33.23.3

3.36.54.9

13.319.416.4

10.03.26.6

26.712.919.7

3.312.98.2

6.712.99.8

0.03.21.6

0.00.00.0

0.03.21.6

Other MFIs:• All Cities• All Regencies• All Locations

3.60.01.9

0.08.03.8

25.028.026.4

14.344.028.3

26.08.0

17.0

3.64.03.8

0.00.00.0

0.00.00.0

0.00.00.0

3.60.01.9

Programs:• All Cities• All Regencies• All Locations

0.00.00.0

0.00.00.0

0.016.714.3

0.00.00.0

0.050.042.9

0.016.714.3

0.00.00.0

0.08.37.1

0.00.00.0

0.00.00.0

USP:• All Cities• All Regencies• All Locations

6.30.02.3

0.05.43.4

15.621.419.3

3.11.82.3

34.423.227.3

6.319.614.8

3.11.82.3

0.05.43.4

0.00.00.0

0.03.62.3

All Non-Bank:• All Cities• All Regencies• All Locations

3.61.42.3

0.95.43.5

17.920.919.6

8.910.19.6

26.620.924.2

6.416.211.5

2.73.43.1

0.04.12.3

0.00.00.0

0.93.42.3

Table 3-4a. Institutions Mentioned by Non-Bank MFIs as Competitors in Granting Loans, by Type of Institution and Location (%)


42

Meanwhile, in mobilization of public savings, the signifi cant competitors to non-

bank institutions are BRI Village Units, general banks, and KSPs. It must be re-

membered 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.

Type of Institution

C o m p e t i t o r I n s t i t u t i o n s

BRI Branches

BRI Units

Bank Mandiri BPD BCA Private

BPRsBPR

Syariah BKD KUD KSP

Government Bank:• All Cities• All Regencies• All Locations

47.445.546.7

31.627.330.0

36.836.436.7

52.681.863.3

42.19.1

30.0

21.127.323.3

0.00.00.0

0.00.00.0

5.30.03.3

15.80.0

10.0BPD:• All Cities• All Regencies• All Locations

40.062.553.8

60.037.546.2

20.025.023.1

0.00.00.0

0.012.57.7

20.012.515.4

0.00.00.0

0.00.00.0

0.00.00.0

20.012.515.4

Private Banks:• All Cities• All Regencies• All Locations

88.966.783.3

44.40.0

33.3

33.366.741.7

33.333.333.3

11.10.08.3

33.333.333.3

0.00.00.0

0.00.00.0

0.00.00.0

11.10.08.3

BPR:• All Cities• All Regencies• All Locations

33.311.16.7

83.383.383.3

33.30.08.3

66.722.233.3

16.716.716.7

50.077.870.8

0.05.64.2

16.75.68.3

16.727.825.0

16.761.150.0

BRI Village units:• All Cities• All Regencies• All Locations

13.35.08.6

6.70.02.9

13.315.014.3

86.735.057.1

13.320.017.1

33.335.034.3

0.00.00.0

0.00.00.0

13.330.022.9

26.750.040.0

All Bank:• All Cities• All Regencies• All Locations

42.625.033.3

35.235.035.1

27.818.322.8

55.635.044.7

22.215.018.4

29.643.336.8

0.01.70.9

1.91.71.8

7.418.313.2

18.536.728.1

Table 3-4b. Institutions Mentioned by Bank MFIs as Competitors in Granting Loans, by Type of Institution and Location (%)


43


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.

Type of Institution

C o m p e t i t o r I n s t i t u t i o nBKD USP/

TPSP/KUD

KSP Other MFIs

Loan Sharks

BRI Units

Private BPRs

Regional Govt.BPRs

BPRSyariah

General Banks


0.00.00.0

0.00.00.0

14.310.012.5

7.110.08.3

35.720.029.2

0.050.020.8

0.00.00.0

0.00.00.0

0.00.00.0

21.40.0

12.5


0.07.75.3

0.07.75.3

16.77.7

10.5

0.07.75.3

0.00.00.0

0.038.526.3

0.00.00.0

0.00.00.0

0.00.00.0

33.323.126.3


3.30.01.6

0.06.53.3

6.719.413.1

3.30.01.6

6.76.56.6

10.022.616.4

3.33.23.3

0.03.21.6

0.00.00.0

23.39.7

16.4


3.60.01.9

0.04.01.9

3.616.09.4

17.916.017.0

0.00.00.0

14.332.022.6

0.00.00.0

0.00.00.0

0.00.00.0

7.18.07.5


0.00.00.0

0.00.00.0

0.08.37.1

0.00.00.0

0.08.37.1

0.033.328.6

0.00.00.0

0.016.714.3

0.00.00.0

0.00.00.0


3.10.01.1

0.03.62.3

3.117.912.5

0.01.81.1

15.510.712.5

15.526.822.7

0.00.00.0

0.01.81.1

0.00.00.0

21.910.714.8


2.70.71.5

0.04.12.3

6.315.511.5

6.34.75.4

10.77.48.8

10.730.421.9

0.90.70.8

0.02.71.5

0.00.00.0

18.89.5

13.5

Table 3-5a. Institutions Mentioned by Non-Bank MFIs as Competitor in Mobilizing Deposits by Type of Institution and Location (%)


44

Type of Institution

C o m p e t i t o r I n s t i t u t i o n

BRI Branches

BRI Units

Bank Mandiri BPD BCA Private

BPRsBPR

Syariah BKD KUD KSP

Government banks:• All Cities• All Regencies• All Locations

36.836.436.7

5.336.416.7

52.654.553.3

21.172.740.0

63.227.350.0

15.818.216.7

0.00.00.0

0.00.00.0

5.20.03.3

5.30.03.3

BPD:• All Cities• All Regencies• All Locations

40.075.061.5

40.037.538.5

60.037.546.2

0.00.00.0

80.025.046.2

0.012.57.7

0.00.00.0

0.00.00.0

0.00.00.0

0.00.00.0

Private banks:• All Cities• All Regencies• All Locations

55.633.350.0

0.00.00.0

100.066.791.7

22.266.733.3

44.40.0

33.3

11.133.316.7

0.00.00.0

0.00.00.0

0.00.00.0

11.10.08.3


33.311.116.7

66.777.875.0

16.70.04.2

50.022.229.2

33.350.045.8

16.766.754.2

16.711.112.5

0.05.64.2

16.716.716.7

16.744.437.5

BRI Village Unit:• All Cities• All Regencies• All Locations

20.010.014.3

0.00.00.0

33.315.022.9

66.735.048.6

40.030.034.3

26.730.028.6

0.00.00.0

0.00.00.0

6.730.020.0

6.735.022.9


35.225.029.8

13.035.024.0

51.923.336.8

35.235.035.1

51.933.342.1

16.736.727.2

1.93.32.6

0.01.70.9

5.615.010.5

7.425.016.7

Table 3-5b. Institutions Mentioned by Bank MFIs as Competitors in Mobilizing Deposits, by Type of Institution and Location (%)


Another difference between competition in savings versus lending is the appearan-

ce 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 microfi nance institutions in

terms of deposits, but not in terms of loans.

45


It should also be noted that if a certain type of institution is mentioned by non-

bank institutions as a competitor but with only a very low percentage (for example,

BPR Syariah), there are two possible explanations: fi rst, 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 refl ected 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 there-

fore presented in the form of a range.

MARKETING

1. Marketing Methods

Incentives for staff to engage in marketing will be discussed in Chapter 5. Mean-

while, Table 3-6 below shows the various marketing methods employed by non-

bank MFIs, both for savings and for loans. The table shows that there are two cat-

egories 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 specifi c methods to market their savings facilities. Most likely,

this means is chosen because it is considered the most effi cient, as the geographic

area of operation of non-bank MFIs is usually not very large.

46

Type of Institution

Marketing Methods

Leafl ets 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

For Loans:

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 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

Table 3-6. Marketing Methods Mentioned by Non-Bank MFIs for Savings and for Loans, by Type of Institution (%)


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 market-

ing. 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 (leafl ets). For both savings and loans, BMTs are the non-bank MFIs that use

leafl ets the most in their marketing.

47


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, signifi cant

variations can be seen between regions. This survey at the fi nancial 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 lower-

middle 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.


Stating Potential Exists (%)

Socio-economic Group (%)

Highest Upper Upper Middle

Lower Middle Lower Lowest

Kab Bandung 53.4 20.0 20.0 20.0 33.3 80.0 86.7

Kab Purwakarta 83.3 4.0 8.0 16.0 48.0 76.0 48.0

Kab Malang 88.9 6.0 6.0 35.4 35.4 47.2 29.5

Kota Madiun 79.0 16.7 20.1 30.1 56.7 83.4 73.4

Kab Sanggau 75.0 50.0 50.0 50.0 83.3 100.0 100.0

Kota Pontianak 88.9 37.5 50.0 50.0 75.0 100.0 100.0

Kab Kutai 64.7 18.2 18.2 27.3 63.6 72.7 81.8

Kota Samarinda 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

Table 3-7. Non-Bank MFIs Stating Potential Exists for Savings, by Regency/City (%)


48

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 refl ects the high

level of demand for micro loans in several regions.

The lowest fi gure 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.


Stating Potential Exists %

Socio-economic Group (%)

Agriculture Trade Small Industries Services Civil

Servants Other

Kab Bandung 78.6 71.4 46.4 56.6 56.6 30.5 4.4

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 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

Table 3-8. Non-Bank MFIs Stating Potential Exists for Loans, by Regency/City (%)


49


PROFITABILITY AND SUSTAINABILITY

1. Indicators of Banks’ Financial Performance

Return on Equity (ROE), the ratio between profi t and capital, which is the measure

generally used to measure a bank’s fi nancial 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 diffi cult 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 microfi -

nance institutions that can be used specifi cally 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 fi gure

tended to remain stable between 2000 and 2002, in the 0.4 to 0.5 range.

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

Table 3-9. Financial Performance Ratios of the Sample Banks, 2000-2002


2. Performance Indicators for Non-Banks

Because of various limitations to the data as explained in the Appendix, the perfor-

mance ratios used for banks cannot be applied to non-bank fi nancial institutions. The

indicator that is appropriate, and comparable to ROA, is the ratio of profi t 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 profi tability of non-bank fi nancial institutions

during the period 2000-2002. The table shows that the institutions with relatively

high and stable levels of profi tability were Other MFIs and USPs. The profi tability

50

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 profi tability of 35 percent but in the other years observed

(2000 and 2002) never reached 10 percent.

Quite interesting is the change in profi tability of Programs (which usually man-

age 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 opera-

tion, but then deteriorate. In a number of cases, the rate of repayment of revolv-

ing funds declined when the borrowers learned that the funds were derived from

grants. In other words, the factor of moral hazard strongly infl uences the fi nancial

performance of Programs.

Type of Institution December 2000 December 2001 December 2002

BMT 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

Table 3-10. Ratio of Profi t/Loss to Credit Portfolio of Non-Bank MFIs, by Type of Institution, 2000-2002 (%)


51

| Microfi nance Services in Indonesia | SERVICES PROVIDED

IV. SERVICES PROVIDED

53


This section is a discussion of exactly what services are provided by microfi nance

institutions, both banks and non-banks, the distribution of services by several cri-

teria, and the requirements related to these microfi nance services.

TYPES OF SERVICES

The banking sector provides many types of fi nancial 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 fi -

nancial 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 microfi nance institutions are

considered in the context of development of micro enterprises. In this context, at-

tention will be focused mainly on the micro loans granted by the various fi nancial

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 microfi nance 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 differ-

54

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 fi nancial

institutions, which offer specifi c types of products.

Non-bank MFIs typically provide a limited range of services, particularly with re-

gard 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 member-

ship, as well as voluntary deposits, for which various incentives are provided.

As with banks, in practice it is not easy to differentiate between mandatory savi-

ngs and voluntary savings, because the counter-deposit requirements (savings re-

quired 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 fi nancial

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 classi-

fi ed into two categories: standard loans (like those normally granted by banks) and

loans of the government program type.

55


1. Numbers and Values of Savings Accounts and Loans

Table 4-1 shows the numbers of accounts and values of savings and loans in vari-

ous 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 refl ecting their differing orientations. Some insti-

tutions 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.

Type of Bank

Savings Loans

Accounts(000)

Value(Rp.000.000)

Value/Account(Rp.000)

Accounts(000)

Value(Rp.000.000)


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

BRI Units 214.4 186,655.4 870.6 34.5 142,878.3 4,136.8

Table 4-1a. Number of Accounts and Value of Deposits and Loans at Bank MFIs by Type of Bank, May 2002


56

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 occasion-

ally not consistent with one another: data from responses to direct questions on

deposits and loans, and data from balance sheets.

Regency(Kab.)/City(Kota.)

Savings Loans

Accounts(000)

Value(Rp.000.000)


Accounts(000)

Value(Rp.000.000)


Kab Bandung 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

Kota Pontianak 18.5 27,229.1 1,473.2 17.0 24,668.8 1,455.1

Kab Kutai 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

Table 4-2. Number of Accounts and Value of Deposits and Loans in Non-Bank MFIs by Regency / City, May 2002 (%)


1 In reality, not all non-bank MFIs provide “full” services (savings and loans); some provide only savings, while others provide only loans.

Type of Bank

Savings Loans

Accounts(000)

Value(Rp.000.000)


Accounts(000)

Value(Rp.000.000)


BMT 7.5 1,864.7 247.6 2.8 1,758.2 624.8Kopkar 9.3 1,957.1 210.3 3.6 1,761.6 483.2KSP 2 36.8 31,626.2 858.3 34.1 35,213.3 1,031.6Other MFIs 3.1 1,432.2 459.6 2.7 1,316.1 493.7Program 1.7 78.2 47.3 2.4 3,504.4 1,446.9USP 33.4 6,221.2 186.3 17.6 9,214.3 522.4


Table 4-1b. Number of Accounts and Value of Deposits and Loans1 at Non-Bank MFIs by Type of Institution, May 2002

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

57


Analogous to the discussion by type of institution, the research regions can also

be divided into two groups. The fi rst 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 require-

ment 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 Jaya-

pura. Generally, the results of fi eld 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.

Type of Bank

Banks With Group Lending % Government

Group Lending Program

Number of Banks

Proportion (%)

Government banks (n=30) 14 47 79

BPD (n=13) 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

Table 4-3a. Banks MFI and Group Lending, by Type of Bank


58

Table 4-3 shows that in all around 30 percent of the clients of non-bank institu-

tions 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 fi rst 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 infl uence loan interest rates and, in turn, the demand for credit.

Calculation using currently effective interest rates is diffi cult, 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 fi nancial 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

the exception of BPRs, the interest rates of non-bank institutions are higher than

Type of BankType of Customer

Individual Group Total

BMT 83.2 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 4-3b. Type of Customers of Non-Bank MFIs by Type of Institution (%)


59


Type of InstitutionSavings Interest Rates

Min Max Median Average Cost of Fund*

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

Table 4-4a. Minimum, Maximum, and Median Values of Annualized Bank Savings Interest Rates and Cost of Funds by Type of Bank (%)

* Data on cost of funds is average fi gure from respondents estimatesSource: Field survey (processed)

Type of InstitutionSavings Interest Rates

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

Table 4-4b. Minimum, Maximum, and Median Values of Annualized Non-Bank MFIsSavings Interest Rates and Cost of Funds by Type of Institution (%)

* Data on cost of fund is average fi gure from respondents estimatesSource: Field survey (processed)

bank interest rates. However, it should also be noted that certain non-bank institu-

tions (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.

60

4. Loan Interest Rates

As explained above, interest rates are a central issue in discussions on microfi -

nance 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 com-

parison, aside from BPRs, the highest interest rates are charged by government

banks, at 26 percent (for working capital credits and investment credits).

Type of BankWorking Capital Investment Other

Min Max Med Min Max Med Min Max Med

Government banks 6.0 26.0 19.0 16.0 26.0 20.0 12.0 24.0 19.5

BPD 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

Table 4-5. Minimum, Maximum, and Median Values of Annualized Interest Ratesfor Bank Micro Loans by Type of Loan and Type of Bank (%)


For non-banks, the interest rates charged to micro loan customers vary tremen-

dously; 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 sig-

nifi cant amounts of funds.

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.

61


RegencyWorking Capital Other

Min Max 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

Table 4-7. Minimum, Maximum, Values of Annualized Interest Rates of Non-Bank MFI Loans by Type of Loan and Region (%)


It is also interesting to compare the loan interest rates of non-bank micro

fi nance institutions by regions. The hypothesis proposed is that loan inter-

est 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 fi eld. Interest rates in Malang

regency (East Java), for example, are relatively low, but so are those in Pontianak

(West Kalimantan).

Type of BankWorking Capital Other

Min Max Med Min Max Med

BMT 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

Table 4-6. Minimum, Maximum, and Median Values of Annualized Interest Ratesfor Non-Bank MFI Micro Loans by Type of Loan and Type of Institution (%)


62

5. Loan Administration Fees

Table 4-8 gives a picture of the costs that must be borne by customers when they

borrow money from fi nancial 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 admin-

istration 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 fi xed

rates, while for others, these fees are a percentage of the value of the loan. For fi xed

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.

Type of Institution 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

Table 4-8a. Non-Bank MFIs that Specify Requirements for Loans by Type of Institution (%)

63


Type of Bank Administration Fees Insurance Fees Notary Fees Mandatory

Savings


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

Table 4-8b Bank MFIs that Specify Requirements for Loans by Type of Bank (%)

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 no-

tary 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.

6. Savings Requirements for Loans

In addition to fi nancial 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.

64

A slightly higher percentage of banks require borrowers to open savings accounts.

This once again confi rms that banks impose relatively greater burdens on borrow-

ers 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 inter-

est 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 non-

bank institutions is higher than that of banks. It should be noted that the net inter-

est margin cannot automatically be interpreted as a profi t earned by the institu-

tion, because it could well be that a high margin is caused by high operating costs.

Type of Bank/Institution

Median Savings Interest

Median Loan Interest Rates

Net Interest Margin

Bank:

• Government banks 10.5 19.5 9.0

• BPD 9.0 16.0 7.0

• Private banks 9.5 20.0 10.5

• BPR 12.0 30.0 18.0

• BRI Units 9.5 24.0 14.5

• All Bank 10.8 21.0 10.2

Non Bank:

• 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

• Programs 9.6 24.8 15.2

• USP 12.0 30.6 18.6

• All Non-Bank 15.0 29.6 14.6

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 (%)


65


Type of Bank Cities Regencies All Locations

Government banks 93.9 97.6 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 4-10a. Repayment Rate of Micro Loans at Bank MFIs by Type of Bank and Region (%)


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 fi nancial 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 10b presents information on the loan repayment rate in non-bank fi nancial

institutions. Compared with banks, the level of loan repayment at non-bank insti-

tutions is lower, only around 93 percent. Among the non-bank fi nancial institu-

tions, the lowest loan repayment rate is seen in USPs.

66

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

Table 4-10b. Repayment Rate of Micro Loans at Non-Bank MFIs by Type of Institution and Region (%)

GEOGRAPHICAL COVERAGE

1. Geographical Coverage of Services

With regard to the geographical extent of MFIs’ service networks, there is a tremen-

dous variation between regencies in terms of numbers of institutions and of cus-

tomers. Services are generally more intensive in urban regions than in regencies.

Furthermore, services are also more limited in many regions outside Java. Manok-

wari (Papua) and Sanggau (West Kalimantan) are the regions whose microfi nance

institutions have the fewest services.

In fact, variation is even found within districts; more micro fi nancial services are

found in district capitals than in villages far from the district capitals. This is indi-

cated by the fact that in around half of the villages surveyed, there were no micro-

fi nance institutions.


67


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 defi ned

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 fi ll

a market not yet reached by traditional banking services.

Type of Institution > 1 Regency/City

District up to Regency

Village up to

District1 Village TOTAL


30.80.0

17.4

53.820.039.1

7.740.021.7

7.740.021.7

100.0100.0100.0


40.015.422.2

40.030.538.9

0.046.233.3

20.00.05.6

100.0100.0100.0


50.06.5

27.9

30.035.532.8

8.725.816.4

13.332.323.0

100.0100.0100.0


11.50.05.8

15.40.07.7

19.219.219.2

53.880.863.3

100.0100.0100.0


50.00.07.1

0.06.37.1

0.041.735.7

50.050.050.0

100.0100.0100.0


25.08.9

14.8

46.919.829.5

6.348.233.0

21.923.222.7

100.0100.0100.0


30.66.1

16.4

34.320.328.2

9.337.225.4

25.936.532.0

100.0100.0100.0

Table 4-11. Distribution of Non-Bank MFIs by Operational Area (%)


68

Table 4-11 shows a signifi cant 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 microfi nance institutions located in cities have more extensive op-

erational 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 re-

search 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.

69


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 fi nan-

cial institutions do not specifi cally 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.

Regency(kab.)/City(kota)

Target Groups

Women MenBoth

women and men

Total

Kab Bandung 0.0 3.6 96.4 100.0

Kab Purwakarta 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 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

Table 4-12. Non-Bank MFIs Target Group by Regency/City (%)


70

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 fi gure is for private banks.

Type of MFIsWomen (%)

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

Non-Bank

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

Table 4-13. Outstanding Loans and Savings Accounts held by Women by Type of MFI (%)


71


Table 4-14a shows that in general, in cases when a difference in character is con-

sidered to exist between male and female customers, female customers are con-

sidered superior to male customers. They are said to be better in promptness of

repayment of loan installments, easier to collect from, and more honest.

Type of Bank Prompter Payers

Usually have fi xed business

Easier to collect from More honest


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

Table 4-14a. Bank MFIs Mentioning Advantages of Female Customers over Males (%)


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


72


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 fi gure is for Other

MFIs (Figure 4-2).

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 respon-

dents felt that women are better in terms of prompt payment of loan installments,

ease of collection, and honesty (Table 4-14b).

Type of Bank Prompter payers

Usually have fi xed 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

Table 4-14b. Non-Bank MFIs Mentioning Advantages of Female Customers over Males (%)


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

73


2. By Socioeconomic Strata

It has been mentioned in other sections of this report that non-bank MFIs are an al-

ternative for the poor and/or micro enterprises to obtain fi nancial 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 profi tability is believed to

infl uence banks’ unwillingness to channel micro credits.

Table 4-15a shows that this indication is not far off the reality in the fi eld. 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 offi ces, and private com-

panies 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 of-

ten states that the lower stratum is their target group (80%), while the lowest fi gure

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 diffi cult to relate to actual socio-economic data. However, a loan of Rp 50

million (defi ned 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.

74

Type of InstitutionSocial Stratum

Upper Middle-Upper Middle Middle-

Lower Lower


7.10.04.2

0.00.00.0

64.310.041.7

100.090.095.8

78.680.079.2


0.023.115.8

33.330.831.6

33.369.257.9

100.069.278.9

50.038.542.1


16.79.7

13.1

26.712.919.7

63.348.455.7

90.083.986.9

66.783.975.4


3.63.83.7

14.311.513.0

32.138.535.2

71.488.579.6

78.688.583.3

Program:• All Cities• All Regencies• All Locations

0.00.00.0

0.00.00.0

50.025.028.6

100.091.792.9

50.0100.092.9


6.314.311.4

21.916.118.2

59.437.545.5

90.683.986.4

87.567.975.0


8.010.19.2

18.813.515.8

52.739.945.4

87.584.585.8

75.975.775.8

Table 4-15a. Non-Bank MFI Market Segments by Type of Institution and Location (%)


75


Type of InstitutionSocial Stratum

Upper Middle-Upper Middle Middle-

Lower Lower


16.727.320.7

27.827.327.6

66.763.665.5

94.490.993.1

44.463.651.7


16.70.07.1

16.70.07.1

66.750.057.1

100.087.592.9

66.775.071.4


11.166.725.0

11.166.725.0

77.8100.083.3

77.866.775.0

44.40.0

33.3


0.016.712.5

66.744.450.0

83.355.662.5

100.088.991.7

50.061.158.3

BRI Units:• All Cities• All Regencies• All Locations

0.025.014.3

6.720.014.3

73.365.068.6

93.385.088.6

80.080.080.0


9.321.715.8

22.228.325.4

72.261.766.7

92.686.789.5

57.466.762.3

Table 4-15b. Bank MFI Market Segments by Type of Bank and Location (%)


76

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 fi ve 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 fl ow is

rapid, and profi t 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 de-

mand side, not many farmers are interested in borrowing money from MFIs, prob-

ably 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 fi nancing the productive sector, because the larg-

est 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).

77


The situation for banks turns out to be consistent with what happens with non-

banks, 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 sec-

tor. 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 fi gures are small) are BPRs and BRI Units.

Type of InstitutionEconomic Sector

Trade Agriculture Industry Services Other TOTAL


59.339.552.7

12.21.08.5

18.317.418.0

8.442.119.6

1.80.01.2

100.0100.0100.0


68.80.0

34.4

0.00.00.0

12.50.06.3

12.50.06.3

6.3100.053.1

100.0100.0100.0


57.129.345.8

7.725.515.0

11.613.012.1

14.55.9

11.0

9.726.316.8

100.0100.0100.0


33.756.545.9

3.19.06.3

32.15.7

18.0

11.114.112.7

19.916.918.4

100.0100.0100.0


49.043.144.8

0.816.912.3

47.33.8

16.2

3.016.312.5

0.020.014.3

100.0100.0100.0


69.842.955.2

4.911.88.7

15.614.014.7

5.710.28.1

4.124.915.3

100.0100.0100.0


58.640.149.4

6.113.79.9

18.111.714.6

9.812.010.9

7.725.116.3

100.0100.0100.0

Table 4-16a. Micro Loan Accounts from Non-Bank MFIs by Economic Sector (%)


78

Type of InstitutionEconomic Sector

Trade Agriculture Industry Services Other TOTAL


43.032.038.2

13.90.88.1

1.60.51.1

3.76.85.1

37.660.07.5

100.0100.0100.0


41.17.8

24.4

3.80.72.3

12.70.36.5

9.60.75.1

32.890.561.7

100.0100.0100.0


26.925.026.5

4.20.03.4

5.80.04.7

1.48.32.8

61.666.762.6

100.0100.0100.0

BPR :• All Cities• All Regencies• All Locations

43.648.747.1

12.412.012.1

6.81.63.3

8.88.48.5

28.429.529.2

100.0100.0100.0

BRI Units:• All Cities• All Regencies• All Locations

39.448.745.0

8.815.312.9

2.73.23.0

19.14.4

10.2

33.228.430.2

100.0100.0100.0


39.741.840.9

9.810.310.1

4.12.13.0

10.45.67.8

37.340.339.0

100.0100.0100.0

Table 4-16b. Micro Loan Accounts from Bank MFIs by Economic Sector (%)


microfinance services in indonesia: a survey of institutions in six

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