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On microfinance (and technology)

On microfinance (and technology). “Dhobis (washermen), tailors and barbers contribute more to the GDP of Andhra Pradesh than the IT sector.” (Vikram Akula, SKS; Source CSO, 2004-05). Aishwarya Ratan, MSR India, March 2007. Our reference segment. Low income households

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On microfinance (and technology)

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  1. On microfinance (and technology) “Dhobis (washermen), tailors and barbers contribute more to the GDP of Andhra Pradesh than the IT sector.” (Vikram Akula, SKS; Source CSO, 2004-05) Aishwarya Ratan, MSR India, March 2007

  2. Our reference segment Low income households Both rural and urban areas Rural Urban >$2000 /year 29 $1-2000 /year 17 <$1000 /year 8 Photo source: CCD Mahakalasam & Ekgaon Data source: NCAER Aishwarya Ratan, MSR India, March 2007 © 2007 Microsoft Corporation Source: Indian National Survey Sample Organization 2001-2002 HH survey

  3. Aishwarya Ratan, MSR India, March 2007 Outline • Microfinance and development • Demand • Supply • Technology and microfinance • Nature of problems • Appropriate solutions

  4. Sustenance (40%) Fulfill basic consumption Protect against shocks Access lump sums for lifecycle needs Growth (60%) Enterprise (30%) Buildup assets: education, home (30%) Aishwarya Ratan, MSR India, March 2007 The poor use finance for growth and survival … Survey of 64 LI & LMI urban and rural HHs, 2006

  5. Aishwarya Ratan, MSR India, March 2007 … but face very high prices for finance. • No ‘acceptable’ collateral/ surety • No unique ID • No record of previous borrowings/ repayments • Irregular income flows • Low literacy 9-12% APR 0-60% APR 24-120% APR

  6. Aishwarya Ratan, MSR India, March 2007 So they turn to a variety of old and new providers to fill the gap… • Microfinance targets urban and rural low-income (<$2000 annual HH income) clients • Uses joint-liability social contracts • Provides affordable finance Banks, Insurance co.s Employers, relatives, neighbors. friends Moneylenders, pvt financiers Microfinance Institutions 18% 37% 16% 4% 26% Formal Semi – Formal Informal 1-on-1 personal Informal 1-on-1 impersonal Informal mutual (Chit funds ) Survey of 64 LI & LMI urban and rural HHs, 2006

  7. India used to offer targeted financial services to the poor & excluded… Priority Sector Lending The 1:4 rule for bank branch expansion Aishwarya Ratan, MSR India, March 2007 Growth of Bank Branches in India Source: Burgess and Pande, “Do Rural Banks Matter? Evidence from the Indian Social Banking Experiment.” 2003

  8. … but these are declining. Direct formal credit to Small Borrowing Accounts (<$600 credit accounts) has shrunk since early 90s: Number of SBAs: 62 mn (1992)  37 mn (2001) Net Banking Credit to SBAs: 25% (1980s) 5% (2003) Aishwarya Ratan, MSR India, March 2007 Banks’ reasons: • High transaction costs in finding and servicing small-ticket clients at high frequency • Regulatory cap on prices banks can charge • Profitability vs. outreach (post-liberalization)

  9. Aishwarya Ratan, MSR India, March 2007 Hence the rising importance of the microfinance industry, characterised by… • High growth • India: $4 mn lent (1995-96) to >$2.8 bn(2006-07) • High potential growth • India: Market size estimated at $16-22 bn • Large outreach • India: >33 mnHHs • Large number of players • India: >3000 MFIs • Few industry leaders • Only 1% of providers WW fully financially self-sustaining

  10. Aishwarya Ratan, MSR India, March 2007 Current models of microfinance delivery Commercial Cooperative RS. NGO facilitator RS. @ 9-12% APR @ 9-12% APR MFI 12-20 members RS. @ 24-36% APR 24-36% APR 5 members External provider is the MFI Interest accrues to 3rd party intermediary ~8 mn outreach in India More profitable More commercially focused – EMI payments Most common model worldwide The group is the MFI Interest accrues to member-borrowers ~33 mn outreach in India Less profitable More welfare focused – flexible payments Most common model in India

  11. Aishwarya Ratan, MSR India, March 2007 Can technology enable microfinance? Front-end IS • Account creation (loan, savings & insurance) • Collecting client data • Screening/ verification • Transaction data • Processing claims (savings, transfers & insurance) Back-end IS • Aggregation of client data • Actuarial analysis • Target offerings GRAMEEN TECHNOLOGY CENTRE m-banking • E-payments • Enabling cashless/ electronic payments • Disbursal of amount (loan) • Collection of dues/ payments (loan, savings & insurance) CGAP

  12. Aishwarya Ratan, MSR India, March 2007 Case: PRADAN’s Computer Munshi experiment Original workflow (90,000 rural clients, EAST/CENTRAL India) • Problem area • Poor quality of financial data • No aggregate record • Issues • Costs associated with: • Time spent on accounting each week • Mistakes discovered at annual audit • Experiment • Goals • Improve SHG data quality & aggregate data • Outsource weekly accounting function – create sustainable business model • Methods • Have an Accountant with a PC serve a Federation of SHGs • Charge nominal fee for data processing service • Use manual transport to ferry data back and forth • Results • Weekly meeting time cut by half • Instant evaluation of financial performance of large group of SHGs possible Annual auditing by NGO Book-keeping done locally Weekly collections Improved workflow Copy of transaction record put in drop-box CM updates records & prints balances & dues Weekly collections Annual auditing by NGO

  13. Pradan’s ‘Computer Munshi’ system (SHG) Rs. 30/ SHG/ mth 1 100-200 SHGs 1 12b 4 5 CM Peon Drop box 30-50 SHGs 6 2 3 1 7 2 14 12a 2 2 8 13 Rs. 3/ SHG/ wk 2 9 11b 11a 10 1 15 or Cluster meeting PRADAN (NGO)

  14. Aishwarya Ratan, MSR India, March 2007 Can technology enable microfinance? Front-end IS • Account creation (loan, savings & insurance) • Collecting client data • Screening/ verification • Transaction data • Processing claims (savings, transfers & insurance) Back-end IS • Aggregation of client data • Actuarial analysis • Target offerings GRAMEEN TECHNOLOGY CENTRE m-banking • E-payments • Enabling cashless/ electronic payments • Disbursal of amount (loan) • Collection of dues/ payments (loan, savings & insurance) CGAP

  15. Aishwarya Ratan, MSR India, March 2007 MSRI Urban pilot with UJJIVAN Existing workflow (25,000 urban clients, SOUTH India) • Problem area New Customer Profile Creation • Issues • Costs associated with: • Double data entry • Error correction • Data transport • Stationery • Back-office staff • Experiment • Goals • Reduce costs • Improve client data quality • Methods • Simple mobile-phone application to record client data in field • Data transmission via SMS • Automatic upload of data into database using a smart phone SMS-server Post all forms to Head Office Customer Profile form filled on paper in field Branch Manager Approval • COST SAVINGS? • Low labour cost • Relative efficiency Head Office enters info to database Customer is approved! Piles of extra paper and money gone to waste Improved workflow Customer Profile form filled electronically in field Manager Approval SMS all forms to Head Office Customer is approved!

  16. Have a balanced appreciation of microfinance as one of many ‘killer apps’ to target poverty and/ or promote growth The value-addition of technology in enabling microfinance greatly depends on delivery model, operational efficiency and labour/ technology costs Hybrid, cost-aware approaches and accurate matching of device with target functionality are key Aishwarya Ratan, MSR India, March 2007 Key take-aways Photo sources: CCD Mahakalasam & Ekgaon; PRADAN

  17. Others involved:Ujjivan and Pradan staff & members, Shabnam Aggarwal, Mahesh Gogineni, Sean Blagsvedt, Kentaro Toyama, Vibhore Goyal, Jonathan Donner, Indrani Medhi, Rajesh Veeraraghavan Thanks! ? aratan@microsoft.com

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