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On microfinance (and technology) Aishwarya Ratan, MSR India, March 2007 Dhobis (washermen), tailors and barbers contribute more to the GDP of Andhra Pradesh.

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Presentation on theme: "On microfinance (and technology) Aishwarya Ratan, MSR India, March 2007 Dhobis (washermen), tailors and barbers contribute more to the GDP of Andhra Pradesh."— Presentation transcript:

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

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

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

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

5 … 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 % APR 0-60% APR Aishwarya Ratan, MSR India, March 2007

6 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 18%37%26%4%16% FormalSemi – FormalInformal 1-on-1 personal Informal 1-on-1 impersonal Informal mutual (Chit funds ) Survey of 64 LI & LMI urban and rural HHs, 2006 Banks, Insurance co.s Microfinance Institutions Employers, relatives, neighbors. friends Moneylenders, pvt financiers Aishwarya Ratan, MSR India, March 2007

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

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) 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) Aishwarya Ratan, MSR India, March 2007 Banks reasons:

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

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

11 Can technology enable microfinance? Front-end IS 1.Account creation (loan, savings & insurance) 1.Collecting client data 2.Screening/ verification 2.Transaction data 3.Processing claims (savings, transfers & insurance) E-payments Enabling cashless/ electronic payments 1.Disbursal of amount (loan) 2.Collection of dues/ payments (loan, savings & insurance) Back-end IS 1.Aggregation of client data 1.Actuarial analysis 2.Target offerings GRAMEEN TECHNOLOGY CENTRE CGAP Aishwarya Ratan, MSR India, March 2007 m-banking

12 Case: PRADANs Computer Munshi experiment 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 Original workflow Improved workflow (90,000 rural clients, EAST/CENTRAL India) Weekly collections Book-keeping done locally Annual auditing by NGO Weekly collections Copy of transaction record put in drop-box CM updates records & prints balances & dues Annual auditing by NGO Aishwarya Ratan, MSR India, March 2007

13 Pradans Computer Munshi system (SHG) Drop box or a 1412a 13 11b 12b 15 PRADAN (NGO) CMPeon Cluster meeting Rs. 30/ SHG/ mth Rs. 3/ SHG/ wk SHGs SHGs

14 Can technology enable microfinance? Front-end IS 1.Account creation (loan, savings & insurance) 1.Collecting client data 2.Screening/ verification 2.Transaction data 3.Processing claims (savings, transfers & insurance) E-payments Enabling cashless/ electronic payments 1.Disbursal of amount (loan) 2.Collection of dues/ payments (loan, savings & insurance) Back-end IS 1.Aggregation of client data 1.Actuarial analysis 2.Target offerings GRAMEEN TECHNOLOGY CENTRE CGAP Aishwarya Ratan, MSR India, March 2007 m-banking

15 MSRI Urban pilot with UJJIVAN Customer Profile form filled on paper in field Branch Manager Approval Post all forms to Head Office Head Office enters info to database Piles of extra paper and money gone to waste Customer is approved! 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 Existing workflow Customer Profile form filled electronically in field Manager Approval Customer is approved! SMS all forms to Head Office Improved workflow COST SAVINGS? -Low labour cost -Relative efficiency (25,000 urban clients, SOUTH India) Aishwarya Ratan, MSR India, March 2007

16 Key take-aways 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 Photo sources: CCD Mahakalasam & Ekgaon; PRADAN Aishwarya Ratan, MSR India, March 2007

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!


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