Ratan Mf Tech Path Bmgf
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Transcript of Ratan Mf Tech Path Bmgf
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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 than the IT sector. (Vikram Akula, SKS; Source CSO, 2004-05)
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Urban Rural
>$2000/year
$1-2000/year
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Outline
Microfinance and development
Demand
Supply ICTs and microfinance
Nature of problems
Appropriate solutions
Aishwarya Ratan, MSR India, March 2007
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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
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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
24-120%APR
0-60%APR
Aishwarya Ratan, MSR India, March 2007
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So they turn to a variety of old and new
providers to fill the gap
Microfinance targets urban and rural low-income (
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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. 2003
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but these are declining.
Direct formal credit to Small Borrowing Accounts (
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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 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
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5members
Current models of microfinance delivery
12-20members24-36%APR
NGOfacilitator
Cooperative
RS.@ 9-12% APR
The group is the MFIInterest accrues to member-borrowers~33 mn outreach in IndiaLess profitableMore welfare focused flexible paymentsMost common model in India
Commercial
RS.
RS.
@ 9-12% APR
@ 24-36% APR
External provider is the MFIInterest accrues to 3rd party intermediary~8 mn outreach in IndiaMore profitableMore commercially focused EMI paymentsMost common model worldwide
MFI
Aishwarya Ratan, MSR India, March 2007
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Can ICTs enable microfinance?
Front-end IS1. Account creation (loan, savings
& insurance)
1. Collecting client data
2. Screening/ verification
2. Transaction data
3. Processing claims (savings,
transfers & insurance)
E-/M-paymentsEnabling cashless transactions
1. Disbursal of amount (loan)2. Collection of dues/ payments (loan, savings & insurance)3. Transfers
Back-end IS1. Aggregation of client data
1. Actuarial analysis
2. Target offerings
GRAMEENTECHNOLOGY
CENTRE
CGAP
Aishwarya Ratan, MSR India, March 2007
m-banking
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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 createsustainable business model
MethodsHave an Accountant with a PC serve a Federation ofSHGsCharge nominal fee for data processing serviceUse manual transport to ferry data back and forth
ResultsWeekly meeting time cut by halfInstant evaluation of financial performance of largegroup of SHGs possible
Original workflow
Improved workflow
(90,000 rural clients, EAST/CENTRAL India)
Weekly collections
Book-keeping done locallyAnnual auditing by NGO
Weekly collections
Copy of transactionrecord put in drop-box
CM updates records &prints balances & dues
Annual auditing by NGO
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Can ICTs enable microfinance?
Front-end IS1. Account creation (loan, savings
& insurance)
1. Collecting client data
2. Screening/ verification
2. Transaction data
3. Processing claims (savings,
transfers & insurance)
Back-end IS1. Aggregation of client data
1. Actuarial analysis
2. Target offerings
GRAMEENTECHNOLOGY
CENTRE
Aishwarya Ratan, MSR India, March 2007
m-bankingE-/M-payments
Enabling cashless transactions1. Disbursal of amount (loan)2. Collection of dues/ payments (loan, savings & insurance)3. Transfers CGAP
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MSRI Urban pilot with UJJIVAN
Customer Profile formfilled on paper in field
Branch Manager ApprovalPost all forms to Head Office
Head Office entersinfo to database
Piles of extra paper andmoney gone to waste
Customer is approved!
Problem areaNew Customer Profile Creation
IssuesCosts associated with:
Double data entry Error correction Data transport
Stationery Back-office staff
ExperimentGoals
Reduce costs Improve client data quality
MethodsSimple mobile-phone application to
record client data in fieldData transmission via SMS
Automatic upload of data into databaseusing a smart phone SMS-server
Existing workflow
Customer Profile formfilled electronically infield
Manager Approval
Customer is approved!
SMS all forms to Head Office
Improved workflow
COSTSAVINGS?-Low labour cost-Relative efficiency
(25,000 urban clients, SOUTH India)
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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 ICTs in enabling microfinance greatly depends ondelivery model, operational efficiency and labour/ technology costs
Hybrid, cost-aware approaches and accurate matching of device withtarget functionality are key
Photo sources: CCD Mahakalasam & Ekgaon; PRADAN
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Others involved:
Ujjivan and Pradan staff & members, Shabnam Aggarwal,
Mahesh Gogineni, Sean Blagsvedt, Kentaro Toyama, Vibhore Goyal,
Jonathan Donner, Indrani Medhi, Rajesh Veeraraghavan
Thanks!