1 Dean Yang University of Michigan The BASIS Smart Development Pilot Project Agenda Matching Financial with Technological Innovations.

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Presentation transcript:

1 Dean Yang University of Michigan The BASIS Smart Development Pilot Project Agenda Matching Financial with Technological Innovations in Southern Africa

Fertilizer per acre on maize, central Malawi Note: Per-hectare fertilizer recommendation for central Malawi is 150 kg urea and 100 kg 23:21 (per acre: ~60kg urea, ~40 kg 23:21).

Raising farm output with rural finance Facilitate credit to buy fertilizer Encourage farmers to save for their own fertilizer purchases 3

Raising farm output with rural finance Facilitate credit to buy fertilizer –Improve repayment via biometric identification Encourage farmers to save for their own fertilizer purchases –Help farmers to save by offering “commitment” savings accounts 4

Raising farm output with rural finance Facilitate credit to buy fertilizer –Improve repayment via biometric identification Encourage farmers to save for their own fertilizer purchases –Help farmers to save by offering “commitment” savings accounts 5

Low credit supply in rural Malawi Most farmers cannot obtain credit because lenders find rural lending unprofitable 74% of farmers we surveyed have not borrowed from a bank/MFI in the last 10 years 6

Identification problems in rural lending Difficulties in identification lead to repayment problems for MFIs –Borrowers default, then take new loans under other names Easier when multiple lenders operate in same area A main problem: lack of a national identification system and credit bureau –Can’t sanction defaulters by excluding them from future lending –Good borrowers can’t prove they are reliable –Upshot: limited credit supply to rural areas 7

Biometrics and loan repayment Fingerprinting could help in future identification, in absence of a national ID system Helps lenders identify past defaulters –Within own institution –Across banks (requires pooling of credit reporting and sharing of fingerprint database) Research question: can fingerprinting of borrowers raise repayment? If so, may raise lending profitability and encourage lenders to expand rural lending 8

Project set up Loans to ~1,200 paprika farmers in central Malawi –Dowa, Dedza, Mchinji, Kasungu Malawi Rural Finance Company (MRFC) provides loans of ~MK 17,000 for paprika seeds, fertilizer and chemicals 50% of paprika clubs are randomly selected to be fingerprinted –Use of fingerprints explained to farmers –Aids in identification of defaulters as well reliable borrowers A “field experiment”, analogous to a medical trial with randomized treatment and control groups –Funded by World Bank and USAID 9

Fingerprinting Farmers fingerprinted in August and September

Demonstrating fingerprint identification 11

Packing paprika for sale 12

Treatment vs. control comparisons Treatment group: farmers fingerprinted in August- September 2007 (prior to loan application) Control group: all other farmers in sample Note: all farmers were given same education module emphasizing importance of credit history 13

Summary of learnings from experiment Biometric fingerprinting can raise repayment rates –Overall, repayment rises from 80% to 88% –Particularly for borrowers with the lowest likelihood of repayment (the “worst” borrowers) –For the worst borrowers, repayment rate more than triples (rises from 26% to 88% ) In response to fingerprinting, worst borrowers use more inputs (esp. fertilizer) and do more cash sales No substantial effects for “better” borrowers 14

Treatment (fingerprinted) vs. control TreatmentControlDifference Total borrowed (MK) 16,584 17, Repayment by Sep. 30 Balance (MK) 1,726 2, % paid88%80%8% 15

Repayment: % of balance paid by Sep

Repayment: balance as of Sep. 30 (MK) 17

Policy implications Biometric identification can raise repayment rates, particularly for the “worst” borrowers If resources for biometrics are scarce, focus on areas with worse repayment performance But impacts likely to be larger when: –Credit bureau established to share information across lenders Prevents defaulters from taking new loans from other lenders –System has been in place for longer, so that farmers observe system in practice 18

Strategies for raising farm output Facilitate credit to buy fertilizer –Improve repayment via biometric identification Encourage farmers to save for their own fertilizer purchases –Help farmers to save by offering “commitment” savings accounts 19

Vicious circles in input or credit subsidies Input/credit subsidies needed 20 Higher harvest income Earnings dissipated prior to next season

Breaking the vicious circle with savings Input / credit subsidy 21 Saving for future input purchases Input purchases without subsidy Savings + subsidy allows more input purchases Higher harvest income

The agricultural cycle in Malawi May June July August September October November December January February March April 22 Harvest Rainy season Planting “Hungry season”

The agricultural cycle in Malawi May June July August September October November December January February March April 23 Harvest Rainy season Planting Savings needed here “Hungry season”

Commitment savings Idea: –Let farmers specify amounts to be placed in special accounts –Farmers can specify date at which they regain access to funds (no access prior to release date) Helps farmers with their self-control problems Also may help farmers resist demands from relatives and friends Further help to farmers: direct deposit –Keep cash out of hands entirely 24

Implementation Offer farmers opportunity to have cash crop proceeds direct deposited into: –Ordinary accounts –“Commitment” accounts Offer 1-2 months before harvest –Before temptation sets in 2008 pilot in Malawi shows high demand for commitment accounts Follow-up work in 2009 and beyond: –Malawi –Mozambique 25

2008 test results among paprika farmers S.No.Name Amount in ordinary savings a/c Amount in commitment savings a/c Date for commitment account 1.Maliko Chithumba 2.Najele Munganyade 3.Samson Kawone15,00010,000Oct. 20, Kachepsya Chiwolagaga 7,0005,000Nov. 25, Waiti Bunayi15,00010,000Nov. 10, Mangani Fikisoni10,0009,000Nov. 7, Masauko Janga 8.Pusaikaziyo Fumu5,000 Oct. 30, Jekeseni Yeduwadi 10.Macdonald Lusitiko 11.Bulaka Sanuni25,0005,000Oct. 1, Greya Chiweza7,00018,000Nov. 5, Edward Jekeseni10,0005,000Nov. 30, Patili Mtemwende6,0005,000Feb. 5, Labisoni Shilingi4,0006,000Oct. 30, 2008

In sum New strategies for improving rural finance in Malawi show considerable promise Biometric fingerprinting raises repayment rates, particularly for the “worst” borrowers – Challenge will be implementing on a wider scale, and actually using fingerprint data for screening Commitment savings can help farmers “self-finance” their input needs –Much evidence of demand for the product –But impact still to be determined 27