Trust and Microfinance in Poor Communities in Peru
We evaluate a novel microfinance model in which new customers need to gain sponsorship by an existing customer. We investigate how relationships between individuals and social networks impact repayment behaviour. This individual lending program screens clients and enforces good practices much in the same way as more traditional group lending does, but allows microcredit to be extended to those who might not qualify or be interested in a group liability loan.
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Microfinance has generated worldwide enthusiasm as a potential catalyst for economic development and poverty reduction. The success of microcredit in providing access to capital without increasing default rates, despite a lack of physical collateral, was originally attributed to the group liability model, in which groups of people are jointly responsible for one another’s loans. However, as the microfinance industry grows and becomes more competitive, institutions must strive to develop new financing methodologies that keep institutional costs low while also extending access to credit. A major problem in microfinance is reaching borrowers who don’t qualify for or are not interested in communal, group liability, banks. Thus, different microfinance structures are needed that reach the poor with individual loans, while still harnessing some of the screening and enforcement benefits of group lending.
Since returning to democratic leadership in 1980, Peru has struggled to regain economic stability and growth. Currently, 44% of its 29 million people live in poverty.1 This plight has driven many rural residents to the outskirts of Lima in search of work, where they make their homes in self-built shantytowns that surround the city’s center. These shantytowns now contain a large proportion of Lima's inhabitants, and their residents have limited access to formal financial services such as savings accounts or loans. This study is located in fairly diverse shanty communities in Ancash, just north of Lima. The economy of these communities is primarily based on mining of gold, copper and zinc and fishing.
In collaboration with PRISMA, a Peruvian NGO offering credit through village banks, researchers designed and implemented a new loan product and administered surveys to 9,000 shantytown households. This program sought to use social connections to screen for responsible clients, outside of the traditional group lending model, by requiring new clients to match up with sponsors who were already bank clients in order to obtain a loan.
Existing communal bank members acted as a pool of potential sponsors who can cosign small, individual loans for residents of the community who are not already bank members. The sponsor was responsible for repaying a loan if the client defaulted, and thus they were incentivized to cosign with more responsible individuals whom they could easily monitor. Each adult household member in the village received a card, which outlined the rules of the program and included a list of all sponsors in the community as well as a map of the community showing sponsor location. Both spouses of a sponsoring household and a borrowing household had to act as co-signers.
The two pilot shantytown communities consisted of 282 households with 26 sponsors, and 371 households with 25 sponsors, respectively. Social network surveys conducted in the communities before the implementation of the loan program allowed researchers to map the relationships between clients and sponsors. Researchers measured the strength of connections between individuals by time spent together per week, and whether individuals were considered trustworthy. Interest rates were randomly assigned between 3% and 5% a month across all client-sponsor pairs, in order determine whether the interest rate or the social distance from one’s sponsor had a greater impact on the likelihood of default.
Reporting early results from the two pilot communities, researchers found that close social relationships and geographic closeness between sponsor and client effectively improves trust between agents, reducing the likelihood of default and the risk of cosigning such a loan. Estimates of the relative effectiveness of interest rates and social connections at reducing defaults suggest that lending with a close neighbor reduces the likelihood of default by the same amount as a 3-4 point decrease in the interest rate.
These findings underscore the prediction on which the program was founded, namely that borrowers with close social relationships to their sponsors allow the bank to be more certain that this new client will repay their loan. Increased information from close social relationships ensures the sponsor, and thus the lender, knows what risk each client represents, and can act to minimize that risk. This individual program therefore effectively screens clients and enforces good practices much in the same way group lending does, and allows microcredit to be extended to those who might not qualify or be interested in a group liability loan.
1 CIA World Factbook, “Peru,” https://www.cia.gov/library/publications/the-world-factbook/geos/pe.html.