Image by John Ritter

In the 50 years since modern microfinance was introduced as a tool to fight poverty, institutions have distributed hundreds of millions of loans to people in developing countries. Such loans are repaid at rates often as high as 98 percent. Those metrics alone seem to tell a convincing story about the sector’s success, but to what extent have the loans meaningfully improved livelihoods? That question has been more difficult to track, say Natalia Rigol and Ben Roth. Both development economists and assistant professors at HBS, Rigol and Roth are among the academics searching for solutions to make the next generation of microfinance tools even more transformative.

One of the great surprises of microfinance has been the astonishingly high rates of loan repayment, at around 96 or 98 percent. How do you interpret that?
Ben Roth: One metric of success is just financial inclusion; and perhaps the fact that there are new borrowers who are taking loans and repaying them is evidence enough that this sector has had enormous impact. But another view that we’re also deeply sympathetic to is that, 30 years into the microfinance story, around 2005 and 2010, some large-scale, randomized control studies started to emerge that all showed the same surprisingly lukewarm message about the impact of microfinance on livelihoods.

Natalia Rigol: People expected to see shifts in household income, business growth, and consumption, but across the board these experiments found no movement, on average. It was quite controversial. When we tell microfinance practitioners about this evidence, it can be hard for them to really engage with it because of their work on the ground and the anecdotes they hear about lives that have been transformed.

Roth: Meanwhile, there’s a parallel body of work that tells a very different story. In randomized control trials all over the world, instead of giving access to a loan, a one-time cash grant was found to have transformative impacts on livelihoods and businesses six months, one year, five years, ten years later. We learned from those studies that there are many small-business owners who could put capital to very good use, but microfinance has not yet unlocked those potential opportunities.

How are these findings shaping your work?
Roth: There are two strands of research that form the basis of our conviction about how microfinance could do better. One is about the timing of repayment obligations. The standard microfinance contract has very little discretion in terms of when you repay your loan, so Natalia and her collaborators did one of the earliest studies to look at what happens if we relax that requirement and let people wait up to two months to repay their first installment. People who got the more flexible contract invested significantly more in their businesses and earned higher returns as a result. Their businesses were bigger three years later, and they are still bigger now, ten years later. That paper was very influential and one of the first indications to academics that small changes to the structure of microfinance contracts could have big consequences for how people spend the money and its impact on their businesses and their livelihoods.

When they have a grace period, how do people use that time and capital differently?
Rigol: Giving people more time up front allows them to better match the cash flows of their business with their repayment obligations. If you are a tailor and you’re switching from sewing by hand to using a sewing machine, you have to learn how to use the machine and make sure your customers are going to like the products that you’ll produce with the sewing machine. The grace period afforded people the time to make significant investments like that.

The second strand of our work is developing new ways to identify which borrowers have high-growth opportunities. Microfinance often operates in environments that are information-scarce, in terms of screening borrowers. Ten years ago, India didn’t have social security numbers, so that is a first-order constraint. We have been going to the neighborhoods where these entrepreneurs live, forming them into groups, and asking people which of their neighbors have the most potential to grow their business.

Roth: About 10 years ago, Natalia and I did a randomized experiment in western India, where we gave out $100 cash grants to a random set of microentrepreneurs. We found that the return on investment to a random entrepreneur in the community is about 8 percent per month, which is a big effect in terms of livelihood generation. But the people who were nominated by their community as high-growth entrepreneurs had a 25 percent monthly return on investment, and the people who weren’t nominated averaged no return at all. That was our first signal that some of these alternative screening mechanisms based on soft information could transform how we think about which entrepreneurs to target with larger or more flexible loans.

Are these findings making their way into practice?
Roth: Not very quickly, so we are working with a microfinance institution in India called Sanghamithra Rural Financial Services to figure out how to operationalize these insights. We have developed two credit products with Sanghamithra that are based on these ideas, and we’ve just deployed the first few dozen of each of them.

The first is a graduation loan. For many borrowers, it’s hard to get a formal bank loan that’s more than $1,200 but less than $10,000, so we’ve been identifying borrowers from Sanghamithra who have demonstrated that they can handle loans of $1,200—and then we’re using community information to figure out which of them could handle loans up to five times that amount. (Larger sums may help them take the next step in growing their business.) These borrowers are already organized in groups, so there’s a community of people that knows them very well. We do a variety of formal and informal interviews to understand who they’d feel comfortable taking a bet on, and then we do a lot of work with the borrower to come up with a personalized repayment schedule that matches their cash flows.

Rigol: We’ve given out about 20 loans so far, and we’re planning to run a randomized evaluation to understand the impact of these kinds of loans on livelihoods. But this is not a research-first project; it is a practice-first project. One of our principal motivations is to develop a set of loan products that will not only help people grow their livelihoods but also to do so in a manner that is profitable and therefore scalable.

Roth: The second product that we’re working on is a loan for market vendors who often rely on informal working capital loans at exorbitant interest rates. Vendors have volatile cash flows, and the one-size-fits-all microfinance repayment model is not a good fit. We are developing a loan product that matches their cash flows, with a repayment schedule between a day and a month. The loans start small but grow as borrowers demonstrate good repayment. They’ve been very popular.

Rigol: A year ago, when CEOs of microfinance institutions heard about these ideas, their response was, “You guys are nuts, but it would be amazing if you can figure this out.” So far, we have good repayment, and the idea that we are bringing new innovations and risk capital to the industry has piqued a lot of curiosity.

So with these products you’re bridging the gap between research and practice?
Rigol: Well, it’s a big gap, and we’re small people. But we believe in these ideas, and we’re trying to validate them beyond what’s done by traditional academic papers.

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