borrowers originally offered the flexible loan (Flex→Flex group) and those offered the standard loan (Std→Flex group). This lack of selection effects suggests the lender would not grow its client base much if it offered flexibility to new clients (although longer-term results, particularly given positive customer feedback, may indicate that more time and spreading of information would lead to stronger client acquisition). In addition, first-time borrowers of the flexible loan had higher default rates and limited downstream benefits. These results can help explain why lenders offer rigid loans, particularly to new clients.

Our sample includes _only_ new clients. This is both a feature and a wart. Studying new clients is important for a more complete understanding of credit markets for small-scale entrepreneurs as they may lack experience with managing simultaneous cash flows and repayments. On the other hand, we cannot compare our results to those of more veteran borrowers studied in the literature discussed above, and our study’s context differs from that of prior work in more than one way (see Appendix Table 1 for an overview of some salient features). We believe the comparison of new versus veteran clients is an important line of inquiry for future research on loan contract flexibility.

The epilogue to the study is indicative of a broader challenge. The lender viewed the use of passes as a simple way of handling repayment difficulties and introduced a modified version of the flexible loan for non-study loans. Crucially, however, only credit officers (and not clients) decided when to use a pass and clients were not made aware of the feature ahead of time. Pass use thus became merely a tool for credit officers to adjust default and pursue enforcement and refinancing when needed.

While such a policy may have its merits, it deviates from the goal of a product that allows borrowers, fearful of default, to take on higher-risk higher-return investments with the comfort of knowing they have some flexibility to repay. We see these results as motivating, for both lenders and researchers, to continue to learn more about how products can better “match cash flows” both with respect to timing and risk.

# **References**

Ahlin, Christian, Selim Gulesci, Andreas Madestam, and Miri Stryjan. 2020. “Loan Contract Structure and Adverse Selection: Survey Evidence from Uganda.” _Journal of Economic Behavior & Organization_ 172 (C): 180–95.

- Armendariz de Aghion, Beatriz, and Jonathan Morduch. 2010. _The Economics of Microfinance_ . 2nd ed. Cambridge, MA: MIT Press.

- Athey, Susan, Julie Tibshirani, and Stefan Wager. 2019. “Generalized Random Forests.” _The Annals of Statistics_ 47 (2): 1148–78.

Banerjee, Abhijit, Dean Karlan, and Jonathan Zinman. 2015. “Six Randomized Evaluations of Microcredit: Introduction and Further Steps.” _American Economic Journal: Applied Economics_ 7 (1): 1–21. https://doi.org/10.1257/app.20140287.

Barboni, Giorgia, and Parul Agarwal. 2023. “How Do Flexible Microfinance Contracts Improve Repayment Rates and Business Outcomes? Experimental Evidence from India.” _Working Paper_ , February. https://papers.ssrn.com/abstract=4358795.