Date of Award

Spring 5-15-2022

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

School of Information Studies

Advisor(s)

Garcia-Murillo, Martha

Second Advisor

Acuna, Daniel

Subject Categories

Business | Economics | Library and Information Science | Social and Behavioral Sciences | Technology and Innovation

Abstract

Access to credit can act as a highly effective tool for poverty reduction and economic growth. The ability to borrow increases the propensity of low-income people to start and maintain businesses, educate their children and withstand financial shocks. These factors, in turn, can help them to move out of poverty and lead to more sustainable economic development. However, traditional financial institutions have inherent limitations that have impeded their ability to serve the poor.

Digital lenders are able to leverage the widespread adoption of mobile phones and mobile money to extend credit quickly and conveniently to more people, especially in developing countries. However, due to a lack of credit bureaus and available financial histories of borrowers, digital lenders frequently need to amass vast amounts of data in order to screen borrowers and experiment to find the appropriate loan amount by gradually increasing credit limits based on past repayment. This can lead to high user default rates and over-indebtedness. The lack of collateral during loan applications also means that digital lenders have limited mechanisms for enforcing repayment of loans. Both of these challenges threaten to limit further adoption of digital credit.

Through three experimental studies conducted with an airtime lender, I explore theoretical and empirical mechanisms for reducing default rates of digital loans. In the first study, I demonstrate that limited mobile phone data contain enough signals for creating effective credit assessment methods that minimize privacy risks to borrowers. In the second study, I find that increasing credit limits negatively impacts repayments and future borrowing, and offer recommendations for increasing credit limits while minimizing the drawbacks. In the final study, I draw on theories from psychology and consumer behavior to develop vivid repayment reminders. This study found that vivid reminders had limited effectiveness for increasing loan repayment and reducing loan duration. Taken together, these three studies propose new avenues for digital lenders to reduce default rates. The hope of this dissertation is that these proposed methods would lead to a reduction in interest rates, that would ultimately benefit the borrowers.

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Open Access

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