Digital lending is significantly boosting financial well-being, income, and employment for borrowers in Kenya, challenging long-held assumptions about credit risk in emerging markets, according to a pivotal new study. The research, co-authored by academics from Harvard Business School, the University of California, Berkeley, the University of British Columbia, and Northwestern University, suggests a powerful role for mobile data in expanding financial access.
The study, titled ‘Digital Lending and Financial Well-Being: Through the Lens of Mobile Phone Data’, utilised fully de-identified and anonymised datasets provided by Tala, a prominent digital lender in Kenya. Researchers conducted a rigorous causal inference analysis on a sample of 20,092 borrowers, specifically focusing on individuals who were randomly approved for loans despite their credit profiles suggesting rejection. This unique methodological approach allowed the team to isolate the direct impact of digital credit, mitigating concerns about selection bias inherent in traditional lending.
The findings reveal a profound positive shift in borrowers’ financial standing. Those granted digital loans were nearly 24 per cent more likely to be employed or self-employed compared to a control group of rejected applicants. Crucially, their self-reported monthly income increased by 21 per cent. This directly addresses a key debate surrounding high-interest digital loans, often criticised for potentially exacerbating financial hardship.
Beyond direct income, the study leveraged mobile-phone-based indicators to track broader economic and social improvements. Approved borrowers travelled to 9.4 per cent more cities, suggesting heightened economic activity and mobility. They also sent 27 per cent more text messages, indicating an expansion of their social and business networks, and saw their average spending per financial transaction rise by 15 per cent. The positive impact was particularly pronounced when borrowers used the funds for business purposes.
“Conventional wisdom would suggest that these borrowers would be more likely to misuse credit,” explained Jung Koo Kang, an Assistant Professor at Harvard Business School and a co-author of the report. “Instead, we found that they experienced significant improvements in financial well-being.”
Kang added that this outcome “may suggest that the traditional cutoffs for creditworthiness can potentially be conservative in emerging markets, where access to even small amounts of credit can unlock meaningful economic opportunities for these borrowers.” The research underscores how digital lenders, by using nontraditional data to assess creditworthiness, are reaching millions typically excluded from formal financial systems.
The study, published in The Accounting Review, also carries significant implications for developed economies. It suggests that responsibly integrating similar alternative credit models could enhance financial inclusion and expand access to affordable credit for underserved populations globally, offering a compelling counter-narrative to concerns about predatory digital lending.
Digital lending is significantly boosting financial well-being, income, and employment for borrowers in Kenya, challenging long-held assumptions about credit risk in emerging markets, according to a pivotal new study. The research, co-authored by academics from Harvard Business School, the University of California, Berkeley, the University of British Columbia, and Northwestern University, suggests a powerful role for mobile data in expanding financial access.
The study, titled ‘Digital Lending and Financial Well-Being: Through the Lens of Mobile Phone Data’, utilised fully de-identified and anonymised datasets provided by Tala, a prominent digital lender in Kenya. Researchers conducted a rigorous causal inference analysis on a sample of 20,092 borrowers, specifically focusing on individuals who were randomly approved for loans despite their
credit profiles suggesting
rejection. This unique methodological approach allowed the team to isolate the direct impact of digital credit, mitigating concerns about selection bias inherent in traditional lending.
The findings reveal a profound positive shift in borrowers’ financial standing. Those granted digital loans were nearly 24 per cent more likely to be employed or self-employed compared to a control group of rejected applicants. Crucially, their self-reported monthly income increased by 21 per cent. This directly addresses a key debate surrounding high-interest digital loans, often criticised for potentially exacerbating financial hardship.
Beyond direct income, the study leveraged mobile-phone-based indicators to track broader economic and social improvements. Approved borrowers travelled to 9.4 per cent more cities, suggesting heightened economic activity and mobility. They also sent 27 per cent more text messages, indicating an expansion of their social and business networks, and saw their average spending per financial transaction rise by 15 per cent. The positive impact was particularly pronounced when borrowers used the funds for business purposes.
“Conventional wisdom would suggest that these borrowers
would be more likely to misuse
credit,” explained Jung Koo Kang, an Assistant Professor at Harvard Business School and a co-author of the report. “Instead, we found that they experienced significant improvements in financial well-being.”
Kang added that this outcome “may suggest that the traditional cutoffs for creditworthiness can potentially be conservative in emerging markets, where access to even small amounts of credit can unlock meaningful economic opportunities for these borrowers.” The research underscores how digital lenders, by using nontraditional data to assess creditworthiness, are reaching millions typically excluded from formal financial systems.
The study, published in The Accounting Review, also carries significant implications for developed economies. It suggests that responsibly integrating similar alternative credit models could enhance financial inclusion and expand access to affordable credit for underserved populations globally, offering a compelling counter-narrative to concerns about predatory digital lending.
By Brian Ngugi