Digital Lending and Financial Well-Being: Through the Lens of Mobile Phone Data
利用肯尼亚一家数字贷款机构的随机审批数据，研究发现数字信贷能改善借款人的金融福祉，包括手机交易、余额、流动性、社交网络及自报收入就业，且对信贷受限者、商业借款人和多贷者效果更显著。
ABSTRACT To mitigate information asymmetry about borrowers in developing economies, digital lenders use machine-learning algorithms and nontraditional data from borrowers’ mobile devices. Consequently, digital lenders have managed to expand access to credit for millions of individuals lacking a prior credit history. However, short-term, high-interest digital loans have raised concerns about predatory lending practices. To examine how digital credit influences borrowers’ financial well-being, we use proprietary data from a digital lender in Kenya that randomly approves loan applications that would have otherwise been rejected based on the borrower’s credit profile. We find that access to digital credit improves borrowers’ financial well-being across various mobile-phone-based well-being measures, including monetary transactions and balances, mobility, and social networks as well as borrowers’ self-reported income and employment. We further show that this positive impact is more pronounced when borrowers have limited access to credit, take loans for business purposes, and obtain more credit. JEL Classifications: D14; G21; G51; M40; M41; O16; O30; O55.