Harnessing Soft Information to Promote Financial Inclusion: The Case of Business Lending by a Native CDFI
研究一家本土社区发展金融机构如何利用基于软信息的借款人风险指标（如品格评分）来预测贷款违约和利率，发现品格评分比信用评分更能解释利率差异，支持其独特的承保实践。
Abstract Native Community Development Financial Institutions (NCDFIs) promote financial inclusion in financially underserved Native communities by adopting innovative lending strategies, including designing their own soft-information-based measures of borrower risk. Drawing on business loan data from one prominent NCDFI, a nonprofit loan fund, we examine to what extent the NCDFI-generated borrower risk measures help explain the NCDFI's loan performance and pricing above and beyond the effect of the credit score, a conventional credit-bureau-produced, hard-information-based metric. All else equal, both loan delinquency hazard and loan interest rate are robustly predicted by one of the NCDFI's two proprietary soft-information-based measures, the character score, but do not vary with the other one, commitment to business score. The credit score is an important determinant of loan delinquency hazard but, all else equal, does not exhibit a detectable relationship with the loan interest rate. We do not find evidence of noteworthy interactions among the three NCDFI-used borrower risk measures. Our study offers evidence in support of the unique underwriting practices and relationship-based lending operations that characterize the NCDFI industry.