Behavior Revealed in Mobile Phone Usage Predicts Credit Repayment
研究发现，手机通话记录中的行为特征能有效预测贷款违约，尤其对缺乏传统信用记录的群体，其预测能力甚至优于信用局数据，为无银行账户者提供信用评估新方法。
Abstract Many households in developing countries lack formal financial histories, making it difficult for firms to extend credit, and for potential borrowers to receive it. However, many of these households have mobile phones, which generate rich data about behavior. This article shows that behavioral signatures in mobile phone data predict default, using call records matched to repayment outcomes for credit extended by a South American telecom. On a sample of individuals with (thin) financial histories, this article's method actually outperforms models using credit bureau information, both within-time and when tested on a different time period. But the method also attains similar performance on those without financial histories, who cannot be scored using traditional methods. Individuals in the highest quintile of risk by the measure used in this article are 2.8 times more likely to default than those in the lowest quintile. The method forms the basis for new forms of credit that reach the unbanked.