Dialing for Dollars or Defaulting Online? Assessing Borrower Risk through Call Activity and Social Media Engagement in Microfinance

This research studies how to predict whether borrowers on micro-lending platforms (small-loan services) will default (fail to repay their loans) by examining their call activity and social media behavior. The study analyzed over 154,000 loans from Indonesian platforms and found that frequent calls and stable calling patterns suggest lower default risk, while frequent social media activity and stable social media patterns actually indicate higher default risk. These findings suggest that micro-lending platforms could improve their credit assessment models (systems for deciding who gets loans) by combining both types of behavioral data.