BETTER RISK ASSESSMENT WITH BEHAVIORAL ANALYSIS
Our client, an international bank, sought to reduce the default rate for small loans in emerging markets. Modeling risk in this environment presented a significant challenge for the bank, as most customers had a limited digital footprint. As a result, less reliable demographic information was used to assess creditworthiness.
INTELLIGENT APPLICATION OF ALTERNATIVE DATA
We developed a risk prediction engine that more appropriately determined credit risk by basing it on customer behavior. Our models used a variety of data sources to better identify and understand the key behavioral indicators that drive loan repayment.
