Case Study: Online Small Business Lender cuts default rate from 30% to 21% and boosts revenue ~4% with Explorium

Reduced Lending Risk and Better Repayment Rates With Enhanced Default Risk Models

Online Small Business Lender, a fintech SMB lender, was struggling with rising loan defaults because traditional credit scores and bank statements didn’t capture true borrower risk. To strengthen underwriting, the lender engaged Explorium to augment its risk models using alternative data and data-augmentation services.

Explorium integrated diverse alternative signals — financial activity, company data, web presence and social media indicators — into the lender’s ML risk models, allowing retraining and more accurate scoring. As a result, the Online Small Business Lender reduced default rates from 30% to 21%, saw nearly a 4% revenue lift in the six months after adoption, and lowered operational costs tied to recovering bad loans.