Case Study: a major auto lender achieves $3.5M in annual savings with SentiLink fraud prevention

How a Major Auto Lender Saves Millions with More Accurate Fraud Prevention

A major auto lender sought to understand the performance of its existing fraud detection system and identify the proportion of its charge-offs and first payment defaults (FPDs) stemming from synthetic fraud and identity theft. To evaluate this, they engaged SentiLink for an analysis using its Synthetic Fraud and ID Theft Scores.

SentiLink's analysis identified that $3.5 million in annualized losses were attributable to fraudulent loans, enabling significant potential savings. Their solution was 10x more effective at predicting FPDs than the lender's previous system, allowing for more precise fraud prevention.