PointPredictive Inc. announced today the launch of Auto Fraud Manager – a real-time predictive pattern recognition scoring solution providing a bundled suite of predictive scores that can instantly assess the risk of First and Early Payment Default, Fraud Misrepresentation and Dealer Risk on each automotive loan application so lenders can stop fraud before underwriting and funding a loan that will likely lead to a loss.
With the launch of Auto Fraud Manager, PointPredictive is addressing the growing problem of auto lending fraud which they currently estimate will reach nearly $6 billion in 2017. PointPredictive research indicates that most of that fraud risk is hidden in losses categorized as First Payment Default or Early Payment Default – terms that lenders use to indicate loans where the borrowers fail to make the first payment or stop making payments within the first six months of the loan, respectively.
“Our research indicates that as many as 70% of auto loans that default without a single payment have some material misrepresentation in the application,” says Frank McKenna, PointPredictive’s Chief Strategy Officer. “The overwhelming majority of those defaulted loans with material misrepresentation are submitted by a small fraction of the auto dealers a lender works with. As few as 3% of a lender’s dealers represent 100% of the risk on some portfolios we have examined.”
Auto Fraud Manager is unique in that it identifies three distinct risks – Fraud Risk, First/Early Payment Default Risk and Dealer Risk – in a single solution so that lenders can make an informed lending decision in real-time while the loan application is being processed and before the car leaves the dealership. Current solutions for verifying employment or verifying income are often not available in real-time, are not able to provide lenders with instant assessments, and often result in high false positives, poor customer experiences, and costly underwriting times. Auto Fraud Manager provides an instant (real-time) full application assessment that shows lenders the probable material misrepresentations on loan applications that will likely lead to a loss. The lender determines their risk tolerance levels and can accept, reject, or order verification solutions depending on their specific loan and dealer risk levels.
As lenders receive applications from a dealer, Auto Fraud Manager scans the application instantly for patterns of fraud risk such as income manipulation, employment fabrication, evidence of straw borrower, collateral inflation, fraud ring activity, and dealer fraud as well as likelihood of first or early payment default. The lender can use that information to take proactive steps to stop the fraud. Recent tests indicate that Auto Fraud Manager can reduce risk losses at lenders by 50% or more and improve their dealer performance by more accurately targeting their riskiest loan providers early, before losses are incurred.
Auto Fraud Manager scoring models leverage a consortium approach to learn patterns of fraud and risk across the automotive industry – spanning millions of loans and a variety of lenders. PointPredictive uses specialized machine learning and pattern recognition algorithms that have been proven successful in fraud and risk solutions for the financial services industry. Payment cards, mortgage lending, telecommunication, and insurance are already using similar solutions to reduce their fraud losses by 50% or more. For auto lending, we can show that this approach detects the highest percentage of risky loans at the lowest false positives to provide the highest dollar loss reductions and the best customer experience.
“We’re seeing great results from Auto Fraud Manager,” adds Tim Grace, CEO of PointPredictive. “In retrospective tests on lender-provided historical loan data, we have shown that if Auto Fraud Manager had been used at application time, the lenders could have realized 50% reductions in fraud losses at very low false positive rates. In addition, many lenders are taking advantage of our ability to score large numbers of loans quickly and sending us the last two years of their auto loan applications. We score these loans and help them identify which loans lead to losses that we would have identified before funding and which loans are classified as credit losses in their portfolio but are actually instances of fraud or misrepresentation.”
For further information on Auto Fraud Manager (including retrospective portfolio scoring or production pilots), contact Kathleen Waid at email@example.com