Leading Auto Lender Leverages Machine Learning Technology Scoring From PointPredictive to Better Pinpoint Risk and to Improve the Consumer Experience at Their Car Dealerships
PointPredictive Inc., the San Diego-based machine learning company, announced that Byrider has selected the company’s risk scoring solutions to help them better segment high- and low-risk applications and dealers to improve profitability, expand loan availability and enhance the lending experience for both consumers and dealers.
@byridercorp is now using PointPredictive’s auto lending fraud solutions
As part of the integration, Byrider will use the company’s scoring solution Auto Fraud Manager with Auto Fraud Alert Reporting to identify misrepresentation and prevent default on high-risk applications while streamlining the approval process of low-risk applications to improve and expedite both the consumer and dealer loan funding experience, ultimately expanding their loan portfolio profitably.
Byrider selected PointPredictive’s machine learning AI scoring after extensive testing of the solution and evaluating retrospective results. “In our retrospective test with PointPredictive, we saw a significant lift in identifying defaults tied to misrepresentation and fraud,” said Gary Harmon, Chief Risk Officer of Byrider.
PointPredictive launched Auto Fraud Manager with Auto Fraud Alert Reporting to help address the $6 billion-dollar annual problem of misrepresentation and fraud that plagues the auto lending industry. The solution uses machine learning to mine historical data from applications across the industry to pinpoint where fraud is happening. Over 60 million applications have been evaluated and scored by the unique machine learning AI system which is continuously learning new patterns as they emerge.
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“PointPredictive is excited to partner with Byrider to help them achieve better relationships with their borrowers and their dealer network,” advises Tim Grace, CEO of PointPredictive. “Our solutions have proven to help lenders reduce their risk of early defaulted loans and, in the process, help them streamline loans for reduced stipulations and friction in the lending process. By better targeting risk, the end beneficiaries are their dealers and borrowers who can see a reduction in the time it takes to fund loans.”