Point Predictive Inc., the San Diego-based company that provides artificial intelligence solutions to lenders, today announced the launch of DealerExplorer™, a solution that helps auto lenders evaluate prospective dealerships before adding them to their network by providing insights into the quality and quantity of deals originating from a dealership. This helps automotive lenders better assess risks associated with dealerships they may be considering for their portfolio.
DealerExplorer provides data for lenders to evaluate prospective dealerships based on their loan performance history as seen in the Point Predictive data consortium. Lenders receive comprehensive reports on prospective dealerships and can extract raw data from the report to use during their internal analysis and onboarding processes. DealerExplorer users can expect to strengthen and expand their dealership portfolio and reduce the risk of loan default. The solution provides insights into more than 150,000 dealerships nationwide to ensure that lenders are receiving high-quality loans and forming successful partnerships with dealers.
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“Historically, when indirect lenders are evaluating a dealership for addition to their portfolio, they have very limited information regarding the dealership’s historic loan performance and what kind of risks that dealership might present,” saidTim Grace, CEO of Point Predictive. “DealerExplorer leverages our data consortium to provide lenders with insights into dealerships they currently have no relationship with. This provides valuable information to help determine whether a particular dealership is a good fit to be added to a lender’s dealership network and can improve the quality of loans in their portfolio.”
The Point Predictive data consortium was purpose-built for risk management with more than 120 million historical applications, reported income for more than 63 million consumers, 17 million employer records with 8,200 fake employers, more than 400,000 social security numbers tied to default, 103 million social security numbers of deceased individuals, more than $7.2 billion in loans with early payment defaults, $2 billion in loans identified as fraudulent, and millions of addresses and telephone numbers linked to risk of fraud or loan default.
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