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Daniel Burke, Chief Information and Strategy Officer, and Chad Stilwell, Chief Technology Officer at Agora Data, are the architects of this first-ever business modeling for the subprime market segment. Their new-to-the-auto-industry model works to identify performance and risk by evaluating loan characteristics and alternative data with a high degree of accuracy. The multi-dimensional model powered by artificial intelligence and machine learning performs thousands of simulations daily on every loan and is backtested on over $15 billion of subprime data. Lenders and auto dealers can now predict loan performance and use the information to make better decisions and optimize business operations.
“Agora’s proprietary modeling produces loan performance results for an asset class previously considered volatile and risky,” said Burke. “The revolutionary approach delivers dependable calculations similar to results observed in prime asset classes.”
“Predicting the unpredictable is a breakthrough for the subprime auto industry,” said Stilwell. “Historically, subprime lending has been difficult to predict due to the reliance on traditional credit scoring models and unfavorable underwriting guidelines. Advanced modeling using data-driven analytics represents the future of subprime lending and opens a large asset class to the broader market.”
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