How Auto Lenders Can Make Effective Underwriting Decisions

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AI can harness large amounts of customer data 

AI technologies and tools can significantly improve the credit underwriting process. Lenders can accurately assess the borrower’s credibility by combining traditional customer data sources (such as credit/repayment history) with alternative information (like banking history). This combination makes credit-lending decisions more effective and accurate. This is particularly beneficial for auto-lenders as they can combine the car’s features and purposes to make the risk models more predictive. For example, the primary usage of the car — leisure, jobs like construction, or farm work — can give valuable insights into the customer’s financial standing and the potential depreciation of the vehicle. Therefore, AI models can be very effective to signal the risk of default.

The car’s features, including its model, year of manufacture, used status, number of current/previous owners of the car, primary usage, and the number of miles driven, can help determine the Loan to Value (LTV) risk cuts. These features are also useful to calculate the difference between the estimate and the actual sale price. Trust Science®,  FinTech SaaS delivering Credit Bureau 2.0®/Credit Bureau +™, identifies a larger pool of creditworthy customers with increased accuracy and insight into the probability of default, probability of delinquency, and ability to manage payback. It collaborates closely with clients in development and integration, providing significant improvements in the lift, stability, bad loan analysis, and return on investment.

AI can make the vehicle depreciation curve more accurate

A car loses its value the minute it leaves the showroom. During the first year, the average rate of depreciation is around 20%, after which it stabilizes to 15% per year each consecutive year. The rate of depreciation depends on the model, mileage, and region. The depreciation curve can be used in estimating the loss, i.e., the value that lenders can get at repossession vs. the value of the loan still withstanding. AI technologies can make the depreciation curve more accurate using actual resale data on loans, regions where the cars are used (example: snowy regions can cause more wear and tear), and the vehicle’s primary purpose. AI can build models that can induce automated loans based on depreciation curves and data analytics, thus, retaining financially stable customers. Besides this, AI models can identify customers trading their cars for new dealerships because their loan is greater than the car’s value. Using advanced AI analytics, auto-lenders can identify such customers and offer remedies, like new car purchases or new loans.

AI can reveal creditworthy Invisible Primes™

The use of AI tools can open the auto-lending markets to many thin-file applicants called subprimes or invisibles. Post-2009 recession, there has been a shift in the auto-lending industry, lending more and more to subprime borrowers than ever. However, the lenders have given more debt to borrowers than their ability to pay. This puts such borrowers at the risk of losing their cars if they default on their loans. In such a circumstance, the use of AI in auto-lending decisions is more advantageous than ever. AI tools can effectively reveal “credit invisibles”/“unscorables” and evaluate their true creditworthiness by aligning traditional credit data with vast data from alternative sources like banking. Using AI in their underwriting decisions, auto-lenders can attract creditworthy subprime borrowers and reduce the probability of default.

Trust Science® is an industry leader in its ability to use AI/ML models that grow with your business, harnessing numerous data sources to deliver meaningful, explainable, and fully compliant risk scores, even on those that were conventionally thought of as credit invisibles. We have a unique ability to score millennials who form the largest demographic segment of the auto market. Most of them lack credit history due to generational differences in credit use. Our AI/ML models collect massive amounts of consented consumer data to calculate an accurate credit score. For lending leaders who need to score these financially stressed or underbanked borrowers fairly and ethically, Trust Science® offers a fully compliant, data-driven, AI-powered solution. To learn more about how Trust Science® can help with your underwriting process, visit us at

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