Power Your Auto Loan Forecasts with Pricing Science

These global trends put a fair amount of pressure on OEM’s prompting them to start shopping for technology solutions to help solve these issues. 

Modern financial tools do a great job of predicting how a customer will behave once they have booked a loan. Driven by reporting requirements and regulatory scrutiny, models for default and prepayment risk are a perennial priority. However, as is the case for most models, the devil is in the assumptions – in this case, the assumption that the loan being modeled has already been booked. To truly manage next year’s volume (and risk), it is essential to understand all your prospective customers, especially the ones who walk away in favor of a competitor.

2 keys for winning new car loans 

Pricing

Pricing is one of the most powerful levers at an auto lender’s disposal when it comes to capturing new customers, retaining old ones and managing market share. But to understand how pricing will impact your bottom line, you must first understand who is walking through the door. Which customers are shopping by interest rate, and which ones are focused on monthly payments? Who is going to be comparing your offer against other lenders, and which customers have strong brand loyalty? And equally important – what kind of alternative offers are going to be most attractive to each individual? 

Quick deployment and instant presentation

Likewise, it’s critical that this intelligence be quickly deployed to the marketplace, instead of gathering dust on the shelf of a data science lab. In order to operationalize behavioral models, they must be integrated with risk and profitability models so that you can forecast critical KPIs for a collection of pricing scenarios. Without a purpose-built platform for these calculations, lenders end up with unwieldy and time-consuming analytical exercises, eventually reverting to ‘expert judgment’ based forecasting in frustration. 

Minimizing, rehashing and digitizing car buying experience – Alternative Deal Structures 

While today’s car market is full of debates, one thing all car buyers agree on is that they don’t want to spend time haggling with the dealer about financing. To serve the customer effectively, the dealer needs to present them with a personalized and approved offer as soon as possible.  Often, the deal is then negotiated and rehashed as the dealer zeroes in on the structure that best meets the customer’s needs. In order to minimize the extra time and work involved in rehashing, the lender can instead provide the dealer with Alternative Deal Structures (ADS) alongside the initial offer. Today, leading lenders are presenting dealers with not just one optimal offer, but with a set of pre-approved alternative offers as well. To generate these ADS, leading lenders and banks today calculate the right prices of these multiple offers using powerful machine learning and optimization technologies. These offers are then deployed in real-time to immediately respond to new application requests. 

Learn what you can do today to get ahead of the competition 

While dynamic pricing is nothing new in the auto lending market, the use of AI-based predictive pricing analytics is capable of addressing a wide array of today’s challenges experienced by the captive industry today. What can a good pricing engine deliver for you? 

Real-time digital decisioning with “what-if” scenario capabilities allow you to combine AI-driven analysis and pricing science to present personalized offers to your customers. Earnix’s automotive lending solution connects to your loan origination system and digital lending channels to deliver Optimized Pricing and Alternative Deal Structures. Whether your goal is total volume, geographic market share or risk exposure, Earnix can calculate a strategy to achieve that goal. And when their goals change, Earnix users can pivot instantly – updating yield curves and competitor data, recalculating sophisticated pricing strategies and deploying to the market before the competition can even schedule a meeting between their data scientists and the pricing team. 

Our pricing solution combines science with integrated risk and profitability models, so that you can accurately forecast (and control) the composition and the performance of your lending portfolio and win customers from the competition.