Pricing Optimization for Tough Markets: Four Use Cases for Auto Lenders

The global auto finance market is definitely seeing a positive trend compared to the two prior years. However, Cox Automotive is keeping its earlier forecast in line. In the U.S., Cox Automotive predicts that the economy will move forward with slow growth with a near flat 2% increase in new vehicle sales and thin profit margins in 2024. According to their latest press release, US auto sales are expected to finish the first half of 2024 higher by 2.9%, in line with expectations for slow growth.

On the brighter side, the UK Finance & Leasing Association (FLA) figures show that consumer car finance new business volumes grew in April 2024 by 8% compared with the same month in 2023. The FLA also commented that their “latest research suggested that the point-of-sale consumer car finance market would see new business by value hold steady in 2024 at around £39 billion.”

The risk of delinquencies remains concerning: for example, Fitch Ratings’ subprime auto ABS 60+ delinquency index reached 5.64% in May 2024–from a low of 2.58% in May 2021. Fitch Ratings predicts delinquencies and defaults to increase moderately in 2024.

All of this is further proof that auto lenders around the world continue to face real pressure to not only grow their market share but also to remain profitable. It’s a real challenge as they strive to keep pace with constantly changing customer expectations, unprecedented market volatility, and the need to quickly respond to macroeconomic changes and competitive shifts.

All of these variables increase overall competition and place more emphasis on pricing strategies that can successfully reduce risk, increase profitability, and help auto lenders gain and maintain market share.

The Need for Better Pricing Strategies in the second half of 2024

Even as we slowly return to “normal” in the car-buying market, pricing speed, and agility are now required to remain competitive. During one of the recent interest rate hikes, many lenders were caught flat-footed as they were only able to update their prices every four to six weeks (or longer). This resulted in an increase in unprofitable loans, lost volume, and many other unhealthy results.

Many lenders used this time to pause and rethink their past aggressive pricing strategies. Clearly, they needed to avoid pricing their loans in ways that could potentially affect their overall profitability. Yet, in doing so, they risked losing momentum and falling behind the competition.

Meeting the quickly accelerating pace of all these changes now demands improved resilience, pricing infrastructure agility, and the ability to quickly react to macroeconomic or competitive changes. Some of the top challenges experienced by auto finance companies worldwide – such as declining loan profitability, compliance and audit issues, rigid pricing structures, and difficulty forecasting pricing scenarios and outcomes – can and should be addressed by modern pricing analytics and decisioning platforms.

Earnix’s pricing optimization, analytics, and decisioning platform – now gives auto lenders the AI-powered analytical tools they need to create cutting-edge, competitive pricing strategies to meet their spread targets, KPIs, and other business goals. Many of the platform features and capabilities came from customer feedback provided over the years and from numerous software deployments. 

Four Critical Pricing Use Cases for Auto Lenders

Let’s take a closer look at how Earnix supports a wide range of auto lending use cases and how its powerful capabilities can dramatically improve pricing processes and outcomes.

Use Case #1: Customer-Level Price Modeling

Many auto lenders let the cost of funds and product type alone dictate the rates they would offer, leaving many other variables out of the equation.

Unfortunately, this approach leads to real risk. If priced too high, loan offers can reduce loan volumes and market share. If priced too low, chances are good that these offers will increase the risk of delinquencies and threaten long-term profitability.

With Earnix, auto lenders can rely on AI-powered analytics, elasticity modeling, and optimization algorithms to determine the perfect sweet spot for loan/lease pricing using many different variables (in addition to the cost of funds).

These include the customer’s risk profile and willingness to pay, competitive pricing, market-level metrics, and various macroeconomic indicators. Lenders can also combine price elasticity forecasts with risk modeling and use price optimization to reliably determine the optimal loan price to charge any given customer. As a result, lenders are more likely to close more loans, win and defend market share, and hit their profitability targets.

Use Case #2: Portfolio-Level Simulation and Optimization

Earnix enables lenders to see how a given portfolio of customers might be impacted by a change in price. As a result, they’re in a better position to answer questions like, “What will next week’s/month’s bookings look like, given a proposed change in price?”

Auto lenders can apply simulations to portfolio-level strategies to gain meaningful insights into how pricing can be used to shape an auto lending portfolio, exactly as specified by the lender.

Additionally, product-driven optimization scenarios may be configured for longer loan terms without affecting the risk profile, helping serve previously untouched customer segments. This can help them find and win business in demographics they may not have considered in the past, which can be a boost in increasing loan volume growth.

Use Case #3: Fast (Even Real-Time) Pricing Deployment

Many lenders struggle with manual pricing approaches, siloed systems, and complex analytical tools. All of this can create significant delays between a decision to make price adjustments, approve them, and actually deploy them. These processes can sometimes take days or weeks, leading to lost momentum and exposing lenders to more risk if the market changes.

With Earnix Price-It, lenders are able to take their newly created pricing strategy and deploy it directly to the market without any intermediate steps or handoffs between internal teams. Not only does this reduce the likelihood of errors, but it lets lenders put loan offers in front of prospective customers faster than ever before, giving them a valuable edge over competitors who can’t keep pace.

Use Case #4: Alternative Deal Structures

The rise of the digital, on-demand economy has led borrowers to expect instant credit decisions along with multiple financing options to choose from. This is exactly what Alternative Deal Structures (ADS) are designed to do.

By leveraging ADS in auto finance, lenders can minimize rehashing, reduce processing costs, increase loan profitability, and essentially get more customers by not letting them walk away. Auto lenders can present data-driven alternatives in real-time and can see the effects on the profitability of a particular loan offer on their overall portfolio.

Real-World Results

We’ve seen how many auto lenders are using Earnix Price-It to update their prices in a much more intelligent and effective way.

For example, one used Earnix pricing optimization solution to update their pricing strategies as often as two or three times per week. Partnering with Earnix also helped this bank achieve impressive results, including:

• A 65% reduction in unprofitable loans

• A 10-15 basis point increase in profitability

• An eight-figure impact on net present value

To learn more about this lender’s use of Earnix Price-It platform and how Earnix delivers all of the key capabilities needed to bring these use cases to life, download our eBook, “Pricing Analytics for Auto Lenders: Four Critical Use Cases”.