Earnix Blog > Pricing

Precision Pricing: Profitability and Agility in Auto Finance

Sean Johnson

February 20, 2024

  • Pricing
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According to the 2024 Cox Automotive forecast the automotive industry will continue to see inventory increase and vehicle prices recede in 2024.

As a consumer, I couldn’t be happier, especially since my daughter will be of driving age in a few years. However, as an ex-banker and someone who is still very much involved in the financial services industry, I understand that this will bring pressure to lenders.

During the recent Q4 2023 earnings season, major lenders faced questions and challenges related to reduced NII (Net Interest Income). Lenders are feeling the pressure of increased borrowing costs, leading to less-than-desired profits. To top it all off, many indications are predicting that interest rates are likely to continue to fluctuate in the new year. 

How can you, as a lender, ensure that your pricing operations are set up to ensure that you can meet these demands in the years to come? Do you have confidence that your pricing software will enable you to achieve optimal profitability and allow you to quickly respond to fluctuating markets and cost of funds?

Improved Profitability

As a former auto lending product line manager for a National Bank, I frequently encountered the challenge of adjusting rates due to the cost of funds in order to meet our spread targets.

I often received a request to increase rates by 50 basis points across all pricing cells, yet this was never as straightforward as it may seem. It required IT collaboration and was dictated by the cost of funds and product type. This led to critical questions: 

  • Is a 50-basis-point increase the correct adjustment?

  • What impact will this have on our loan volumes?

  • Will this allow us to achieve the forecast or even plan?

Traditionally, the answer was to adopt a wait-and-see approach, adjusting reactively based on the next month’s loan volume data. This method often resulted in lost opportunities due to its slow, reactive nature.

While maintaining spread targets and considering the cost of funds is vital, understanding market reactions to rate adjustments and being able to deploy price updates at the click of a button can be just as crucial.

Each time we implemented a blanket rate increase (50bps in all cells), we observed an expected decline in loan volumes. The principle of supply and demand was clear: a lower rate meant a lower spread but higher loan volumes. A higher rate meant a higher spread but lower loan volumes.

This pattern led me to question whether we could precisely gain this level of insight in our portfolio and identify the optimal balance—the pricing sweet spot. In other words, could we refine our approach to maintain a healthy spread, offer competitive rates, and gain insights into each pricing cell?

The answer lies in developing proactive, optimal pricing strategies powered by data and analytics. To do this, a lender needs to be able to accurately model previous loan/offer data to predict the market's response to price changes. From here, the lender can run various pricing scenarios to determine which KPIs it would like to achieve (e.g., volume, spread/ROE, risk) and what the tradeoffs are.

This analysis will not just encompass key pricing cells but all pricing cells to fully optimize and ensure that each individual cell is working towards a lender's desired pricing strategy. This allows a lender to ditch the wait-and-see approach and adopt the simulate-and-achieve approach. All of the guesswork has been removed from the equation.

Increasing the Agility of Pricing Operations

While important, precise pricing is only part of truly transforming your pricing operations. Another major component is agility, or to think of it another way, how quickly can you respond to changing interest rates and the cost of funds?

Modern technology equips auto lenders with the tools they need to be more responsive and successful in their pricing strategies. Advanced data analytics, machine learning, and AI, coupled with autonomous monitoring, empower pricing teams to access vast data sets, run detailed scenarios, and deploy more effective rates, without depending on IT’s release schedules or other departments’ policies or requirements.

Not only can these teams deploy to the market extremely quickly, but they can also perform detailed analyses and run “what if” scenarios in minutes. They no longer rely on other departments or need additional resources to complete vast manual analyses. They are now empowered and unrestrained to do more in much less time. This can help lenders stay a step ahead of the competition while also providing customers with the right price.

How is this all possible? Earnix can enable you to revolutionize your pricing strategy by offering the following capabilities and advantages.

Agility in Deployment

With Earnix integrated into your LOS, rate deployment can occur as frequently as needed, bypassing IT delays. In my previous role, this would have meant daily rate adjustments instead of monthly.

Agility in Operations 

Earnix can perform a wide range of scenarios and optimize rate sheets in minutes, which eliminates the need to hire additional FTEs. On top of this, Earnix can be the single source of truth for pricing operations, ensuring streamlined processes for maximum efficiency. 

Increased Granularity

Earnix pricing analytics software allows for increased granularity, moving beyond traditional pricing grids. Lenders can now segment by various criteria, including LTV, mileage, customer relationship, and more, leading to more precise pricing.

Granularity for segment-level pricing can help you influence demand across narrower, more targeted risk segments beyond typical swaths of consumers, such as those with certain credit scores, income levels, or past loan histories.


Earnix enables lenders to simulate and test different pricing strategies using internal and external data, helping them to proactively find the sweet spot for each cell. Using “what-if” scenario simulation and forecasting, you can manage tradeoffs between volume, risk, and profitability using a data-driven approach and avoid lengthy, manual spreadsheet analysis.

If your goal is profitability, you can use simulation to optimize for this specific constraint without impacting volume or risk profile. Using different goals and a set of constraints, the Earnix solution will recommend the best scenario possible to achieve these goals and determine the optimal price at the user-defined segment levels.

Finally, lenders can optimize their entire portfolio composition by understanding what type of loans they should book and the volume of each loan type to achieve the results they need.


When starting any large software implementation, it is critical to engage with a vendor that has done numerous deployments just like yours to anticipate the bottlenecks and foresee roadblocks and challenges.

With many years of experience with multiple financial institution customers, Earnix has developed a deep understanding of what a pricing team is and how it operates. Our solutions have years of iterations from customer feedback and are built with best practices from so many previous engagements.

This has enabled us to design our pricing and rating platform with specific users in mind, matching workflows and functionality to their job functions and daily tasks. Additionally, many of our features and capabilities came directly from customer feedback provided over the years, as well as many successful software deployments.

Interested in learning more about these new approaches to precision pricing in auto lending? Feel free to contact me or visit www.earnix.com today.


Partager article:

Sean Johnson

Customer Success Manager, Earnix

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