A Real-Time Pricing Engine: The Key Ingredient to Increased Profitability for Auto Lenders
24. May 2023
Ongoing digitalization demands, unpredictable inflation, a shrinking market of subprime borrowers, and the increasing cost of funds have hit auto lenders’ bottom lines hard in recent months.
On the consumer side, changing expectations, the need to grapple with soaring vehicle prices, high interest rates, and an emerging wave of defaults have depressed demand for new loans and increased competitive pressures on lenders.
To state the obvious, lenders are dealing with significant turbulence when it comes to pricing auto loans.
They are responding with a variety of strategic shifts in an attempt to maintain volume and profitability within the bounds of good corporate stewardship.
Some have raised prices indefinitely, although that risks losing market share. Others are pausing to regroup and reprice, with an eye to avoiding undue risk exposure. Some banks have exited certain market segments, such as subprime, completely. Still others are pricing aggressively to gain market share.
The strategies seem to be different, but one thing most of them have in common is that these decisions are being made with a “broad brush” and not backed by the best available data and technology, making them reactive “guesses” rather than scientifically informed decisions. We see a need to inject more precision into the equation.
Pricing – a Key Lever between Profitability and Market Share
What technology can help lenders implement to make pricing a competitive weapon, no matter how the market evolves?
In a market that’s constantly changing, lenders are searching for new and better ways to set loan and lease pricing, as pricing is a key lever to manage the trade-offs between profitability, risk exposure, volume, and market share. As lenders manage these trade-offs, they are also de facto adjusting how they optimize their portfolios.
Over the years, auto lenders have developed any number of models to simulate consumer behavior, and they have used those models to “turn the dials” on pricing to reach the “right” solution for any given moment in time.
In a more stable world, those models could be adjusted at somewhat leisurely intervals, but we no longer live in a stable or predictable world. Any process that takes time is one that risks real business downside.
Portfolio Risk Enters the Equation
Recently the loan pricing discussion has expanded to include how lenders can also use pricing to control the risk profile of their portfolios, a necessity given the recent increases in cost of funds and the trend of rising delinquencies.
As with market share and profitability, lenders have built models over time for managing portfolio risk and have attempted to factor pricing into the equation.
A key challenge, though, in using pricing for risk management is that many lenders paint markets with a “broad brush” because their existing technology is incapable of solving for segment-level pricing. Solutions are needed that allow more granular pricing management to influence demand across narrower, more targeted risk segments, ultimately down to the level of individual customers.
The Solution – Agility
As a leader in analytics in financial services, Earnix is a firm believer in a philosophy often attributed to Nobel Peace Prize winner and peace activist Betty Williams: “There’s no use talking about the problem unless you talk about the solution.”
The solution to the auto pricing conundrum requires several concrete steps, all based on one key attribute: agility. Agility needs to be pursued organizationally, architecturally, and technologically.
Build The Agile Pricing Organization
The lending organization needs to move quickly to imagine, analyze, approve, and implement pricing strategies that capitalize on rapid market changes.
The modern, agile pricing function needs to break down silos and organizational barriers that may have been erected (consciously or not) over the years. This cross-functional team must include analytics skills (driven by the latest artificial intelligence- and machine learning-powered modeling), go-to-market planning, and competitive intelligence.
This team needs to assess the current market quickly and proactively and how it could affect the lender’s portfolio, including shifting Treasury rates, competitors’ pricing, delinquency rates, car prices, and macroeconomic trends.
Unlike in the past, the pricing team needs to adopt a philosophy that any plan is valid only for a very short period. They need to continuously monitor pricing performance in real time, and be prepared for real-time price deployment, dynamic A/B testing, and continuous monitoring in order to make the best decisions possible.
Take Full Advantage of Valuable Data Assets
Data plays a huge role in designing the agile pricing solution and in its everyday operation.
To gain intelligence and paint an accurate picture of the current state of the market, lenders need to be able to factor in external data in real time, as changing market conditions (interest rates, competitors’ pricing, demand for new loans, macroeconomic data, etc.) are considered.
Technology that provides a forecasting framework is absolutely necessary, one that allows changes in the cost of funds or competitors’ behaviors to be instantly reflected in demand and profitability forecasts.
Internal data, on current customers and loan performance, also factors in. With delinquencies on the rise, some customers may be paying late or teetering on the brink of default, and you may want to reach out with an offer to renegotiate.
All this data is instrumental in powering prescriptive analytics to not only optimize pricing strategies, but also to assess and adjust those strategies based on real-time performance data. This gives lenders more confidence that they can balance new customer acquisition efforts, financial performance, and regulatory compliance to optimize their portfolios.
With modern analytics and the right data to feed the models, lenders can be much more agile in response to changing conditions, and rapid outcomes analysis allows them to assess the effectiveness of their strategies and adjust quickly as necessary.
Construct a Flexible and Composable Pricing Architecture
When lenders realize that their legacy architecture and applications are no longer capable of reacting quickly to change, some go down the “all or nothing” path, looking at wholesale technology replacement as the strategy for the future. Midway through the transition, they become overwhelmed with the task and with the resource requirements, and as a result they never achieve the promised results.
At Earnix we take a more agile and modular approach. Our strategy is one of building what we call composable solutions.
Some existing systems, such as loan origination systems (LOS), are perfectly fine as they are, and need only be connected to a new pricing solution. Much of the data lenders need for smarter decision-making is already in-house, but inaccessible due to disconnected, siloed systems and internal data management issues.
Through modular construction and the use of technologies such as application programming interfaces (APIs), we avoid “throwing the baby out with the bath water.”
Composable solutions avoid having to deploy ALL technology at once, and allow lenders to instead focus on quick wins, such as operationalizing their existing data, segmenting markets with more precision, deploying scenario modeling, and automating their real-time pricing strategies.
That allows lenders to retain what works, and to realize the benefits of rapid solution deployment and reduced time to market, while always keeping the long-term strategy in mind.
Deploy a Best-of-Breed Dynamic Pricing Solution
Earnix pricing software offers powerful automation capabilities – critical to eliminating excessive internal handoffs and to accelerating time to market – as well as ML and AI capabilities that use self-learning cycles to improve pricing strategies and deliver results over time.
An integrated, purpose-built pricing analytics framework that allows lenders to understand within minutes how a change in the market will impact their businesses, and the best way to rapidly respond to those changes.
The combination of data and modern analytics allows for the real-time deployment of pricing, giving lenders a competitive advantage through immediate responses, automated test-and-learn cycles, and rapid deployment of new pricing models.
“Ladies and Gentlemen, We Anticipate That This Turbulence May Continue…”
While the current environment may present “a bumpy ride” for auto loan originators for some time to come, it can also offer new opportunities.
By implementing a state-of-the-art real-time pricing engine, lenders can move away from cumbersome, time-consuming pricing approaches and embrace new technologies for faster, more-effective pricing, gaining a competitive advantage and delivering long-term financial performance.