5 minutes
Is your institution adjusting its approach to the requirements of modern lending?
In March 2022, the first of 11 consecutive rate increases by the Federal Reserve reawakened scrutiny on lending. As inflation has remained stubbornly high and consumers savings from COVID-19 have evaporated, focus has rightly shifted to the ongoing ability of consumers to service their existing debt and take on new loans. In automotive finance, the convergence of higher borrowing costs and increasing auto loan delinquencies and defaults came about just as dealer inventory levels were beginning to recover.
As if automotive lenders needed even more to contend with, their business leaders are also increasingly challenged with how to properly utilize the increasing deluge of data and emerging tools like artificial intelligence. Exhausted yet? Where to start? What now?
One conclusion can’t be escaped—the fundamentals in auto lending have changed. Expectations from consumers, dealers, regulators and shareholders have never been higher. Here are four new fundamentals that are now required in the auto lending marketplace that you should consider in evaluating your auto loan processes and the data and technology that enable them.
1. Fast
Quick loan decisioning is no longer a nice-to-have for consumers and dealers—it’s a must. And while some lenders think reviewing applications too quickly presents risk, the opposite is also true. Open Lending’s “2024 Lending Enablement Benchmark Survey” found that lenders who take hours or days to return offers are seeing a greater increase in delinquencies among prime and super-prime approved borrowers than lenders who approve in seconds or minutes.
Consumers routinely cite finance and insurance as the most time-consuming and least satisfying part of the car-buying experience. To compensate, lenders have traditionally set rates sheets to avoid an even more exacting loan-approval process. The rise in delinquencies and defaults to levels that are now equaling those last seen during the Great Recession of 2008 should serve as an alarm that there is something wrong with the status quo. And yet all of this is happening when more data than ever is available.
Using more data, including alternative data, with the capabilities of an AI platform and coupled with human knowledge will allow the industry to move faster. This coupling should be viewed as “actual intelligence”—the application of more data into a mysterious AI platform alone is not the answer. The combination of advanced platforms, called lending enablement solutions, is making it possible to be fast and more accurate, without introducing unnecessary risk.
2. Fair
The ability to see creditworthiness, even and especially in lower credit tiers, is crucial today. Fair is table stakes. In the words of Yoda, “Do or do not. There is no try.” To be fair and to be accurate is the challenge.
Regulators are expecting to see fair treatment, but that’s no reason to put all responsibility for risk aside. Simply rescoring an application in the name of being fair should be avoided. The new way forward is to better approach deal structure and loan pricing commensurate with the modeled risk of the deal, not just the consumer.
The good news is that by combining alternative data with an evaluation of the deal parameters enables lenders to buy into the near-prime and non-prime space, which brings with it the ability to serve those commonly underserved by lending in the past.
A recent study by the Urban Institute lays out the challenge for lenders, with median credit scores for Black, Hispanic and Native American communities falling outside the commonly defined lower threshold of prime. As lenders look to achieve fairness, being empowered to extend credit to near-prime and non-prime applicants will further enable lending to historically excluded borrowers.
3. Flexible
A flexible approach to auto lending should be viewed in two ways.
First, you must retain the flexibility to structure and price loans that address your institution’s needs and the realities of your market. Cost of funds and loan servicing, targeting ROA yields and being market-competitive on rate need to be driven by you and embedded into your decisioning process and technology.
Second, you must ensure that your approval process offers flexibility to the dealer and the consumer. As deals become accepted offers and booked loans, things may move: payoff amounts on the pre-existing auto loan, trade-in valuations, cash down from the consumer, qualification for OEM incentives and availability and price of the vehicle. Ensure that changes in these areas don’t completely restart the process. Restarting only compromises speed.
4. Flawless
Yields and expected losses on your loan portfolio should be able to be forecasted with great accuracy, as consumers and dealers alike will demand that LTVs and loan amounts are as approved. While the industry has grown accustomed to using rate cards, this approach may be falling short of new expectations.
For auto lenders like credit unions and their dealer partners, the simplicity of the rate card allows speed and certainty on what will be offered for a set credit score. But the rate card also masks downside risk and to some extent prevents even more attractive rates on the upside.
Combining the analytics required to assess each application with a decisioning engine delivers risk-based pricing that fulfills the need for a fast response and replaces the certainty of the rate with the certainty of pricing appropriately for the risk.
More accurate and forecastable results are within lenders’ reach. Alternative data and expanded use of lending enablement solutions that allow the application of that data into a fully structured, risk-based price for each application and deal make it possible.
Kevin Filan is SVP/marketing for Open Lending, Austin, Texas.
