By Eric Steinhoff, Scienaptic AI; Published in CUInsight
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The answer isn’t complicated. The Honda holds its value more predictably, the monthly payments are more affordable across a broader range of incomes, default rates are lower, and recoveries are stronger when something goes wrong.
Yet at many credit unions, both loans are priced identically if the borrower has a 720 credit score. In some cases, the used Honda is even priced higher.
The same logic applies elsewhere in the portfolio. A 2019 pickup truck and a 2019 sedan frequently receive the same pricing treatment, even though pickup truck values have swung dramatically in recent years while sedan prices have remained comparatively stable.
These outcomes aren’t the result of poor underwriting or a misunderstanding of the variables that impact risk. They stem from a deeper issue: most institutions are still using static pricing frameworks to operate in highly dynamic markets.
The hidden cost of static pricing
Across the auto lending industry, a significant share of loans are mispriced, not because credit decisions are wrong, but because pricing systems lag reality. Quarterly rate sheets are being used to navigate markets that change weekly or even daily.
Vehicle values respond to forces well outside traditional credit models: supply chain disruptions, manufacturer incentives, fuel prices, regional demand shifts, and macroeconomic conditions. When pricing assumptions are built in January but loans are booked in June, institutions are effectively flying blind.