Navigating Uncertainty: How Lenders Can Adapt Lending Strategies Amid Tariffs and Consumer Pressures

The lending industry stands at a crossroads. The talk of tariffs, such as the proposed 25% tariffs on imported vehicles and auto parts manufactured outside the U.S., has consumers and lenders preparing for potential ripple effects. According to industry experts at Edmunds, if implemented, these tariffs could increase imported vehicle prices by more than $10,000 in some cases, with the average new vehicle transaction price already hovering around $50,000. 

This comes at a particularly challenging time for American consumers:

• 70% of Americans report living paycheck to paycheck
• Auto loan delinquency rates remain elevated across all lender types
• Financial institutions have experienced significant increases in delinquencies year over year, according to recent Equifax data.

The ripple effects could touch every aspect of consumer lending, from approval rates to loan terms and portfolio performance. This policy uncertainty and the constantly shifting regulatory landscape make it even more critical for lenders to have robust, adaptable tools that allow them to adjust their strategies quickly as market conditions evolve or policy directions change.

Strategic opportunity: the critical need for proven AI models

The immediate reaction when faced with so much uncertainty might be to drastically reduce lending down the credit spectrum. While this conservative approach may seem safe, it fails to allow lenders to balance their portfolios strategically or take advantage of responsible lending opportunities that still exist.

Financial institutions that maintain a customer-first approach while employing sophisticated analytical tools will be best positioned to weather this storm. In this environment, the ability to make precise, data-driven decisions becomes even more critical as customers navigate potentially higher vehicle costs and ongoing financial pressures.

While machine learning (ML) underwriting models have been available to lenders for years, the current environment demands not just any machine learning solution, but proven, sophisticated systems with transparency and actionable monitoring built in. When evaluating current underwriting systems, lenders should ask themselves several critical questions:

• Do you have the transparency and data to understand the how and why of lending decisions? Many ML underwriting models and decisioning solutions provide predictions, but lack the interpretability to allow you to confidently adjust guardrails.
• Do you have inherent and direct control over your policies and cut-offs? The ability to quickly implement strategy changes without lengthy development cycles is crucial when market conditions shift rapidly.
• Are you able to take action quickly? Many banks and credit unions are slow movers in adjusting their policies and strategy, falling behind as portfolios season and delinquencies emerge due to not closing gaps earlier.
• Is deeper intelligence available to back up your strategy changes? Advanced systems should provide not just recommendations but supporting evidence and projected impacts of policy adjustments.

Smart, configurable, and efficient: the lending imperatives

For lenders to effectively serve customers while protecting institutional stability, several capabilities have become non-negotiable:

1. Rapid policy adjustment: The ability to modify lending criteria quickly in response to market changes is essential. Financial institutions that delay adapting their lending strategies could face significant consequences both to their bottom lines and to their customers’ financial stability.
2. Portfolio intelligence: Deep insights into current portfolio performance allow for targeted rather than blanket policy changes.
3. Balanced risk assessment: The capacity to identify promising lending opportunities even within challenging segments requires sophisticated analysis tools beyond traditional credit scoring.

Looking forward: GenAI and ML as a competitive advantage

As the lending landscape continues to evolve with fear of these new tariffs and persistent consumer financial challenges, the financial institutions and lenders that will thrive are those that combine their traditional customer-first focus with lending intelligence and enhanced credit underwriting agility.

By leveraging advanced analytics tools like Zest AI’s GenAI-powered Lending Intelligence Companion, LuLu, and proven AI-automated underwriting, while maintaining the flexibility to adjust credit policies quickly to changing conditions, financial institutions of all sizes can continue fulfilling their mission of responsible lending while navigating what stands to be a challenging period in auto financing. The institutions that view these challenges not merely as obstacles to avoid but as opportunities to demonstrate their technological leadership and unique value proposition will emerge stronger and better positioned to serve their communities in the long-term.