The New Roadmap for Auto: Navigating the Industry's Biggest Priorities in 2026

Highlights: 

• To combat high costs and economic uncertainty, lenders must move beyond traditional credit data, adopting a 360-degree consumer view with unique data assets like instant income and employment verification to improve lending confidence.
• As digital transactions and AI adoption grow, the auto industry must prioritize "explainable AI" with transparent guardrails and implement robust ID verification solutions to combat sophisticated first-party and synthetic fraud.

The automotive industry is currently navigating a period of significant transformation, marked by economic shifts and rapid technological advancement. At two recent industry conferences, the American Financial Services Association Vehicle Finance Conference (AFSA) and the National Automobile Dealers Association Show (NADA), leaders from the Equifax automotive team engaged in critical conversations regarding the future of the market. 

Three central themes continue to be the most pressing priorities on the minds of lenders and dealers alike: Affordability, AI, and Fraud. While the industry faces a "flat" sales year, represented by an estimated 2.5% increase in overall sales, the focus has shifted toward leveraging data and technology in new ways to find growth. This blog explores where these experts think the industry is headed and what you should know now to stay prepared.

Jessica Fang, VP, Strategic Alliance - Automotive

Affordability: Navigating High Costs and Economic Uncertainty 

During her time at NADA, Fang noted that the conversation around affordability has expanded far beyond simple vehicle pricing. Dealers and lenders are increasingly concerned with the "total cost of ownership," which now includes skyrocketing costs for parts, service, and insurance premiums. The pressure on consumers is compounded by high delinquency rates, potential interest rate caps, and the end of EV tax credits, creating a complex web of economic uncertainty for the average consumer. To address these challenges, the industry cannot look to traditional credit data alone to gain a complete understanding of a customer’s full financial picture.

• Actionable Insight: Success in this environment requires a 360-degree view of the consumer. By utilizing unique data assets—such as instant income and employment verification—lenders can better understand a borrower's true financial standing. This breadth of data allows for more confident "yes" decisions even when traditional scores may not tell the full story.

Fraud: Combatting the Rise of Sophisticated Bad Actors 

A major point of discussion at NADA was the continued rise of fraud, specifically synthetic identity and the need for robust ID verification. As digital transactions become the norm, the risk of bad actors exploiting the system grows. Jessica emphasized that the industry needs digital trust to move at the speed of today's market without compromising security.

• Actionable Insight: To combat this growing problem, Jessica suggests adding Employment Insights to the toolbox. Integrating employment data into prequalification and financing processes, served alongside their credit report, helps lenders make faster, more profitable decisions, providing an extra layer of protection for both lenders and the consumers they serve.

Barrett Teague, VP, Sales - Auto Lending

Affordability: The Shift from New to Used Driven by MSRP Peaks 

With the average MSRP for a new vehicle hitting $50,000, Teague highlighted that many consumers could start  being pushed out of the new car market and toward used vehicles. This shift, a hot topic at AFSA, is further intensified by the rising costs of repair and maintenance, particularly for electric vehicles, which feature complex technological systems that are expensive to fix.

• Actionable Insight: Lenders should employ a data-driven solution like Consumer Affordability View to help get a more complete picture of a prospective customer’s true financial capacity. This tool provides an affordability risk score and a monthly repayment capacity estimate, allowing lenders to rank-order consumers by their predicted ability to take on new debt responsibly.

AI: The Mandate for Explainability and Guardrails 

The discussion around AI at AFSA centered on machine learning and Large Language Models (LLMs), with a specific focus on "explainable AI." Lenders are eager to bring disparate data together, but they are equally concerned with putting the right guardrails in place to prevent biased or non-compliant automated decisions. AI cannot go unmonitored; it must be transparent and compliant.

Fraud: Managing Risk in a "Soft Pull" Environment 

Teague noted a growing concern among lenders regarding the shift toward "soft pulls." While beneficial for the consumer experience, some lenders worry this trend has decreased visibility into when competitors are pulling credit reports, leading to worries about increased fraud and "bust-out" behavior.

• Actionable Insight: Utilizing a solution like Credit Abuse Risk allows lenders to detect potential threats at the account origination stage. This tool provides an explainable, FCRA-compliant score that analyzes patterns linked to loan stacking, helping to mitigate first-party fraud before it hits the books.

Angelica Jeffreys, SVP, Automotive Retail

Affordability: Solving "Payment Shock" with Proactive Guidance 

Jeffreys observed at NADA that many shoppers abandon their purchase journey late in the process due to "payment shock." She argues that the industry must move toward "proactive affordability guidance," placing financial alignment earlier in the process—specifically on Vehicle Detail Pages (VDPs)—to ensure shoppers are looking at inventory they can actually afford. Additionally, she noted that 60% of households are spending more on essentials, making "financial durability" metrics critical for finding hidden creditworthy buyers.

AI: Moving from Browsers to Buyers with Predictive Propensity 

AI's primary role is automating the "deal-to-dashboard" process and reducing technical friction. Jeffreys advocates for AI-driven propensity models that layer behavioral intent with financial indicators to separate serious buyers from anonymous browsers.

Actionable Insight: Use AI and machine learning within Customer Data Platforms (CDPs) to surface relevant offers instantly. This allows for dynamic personalization—such as highlighting luxury brands for high-asset households—without requiring a login, thereby reducing lead drop-off.