Used Cars Surge as Credit Tightens: The Auto Industry’s Balancing Act

As the credit card landscape evolves, understanding how consumers and businesses are adapting has never been more important.

Our second annual State of Credit Cards Report provides a timely update on key market dynamics and dives into an often-overlooked segment within credit card portfolios: business accounts.

Key takeaways:

• 30+ DPD delinquency rates remained above pre-pandemic levels in 2025.
• Fintechs continue to gain share in the credit card market, posting a 71% YoY increase in account originations.
• Many businesses use consumer credit cards to support business-related activity, making this segment easy for lenders to overlook.

The Regional Economic Health Tracker examines consumer health across the four U.S. census regions. It highlights how regional dynamics, from data center growth to housing costs and credit conditions, are shaping household finances today.

• Regional income, spending, and cost-of-living trends
  
• Housing market performance and price changes
  
• Consumer stress and 30+ DPD balances by product

ITIN holders are active, responsible participants in the U.S. credit economy — yet many remain overlooked by traditional lending models.

Our white paper takes a closer look at this financially active and resilient population, revealing key insights into their credit performance and long-term growth potential.

Some findings include:

• Most ITIN holders are concentrated in states that represent a large share of the U.S. economy: California, Texas and New York.
• 76.9% of ITIN holders remained current on trades after 12 months, a rate 15% higher than SSN consumers.
• ITIN holders maintain a lower debt-to-income ratio (25%) than SSN consumers.

Read the full white paper for more insights.

This summary outlines important research findings that help lenders drive a more inclusive environment for customers, while mitigating risk.

A few takeaways:

• Understanding the profiles of who’s more prone to exclusion informs risk management.
• Machine learning techniques can also be deployed to help detect economic interaction effects or shifts.
• Attributes like education level, occupation or rent/utilities payment history have predictive power in credit outcomes.