Key Takeaways
- 1.9% of auto loan balances were in charge-off status in Q1 2024
- 2.0% of auto loan balances were in charge-off status in Q4 2023
- 0.51% of auto loans were in REPO status in September 2024
- In Q2 2024, 4.9% of auto loans were 30+ days delinquent among subprime borrowers (NY Fed Consumer Credit)
- Moody’s Analytics projected charge-offs to rise to 2.2% by Q1 2025
- In 2024, loss-given-default on auto loans improved by 5% year-over-year due to higher used-vehicle liquidation values (S&P Global)
- 32% of delinquent auto loan balances were tied to borrowers with FICO scores below 620 (2024)
- 27% of delinquent auto loan balances were tied to borrowers with FICO scores below 600 (2023)
- In 2024, 14% of auto-loan originations had FICO scores below 600 (Experian data)
- Auto ABS 30+ day delinquency in the subprime segment was 5.8% in September 2024
- Repos and recoveries accounted for 26% of gross losses in auto ABS portfolios in 2023
- WA loss severity on auto loan ABS was 16.2% in 2023 (industry estimate)
- Auto loan delinquencies tracked rising unemployment; the U.S. unemployment rate averaged 4.3% in 2024 (BLS)
- The consumer price index (CPI-U) rose 3.4% in 2024 (BLS), raising effective affordability pressure
- U.S. real median household income declined 2.1% from 2022 to 2023 (Census, real income measure)
Auto loan delinquency worsened in 2024, with higher subprime and affordability pressures driving rising charge offs.
Related reading
Delinquency Rates
Delinquency Rates Interpretation
Forecasting & Performance
Forecasting & Performance Interpretation
Borrower Risk Mix
Borrower Risk Mix Interpretation
Portfolio & Securitization
Portfolio & Securitization Interpretation
Macroeconomic Context
Macroeconomic Context Interpretation
Industry & Policy Factors
Industry & Policy Factors Interpretation
Charge Off Status
Charge Off Status Interpretation
Recovery & Loss
Recovery & Loss Interpretation
Macro Sensitivity
Macro Sensitivity Interpretation
Underwriting & Terms
Underwriting & Terms Interpretation
Risk & Fraud
Risk & Fraud Interpretation
Servicing & Borrower Support
Servicing & Borrower Support Interpretation
How We Rate Confidence
Every statistic is queried across four AI models (ChatGPT, Claude, Gemini, Perplexity). The confidence rating reflects how many models return a consistent figure for that data point. Label assignment per row uses a deterministic weighted mix targeting approximately 70% Verified, 15% Directional, and 15% Single source.
Only one AI model returns this statistic from its training data. The figure comes from a single primary source and has not been corroborated by independent systems. Use with caution; cross-reference before citing.
AI consensus: 1 of 4 models agree
Multiple AI models cite this figure or figures in the same direction, but with minor variance. The trend and magnitude are reliable; the precise decimal may differ by source. Suitable for directional analysis.
AI consensus: 2–3 of 4 models broadly agree
All AI models independently return the same statistic, unprompted. This level of cross-model agreement indicates the figure is robustly established in published literature and suitable for citation.
AI consensus: 4 of 4 models fully agree
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
Emilia Santos. (2026, February 13). Auto Loan Delinquency Statistics. Gitnux. https://gitnux.org/auto-loan-delinquency-statistics
Emilia Santos. "Auto Loan Delinquency Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/auto-loan-delinquency-statistics.
Emilia Santos. 2026. "Auto Loan Delinquency Statistics." Gitnux. https://gitnux.org/auto-loan-delinquency-statistics.
References
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- 2newyorkfed.org/medialibrary/media/research/consumer-credit/ccr/2024-02-consumer-credit.pdf
- 5newyorkfed.org/microeconomics/databank/consumer-credit/delinquency
- 7newyorkfed.org/medialibrary/media/research/consumer-credit/ccr/2024-08-consumer-credit.pdf
- 31newyorkfed.org/research/policy/hhdc
- 34newyorkfed.org/microeconomics/databank/consumer-credit/chargeoff
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- 28federalreserve.gov/releases/g19/current/
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- 27consumerfinance.gov/enforcement/actions/
- 32nationalservice.org/wp-content/uploads/2024/auto-servicing-hardship-metrics-2024.pdf
- 35carbonato.com/resources/auto-finance-trends-report-2024
- 36fred.stlouisfed.org/series/MORTGAGE30US
- 37cars.com/research/average-down-payment-study/
- 39cars.com/research/credit-score-distribution-auto-loans/







