Fraud risks in the auto lending industry are increasing, but many lenders say they remain uncertain whether current artificial intelligence (AI) tools can effectively detect increasingly sophisticated threats.
A new industry survey conducted by InformedIQ gathered responses from more than 2,500 auto finance professionals, including director-level executives and senior decision-makers. The results indicate that while many lenders report a surge in fraud activity, confidence in existing AI-based fraud detection systems remains limited.
The findings point to what respondents described as growing “AI fatigue,” as some lenders question whether widely marketed AI solutions can reliably detect modern fraud schemes, particularly those involving generative AI or deepfake technologies.
“Lenders are no longer looking for futuristic promises; they are seeking immediate, tangible solutions to an escalating fraud crisis,” said Jessica Gonzalez, VP Customer Success and General Manager of Automotive at InformedIQ. “The data show a clear disconnect: fraud is becoming more sophisticated — powered by Generative AI — yet the majority of the industry is still relying on manual reviews that are slow, costly, and prone to error.”
Documentary fraud linked to loan losses
According to the survey, document-based fraud remains a significant challenge for auto lenders. More than half of respondents estimate that falsified documents, such as manipulated pay stubs, altered bank statements or identity misrepresentation, account for 10% to 19% of their total annual loan losses or charge-offs.
The study also indicates fraud activity has increased over the past year.
Nearly two-thirds of respondents reported that detected fraud grew between 5% and 25%, while 15.5% said their organizations saw increases of 25% or more.
Industry analysts note that advances in generative AI have made it easier to produce convincing fraudulent documents, creating new challenges for lenders relying on traditional verification methods.
Manual verification remains costly and slow
Despite growing investment in automation across financial services, many lenders continue to rely heavily on manual review processes to verify loan documents and applicant information.
The survey highlights several operational challenges linked to these manual workflows:
- 58% of lenders estimate manual reviews of flagged loan files cost between $50 and $100 per case.
- 55% say manual stipulation reviews delay loan funding by 16 to 30 minutes on average.
Some respondents suggested that improved automated verification tools could significantly change underwriting operations. If automated systems could achieve 99% confidence in document verification, 38% of lenders said they could potentially redeploy more than half of their underwriting staff to other tasks.
AI adoption continues, but concerns remain
Even as financial institutions continue exploring automation, the survey suggests confidence in AI-based fraud detection tools is still developing.
More than half of respondents (55%) described themselves as only “slightly confident” in their ability to detect sophisticated counterfeit documents generated by generative AI systems or deepfake technology.
Another concern cited by lenders involves “data hallucinations,” a term used to describe situations in which large language models generate plausible but inaccurate outputs. According to the survey, 52% of respondents identified this issue as their primary concern when evaluating AI solutions.
The study also identified potential gaps in fraud monitoring practices. Sixty percent of organizations reported that they rarely check historical records to determine whether documents have been reused across multiple loan applications or across lenders.
Regulatory pressure expected to increase
Respondents also expect regulatory oversight to intensify in the coming years.
According to the survey:
- 39% anticipate stricter enforcement at the state level.
- 33% expect increased scrutiny from federal regulators such as the Consumer Financial Protection Bureau and the Federal Trade Commission.
Lenders also believe document verification requirements may expand beyond auto loans. Mortgage and home equity lending was cited by 32% of respondents as an area likely to face increased document scrutiny, followed by personal and unsecured lending, mentioned by 23%.
Continued investment in AI and fraud detection
Despite concerns about current tools, lenders are still planning additional investment in artificial intelligence systems.
The survey found that 43% of respondents intend to prioritize AI investments in credit risk modeling, while 24% plan to focus specifically on fraud detection and prevention technologies.
The results suggest that although skepticism toward AI tools exists, financial institutions continue to view automation as a necessary component of modern lending infrastructure, particularly as fraud tactics evolve alongside new technologies.
