The new Credit Abuse Risk model uses behavioral insights and Fair Credit Reporting Act (FCRA) data to detect these activities during prequalification offers, account origination or portfolio review so lenders can modify loan terms based on FCRA-complaint insights, the company said in a Friday (Jan. 30) press release.
Loan stacking is a form of fraud in which an individual quickly applies for multiple loans with no intent to repay them, according to the release. Credit washing is when a person tries to remove from a credit report information that is accurate but negative.
The Credit Abuse Risk model identifies atypical credit behavior, enables targeted decisioning without limiting consumer protections, provides insights across all credit tiers, and provides an FCRA-compliant score with adverse action reason codes, the release said.
The model works alongside Equifax’s Synthetic Identity Risk tools to provide lenders with a complete view of identity legitimacy and repayment risk, per the release.
“By focusing on application behavior in real time, Credit Abuse Risk quickly helps to reduce the potential for fraud and related costs,” Felipe Castillo, chief product officer for U.S. Information Solutions at Equifax, said in the release. “This supports a more confident lending environment, and helps keep credit available for consumers.”
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Equifax launched its Synthetic Identity Risk product on Jan. 23, saying it uses artificial intelligence (AI) to detect and help prevent synthetic identity fraud, a fast-growing threat in which scammers create a fictitious identity and use it to open credit accounts or obtain loans. Synthetic Identity Risk can be used at account opening or continuously as an account management tool.
Equifax said in October 2025 that it was preparing to launch new fraud prevention tools, including a synthetic identity model and a first-party fraud model.
“Fraud remains one of the most significant and rapidly evolving threats our customers face,” Equifax CEO Mark Begor said during an Oct. 21 earnings call. “We are leveraging our new advanced AI capabilities and unique data assets to deliver a new generation of fraud prevention tools that can identify risks that are invisible to traditional methods.”
PYMNTS reported in March 2024 that first-party fraud was increasingly warranting a first line of defense from the payment networks and that those networks were using data and AI to uncover fraudulent disputes in transactions.
