Equifax is doubling down on artificial intelligence (AI) to combat the rising tide of financial fraud even as its core business shows renewed strength.
On Tuesday (Oct. 21), the credit reporting agency reported a 7% overall revenue increase, led by a 13% jump in mortgage revenue, despite ongoing softness in the broader U.S. housing and hiring markets.
CEO Mark Begor said during the company’s earnings call that fraud has become “one of the most significant and rapidly evolving threats” faced by financial institutions and lenders. To counter it, Equifax is deploying new AI-driven fraud prevention tools that can uncover risks invisible to traditional systems.
“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,” Begor said.
Mortgage Growth Defies Market Trends
Despite a decline in the overall U.S. mortgage market, Equifax reported growth in its mortgage revenues — a sign that its data and analytics divisions continue to outperform cyclical market pressures.
| Metric | Q3 2025 Performance | Change Year-over-Year |
|---|---|---|
| Total Revenue | $1.43 billion | +7% |
| Mortgage Revenue | $212 million | +13% |
| Consumer Lending Revenue | $375 million | +20% |
| Auto & Card Lending | Strong double-digit growth | — |
| Employment & Income Verification (Workforce Solutions) | Stable with high demand | — |
The company credited its broad product diversification for maintaining growth across verticals. Even as housing markets remain constrained by higher interest rates, Equifax’s consumer credit and verification tools have helped it gain share among lenders eager to improve risk detection and borrower insights.
AI Tools Targeting Synthetic and First-Party Fraud
Equifax’s newest AI models focus on two of the most challenging types of fraud facing lenders: synthetic identity fraud and first-party (friendly) fraud.
- Synthetic Identity Model: This system analyzes billions of non-traditional data points — such as utility payments, digital behavior, and cross-platform patterns — to detect “ghost identities.” These are profiles created by combining real and fake personal information to establish credit and disappear after borrowing.
- First-Party Fraud Model: This tool identifies behavioral cues that suggest a borrower is taking out credit with no intent to repay. It’s designed to help lenders spot patterns that often slip through standard credit scoring models.
“The traditional fraud stack was designed for the analog economy,” explained Angela Hoffman, Financial Crime Risk Analyst at FinReg Labs. “What Equifax is doing — applying behavioral AI to massive data sets — is exactly the kind of modernization that financial crime prevention needs.”
According to industry estimates, first-party fraud costs U.S. lenders over $100 billion annually, encompassing chargebacks, false disputes, and ATM withdrawal reversals.
The Broader Push: AI Across Lending and Risk
The new fraud tools build on Equifax’s recent rollout of Ignite AI Advisor, an AI-powered decision-support system designed for financial institutions.
The system merges lenders’ internal data with Equifax’s proprietary credit and risk analytics, allowing teams to query data using natural language and receive interactive insights without specialized data science expertise.
“Ignite AI Advisor democratizes analytics,” said Felipe Castillo, Equifax’s U.S. Chief Product Officer. “It helps lenders gain a clearer view of portfolio performance and respond to shifting credit dynamics faster.”
Equifax said the solution helps clients measure delinquency, origination trends, and market share relative to peers while generating actionable insights for growth or risk mitigation.
| Equifax AI Innovation Highlights (2025) | Function | Impact |
|---|---|---|
| Ignite AI Advisor | Generative AI-powered analytics dashboard | Faster portfolio insights for lenders |
| Amplify AI Engine | Core model framework supporting AI innovation | Enables explainable and auditable outputs |
| Synthetic Identity Model | Detects ghost or fraudulent credit identities | Reduces lender losses from hidden fraud |
| First-Party Fraud Model | Identifies behavior suggesting non-repayment intent | Strengthens lender underwriting confidence |
Balancing Fraud Prevention and Market Opportunity
Equifax’s expansion into AI-based fraud detection comes amid a delicate balance: maintaining growth in traditional lending while safeguarding against new digital risks.
The company said consumer lending revenue surged 20%, driven by broad-based growth across auto, personal loan, and credit card markets. However, executives noted that fraud — particularly synthetic and first-party variants — continues to pressure lenders’ margins.
“The credit ecosystem is only as strong as its weakest link,” said Dr. Steven Marx, Senior Economist at the Center for Financial Analytics. “AI is redefining that strength by letting firms analyze risk behaviorally, not just historically.”
Equifax’s fraud prevention suite positions it to benefit from both regulatory and market tailwinds, as banks, fintechs, and mortgage originators increase their compliance budgets for anti-fraud and identity verification in 2025.
Competitive Landscape: AI Becomes the Core Differentiator
Equifax’s AI expansion mirrors moves by peers like FICO and TransUnion, which are also embedding generative AI to improve accuracy, explainability, and compliance.
FICO recently introduced tools to reduce AI hallucinations and strengthen auditability, while TransUnion is focusing on cross-platform fraud detection powered by data partnerships.
“Accuracy and trust are the new frontiers in credit data,” said Maya Patel, Lead Analyst at Fintech Equity Research. “Equifax’s dual play — AI-powered growth and AI-powered fraud prevention — could set a new benchmark for how data firms manage both opportunity and risk.”
Why It Matters: AI, Fraud, and Financial Stability?
Equifax’s new initiatives underscore a larger trend: AI isn’t just a growth enabler — it’s now a risk defense mechanism. As fraud tactics evolve, the ability to detect deception before losses occur could determine the resilience of the entire lending system.
With consumer credit expansion showing signs of stabilization and mortgage revenues rebounding, Equifax’s pivot toward intelligent fraud analytics signals how major financial infrastructure players are preparing for the next phase of the credit cycle — one where AI safeguards trust as much as it drives performance.
FAQs
What drove Equifax’s mortgage revenue growth?
Despite a weak overall mortgage market, Equifax saw a 13% rise in mortgage-related revenues thanks to demand for its credit data, verification, and fraud analytics tools.
What are Equifax’s new fraud prevention tools?
The company is rolling out AI-based synthetic identity and first-party fraud models designed to detect hidden or deceptive borrowing behaviors using billions of data points.
What is synthetic identity fraud?
It occurs when fraudsters combine real and fake personal data to create “ghost identities” that establish credit histories and eventually default.
What is first-party or friendly fraud?
It involves legitimate consumers misusing their own credit accounts — such as disputing valid transactions or taking loans without intent to repay.
How is Equifax using AI beyond fraud prevention?
Through Ignite AI Advisor and Amplify AI, Equifax is helping lenders analyze portfolios, benchmark performance, and identify growth opportunities using conversational AI interfaces.
What’s next for Equifax?
The company plans to expand AI capabilities across cloud-based lending ecosystems and deepen its partnerships with banks, fintechs, and regulators to advance trustworthy credit analytics.