[AI]Experian uncovers fraud paradox in financial services’ AI adoption

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The same technology that financial institutions deploying is being weaponised against them. That is the core tension running through Experian’s

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, and it’s a tension the company is in a position to name because it sits on both sides of it.

According to FTC data cited in the forecast, consumers lost more than US$12.5 billion to fraud in 2024. As per Experian’s own data accompanying the report, nearly 60% of companies reported an increase in fraud losses from 2024 to 2025. Experian’s fraud prevention solutions helped clients avoid an estimated US$19 billion in fraud losses globally in 2025, a figure that underscores the scale of the problem and how much defence now depends on AI matching the speed and autonomy of attacks.

The agentic AI issue

The most pressing finding in Experian’s forecast is what the company calls machine-to-machine mayhem, the point at which agentic AI systems, designed to transact autonomously on behalf of users, become indistinguishable from the bots fraudsters deploy for the same purpose.

According to Experian’s forecast, as organisations strive to integrate AI agents capable of independent decision-making, fraudsters are exploiting those same systems to run high-volume digital fraud at a scale and speed no human operation could sustain. The core challenge, as per the report, is that machine-to-machine interactions carry no clear ownership of liability; when an AI agent initiates a transaction that turns out to be fraudulent, the question of who is responsible has no settled answer.

Kathleen Peters, chief innovation officer for Fraud and Identity at Experian North America, framed the problem: “Technology is accelerating the evolution of fraud, making it more sophisticated and harder to detect. By combining differentiated data with advanced analytics and cutting-edge technology, businesses can strengthen fraud defences, safeguard consumers, and deliver secure, seamless experiences.”

Experian predicts that this will reach a tipping point in 2026, forcing substantive industry conversations around liability and the governance of agentic AI in commerce. Some organisations are already making preemptive moves.

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, for instance, has stated it blocks third-party AI agents from browsing and transacting on its platform, citing security and privacy concerns.

Four other threats the forecast identifies

Beyond the agentic AI issue, Experian’s forecast identifies four additional trends that financial institutions need to consider in 2026.

Deepfake candidates infiltrating remote workforces; Generative AI tools can now produce tailored CVs and real-time deepfake video capable of passing job interviews. According to the forecast, employers will onboard individuals who are not who they claim to be, granting bad actors access to internal systems. The FBI and Department of Justice issued multiple warnings in 2025 about documented instances of North Korean operatives using this approach to gain employment at US companies.

Website cloning overwhelms fraud teams; AI tools have made it easier to create replicas of legitimate sites, and harder to eliminate them permanently. As per the forecast, even after takedown requests are actioned, spoofed domains continue to resurface, forcing fraud teams into reactive patterns.

Emotionally intelligent scam bots; Generative AI means bots can conduct complex romance fraud and relative-in-need scams without human operators. According to Experian’s forecast, such bots respond convincingly, build trust over extended periods, and are becoming increasingly difficult distinguish from genuine human interaction.

Smart home vulnerabilities: Devices including virtual assistants, smart locks, and connected appliances create new entry points for fraudsters. Experian forecasts that bad actors will exploit these devices to access personal data and monitor household activity as the connected home becomes a more greater part of everyday financial behaviour.

Financial institutions’ responses

According to Experian’s

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, drawing on responses from more than 200 decision-makers at leading financial institutions, 84% identify AI as a critical or high priority for their business strategy over the next two years. A further 89% say AI will play an important role in the lending lifecycle.

The governance dimension, however, is where institutions struggle. According to the same report, 73% of respondents are concerned about the regulatory environment around AI, and 65% identify AI-ready data as one of their biggest deployment challenges. Data quality was rated the single most important factor in choosing an AI vendor, which positions Experian’s data-first positioning at the intersection of what financial institutions say they need most.

On the compliance side, Experian’s AI-powered Assistant for Model Risk Management addresses one of the most resource-intensive requirements facing institutions deploying AI. According to a 2025 Experian study of more than 500 global financial institutions, 67% struggle to meet their country’s regulatory requirements, 79% report more frequent supervisory communications from regulators than a year ago, and 60% still use manual compliance processes. In Experian’s announcement, the company states that more than 70% of larger institutions report model documentation compliance involves over 50 people, a figure that signals the scale of the automation opportunity.

Vijay Mehta, EVP of Global Solutions and Analytics at Experian Software Solutions, described the challenge the product addresses: “The AI-enabled speed of data analytics and model development is driving unprecedented business opportunities for financial institutions, but it comes with a challenge: global regulations that require time-consuming documentation. Experian Assistant for Model Risk Management helps solve this labour and resource-intensive requirement with end-to-end model documentation automation.”

The data quality foundation

Running underneath Experian’s fraud and compliance products is the same structural argument that appears in both

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and

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AI narratives that appeared this week: AI is only as reliable as the data it runs on. As per Experian’s Perceptions of AI Report, 65% of financial institution decision-makers consider AI-ready data one of their biggest challenges, and data quality is the most critical factor influencing trust in AI vendors.

That is not a coincidence of messaging. It reflects a constraint facing financial services institutions as they move AI from pilots into production credit decisioning, fraud detection, and regulatory reporting; functions where explainability and auditability are not optional.

Experian’s CDAO Paul Heywood is among the confirmed speakers at the AI & Big Data Expo, part of

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, taking place 18 – 19 May 2026 at the San Jose McEnery Convention Centre, California.

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is a Platinum Sponsor at TechEx Global.

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