Deepfake fraud attacks rise 180% as identity checks fail

Deepfake fraud attacks rose 180% year on year, according to LexisNexis Risk Solutions. One in every 100 failed identity verification checks now involves a deepfake document, image or liveness video.

The figures point to growing use of AI-generated material in attempts to pass digital identity checks, open fraudulent accounts and take over existing ones. Passports, driver's licences and national identity cards are among the documents most often targeted.

The assessment comes as businesses handle rising volumes of digital identity checks across banking, payments and online services. Juniper Research estimates the total number carried out globally will reach 100.4 billion in 2026, up 16% from a year earlier.

That increase gives fraudsters a larger field to exploit, especially as more customer onboarding and account access functions move online. Organisations face greater exposure if identity verification controls do not keep pace with the quality of AI-generated content.

LexisNexis linked deepfake attacks to several types of fraud, including the creation of new accounts for criminal use, the takeover of existing customer accounts, unauthorised payments, withdrawals and online purchases, the laundering of criminal proceeds and the abuse of sign-up incentives.

Its latest Cybercrime Report also found that one in every 11 new account creations in 2025 was a fraud attack. Almost a fifth of all reported fraud involved unauthorised access to customer accounts, the research found.

Document targets

Fraudsters favour identity documents that can be reused and tend to carry higher value in verification processes. Passports, driver's licences and national ID cards ranked among the most sought-after documents, with those issued by the United States, United Kingdom, Germany and France highlighted as the most frequently faked.

The latest generation of deepfakes often differs from traditional physical forgeries. Rather than failing on one obvious flaw, AI-generated documents and images may contain several smaller defects that are harder for manual reviewers to detect.

That raises the importance of systems that can inspect fine details in document design and biometric evidence. Checks include analysis of holograms, microtext, etching, document structure and image integrity, as well as facial movements, light reflection and signs of image manipulation in liveness testing.

Kimberly Sutherland, Global Head of Fraud and Identity at LexisNexis Risk Solutions, said verification teams face a more complex challenge.

"Deepfakes vastly complicate digital identity verification. Protecting against this surge of attacks requires a solid line of defense incorporating end-to-end capture, fraud analysis and liveness checks. Even the smallest gap in your defenses is like an open window that a fraudster can climb through," said Kimberly Sutherland, Global Head of Fraud and Identity at LexisNexis Risk Solutions.

Detection pressure

The warning reflects a wider shift in fraud controls as identity-checking tools are asked to assess both document authenticity and whether the person presenting the document is real. For sectors such as financial services, eCommerce and digital platforms, that means balancing stronger fraud detection with the need to keep customer onboarding and login processes usable.

Juniper Research said the technical demands are increasing as fraud threats become more complex. It pointed to the need to combine multiple trust signals within one process rather than relying on a single form of verification.

"As digital identity verification evolves, the core requirements shift toward the technical ability to integrate multiple trust signals into a coherent system architecture. Effective solutions depend on the coordination of document authentication, biometric liveness detection and real-time risk analysis within a single workflow. Increasingly, fraud detection system success is defined by how well it can detect advanced threats such as synthetic identities and deepfakes while maintaining interoperability across standards and minimising latency and user friction," said Shane O'Sullivan, Research Analyst at Juniper Research.

LexisNexis said the pace of change in AI-generated fraud means businesses should expect more attempts to target digital services each day. It said the financial and reputational costs of missed attacks are rising as deepfakes become more realistic and more common in failed verification checks.

Sutherland said the issue is no longer theoretical for risk and fraud teams handling identity workflows at scale.

"Highly realistic deepfakes call for forensic examination of hundreds of security features: document structure, image integrity, holograms, etching and microtext. Deepfakes typically fail on several minor flaws, as opposed to physical forgeries that fail on one major issue, but they are not easy to spot with the human eye during manual checks. The same goes for deepfake images and videos. Checks need to assess micro movements in facial muscles, analyse light reflection and detect image manipulation and injection tactics," said Sutherland.

"The risk to businesses is real from both a financial and reputational standpoint. The reality is that AI-generated attacks are practically doubling year over year and getting more sophisticated with every attack," said Sutherland.