Global Report Warns Of Rapid Rise In AI-Driven Identity Fraud

 

A sharp rise in digital identity fraud driven by artificial intelligence tools and automated cyber operations pushed duplicate identity attacks to more than double in 2025, according to a new global report released by identity verification firm Smile ID.

The findings appear in the company’s 2026 Digital Identity Fraud Report, titled From Selfies to Signals: Identity Enters the Security Era. The study indicates that organised criminal networks are increasingly reusing stolen or fabricated identity data across multiple digital platforms to bypass security systems.

Data analysed in the report covers more than 200 million identity verification checks conducted during 2025 across 37 industries in over 35 countries. The sectors include banking, financial technology, telecommunications, e-commerce and other digital services that rely heavily on remote identity verification.

According to the report, duplicate identity fraud attempts surged year on year in 2025 and nearly tripled the combined totals recorded in 2023 and 2024. These attempts typically involve criminals repeatedly submitting the same compromised identity credentials to gain access to accounts or services on different platforms.

The report attributes the surge partly to the rapid expansion of artificial intelligence tools capable of generating deepfakes and automating large-scale digital attacks at relatively low cost.

Mark Straub, Chief Executive Officer of Smile ID, said the pattern reflects a structural shift in how identity fraud is carried out.

“Fraud is no longer a KYC problem; it is a continuous cybersecurity challenge,” Straub said in the report. “AI enables fraudsters to operate at unprecedented scale and sophistication. Effective defence now requires network intelligence.”

The report argues that traditional identity verification systems built primarily around customer onboarding are increasingly insufficient, as attackers are now targeting verified accounts rather than newly created ones.

Authentication-related fraud attempts were found to exceed onboarding fraud by more than five times during 2025. Criminal actors are increasingly exploiting login systems, account recovery processes, device changes and high-value transaction flows in order to gain control of accounts that have already passed identity checks.

According to the report, this trend reflects the rising economic value of verified digital identities across industries such as banking and financial technology, where access to an authenticated account can enable financial transfers or other sensitive transactions.

The report also highlights regional trends across Africa, including significant activity in West Africa where digital financial services have expanded rapidly over the past decade.

Identity fraud attempts in the region were found to be largely driven by identity farming operations and account takeover schemes. Some incidents were also linked to insider assistance within organisations that manage digital verification systems.

About 65 per cent of suspected fraud attempts in West Africa involved biometric spoofing or no-face-match incidents during verification checks. These cases typically involve attempts to manipulate facial recognition systems by presenting altered or synthetic biometric data.

Automation and credential reuse at scale accounted for approximately 22 per cent of detected fraud attempts in the region. Another 13 per cent involved document integrity and presentation manipulation, including altered identity images, portrait anomalies and attempts to submit non-legitimate identity documents.

The report states that such methods are often combined in coordinated campaigns where attackers test different vulnerabilities within digital identity systems.

Beyond conventional spoofing methods, the report identifies a growing use of technically advanced attacks that target the identity verification pipeline itself.

During 2025, Smile ID said it detected more than 100,000 injection-style fraud attempts every month. These attacks typically involve the use of emulators, virtual cameras or manipulated device environments designed to bypass verification checks.

Unlike traditional spoofing attacks that rely on displaying fake images or videos to a device camera, injection attacks feed synthetic or pre-recorded media directly into the verification system. This approach allows attackers to bypass the camera entirely and interact with the verification process at a deeper technical level.

The report describes the technique as a major shift in the digital fraud landscape, where attackers are moving beyond visual deception toward systematic interference with the underlying verification infrastructure.

Artificial intelligence tools have further expanded the capabilities of fraud networks. According to the report, AI systems can generate deepfake biometric data, automate identity testing across multiple platforms and reuse verified biometric profiles.

These capabilities enable attackers to take control of accounts during verification processes and move funds across several platforms in coordinated campaigns.

To counter these threats, the report highlights the growing importance of device-level signals in identity verification systems.

Smile ID said its fraud detection systems increasingly rely on indicators generated through mobile software development kits installed within partner applications. These signals analyse device characteristics and behaviour patterns to identify suspicious activity.

Nearly 90 per cent of fraud attempts blocked by the company in 2025 were triggered by mobile SDK signals. The figure represents a significant increase from 68 per cent recorded in 2024, suggesting that device intelligence is becoming a critical component of identity security.

As a shared digital identity infrastructure provider serving multiple industries, the company said it can detect coordinated fraud patterns that may not be visible to individual organisations operating in isolation.

By analysing privacy-preserving metadata and behavioural signals across its network, Smile ID said it identified hundreds of thousands of coordinated fraud attempts that might otherwise appear legitimate when viewed individually.

Straub said the evolving nature of identity fraud requires collaborative security strategies that extend beyond individual verification systems.

“By leveraging privacy-preserving indicators throughout the customer lifecycle, we enable real-time adaptation,” he said. “Identity has entered the security era, where ecosystem-wide protection is essential to safeguarding the individual.”

The report concludes that as digital services continue to expand globally, identity verification will increasingly function as part of broader cybersecurity infrastructure rather than a one-time onboarding requirement.