Reported by Parya Lotfi

(Excerpt shown below. To read full report, go to: https://www.forbes.com/councils/forbestechcouncil/2025/06/23/how-deepfakes-are-disrupting-kyc-and-financial-security/)

Inside The Deepfake KYC Fraud Playbook

Deepfake-enabled KYC fraud follows a methodical, multistage process:

1. Data Acquisition: Fraudsters begin by collecting personal data, in many instances using malware, social networking sites, phishing scams or the dark web. This data is then used to create convincing fake identities.

2. Manipulation: Deepfake technology is then used to alter identity documents. Fraudsters swap photos, adjust details or even re-create entire identities to bypass traditional KYC checks.

3. Exploitation: Fraudsters use virtual cameras or prerecorded deepfake videos to supply spurious biometric data to verification systems. This helps them evade detection of liveness by simulating real-time interactions.

4. Execution: With these tools in place, fraudsters can open fraudulent accounts, apply for loans and carry out high-value transactions, all while appearing completely legitimate.

This opens up a tough reality: The conventional authentication procedures, including facial recognition or document verification, are no longer sufficient to counter these advanced attacks. Consider that, on average, there has been one deepfake attempt every five minutesover the past 12 months, while, in a recent 2025 study, only 0.1% of people can spot deepfakes.

Fortifying KYC: A Multilayer Defense Strategy

Together, these issues highlight an urgent need for financial institutions to evolve from reactive incident response toward proactive, AI-powered detection and multilayer defenses.

Some of the technologies that companies should be considering in the fight against deepfakes include:

1. Multimodal Biometrics: Combine facial recognition with voice biometrics, behavioral patterns (e.g., typing rhythms) and advanced liveness cues to create overlapping verification barriers.

2. Explainable-AI Detection: Deploy AI tools trained to spot deepfake artifacts, such as unnatural flickering, mismatched body movement or inconsistencies between speech and facial expressions.

3. Layered Verification: Integrate document‐authenticity checks, geolocation validation and transaction‐pattern analytics alongside biometric scans to catch anomalies before account approval.

4. Continuous Monitoring: Extend fraud detection beyond onboarding. Real‐time AI monitoring of account behavior can detect suspicious transfers or device changes indicative of post-admission compromise.

5. Employee Training: Arm employees with deepfake-awareness training so they can spot red flags, such as off-sync audio or unnatural facial movement, in live or recorded customer interactions.

Beyond technology, institutions must establish robust internal protocols and cross-functional collaboration.