Deepfake technology, powered by artificial intelligence, increasingly challenges compliance and fraud prevention processes in the financial and insurance sectors by enabling fraudsters to create convincing fake media that bypass traditional internal controls. This evolving threat has led to significant financial losses, necessitating the adoption of advanced detection technologies and continuous monitoring to combat these sophisticated scams.
Deepfake Identity Verification Challenges
Deepfake technology poses significant challenges to remote identity verification systems, particularly in the financial sector. Fraudsters can now create highly convincing fake images, videos, and audio to circumvent traditional security measures. Identification and verification based on "seeing is believing" is losing its reliability without technological assistance and additional training of all three lines of defense.
The Guarding reported about the case where employee was tricked by someone posing as senior officers of the company into transferring £20 m to a fraudster.1
To combat these threats, organizations are implementing advanced detection technologies, multi-modal biometrics, and continuous monitoring systems. However, as deepfake technology evolves, identity verification solutions must constantly adapt to stay ahead of increasingly sophisticated fraud attempts
Financial Document Fraud
Deepfakes pose a significant threat to Know Your Customer procedures, with criminals using AI to create convincing fake identity documents. Financial institutions have reported a surge in sophisticated forgeries, including AI-generated photos and videos designed to bypass verification systems. Common tactics include:
Creating synthetic identities by combining real and fake information
Altering existing ID documents with AI-generated elements
Producing entirely fake government IDs that can fool traditional checks
A week ago, the U.S. Financial Crimes Enforcement Network issued the FinCEN Alert on Fraud Schemes involving Deepfake Media Targeting Financial institutions2. To combat this, financial institutions are adopting multi-factor authentication, live verification checks, and advanced AI-powered detection techniques. Red flags issued by FinCEN are valuable recommendation across industries:
A customer’s photo is internally inconsistent or is inconsistent with their other identifying information
A customer presents multiple identity documents that are inconsistent with each other.
A customer uses a third-party webcam plugin during a live verification check.
A customer declines to use multifactor authentication to verify their identity.
A reverse-image lookup or open-source search of an identity photo matches an image in an online gallery of GenAI-produced faces.
A customer’s photo or video is flagged by commercial or open-source deepfake detection software.
GenAI-detection software flags the potential use of GenAI text in a customer’s profile or responses to prompts.
A customer’s geographic or device data is inconsistent with the customer’s identity documents.
Insurance Deepfake Scams
Deepfake technology poses a significant threat to the insurance industry, enabling sophisticated fraud schemes that can result in substantial financial losses3. Fraudsters leverage AI-generated synthetic media to fabricate evidence for insurance claims, manipulating images and videos to support false claims. For instance, criminals have used deepfake technology to photoshop registration numbers onto "total loss" vehicles, allowing them to file fraudulent claims and reap undeserved insurance benefits.
The potential impact of deepfake fraud on the insurance sector is staggering, as it creates opportunities for exploitation during the underwriting and claims process. As insurers move towards automated claims processing, the risk of AI-manipulated evidence slipping through automated systems increases. To combat this threat, insurance companies are investing in AI-powered detection tools that can automatically assess the authenticity of images and videos submitted with claims.
Salviol’s prevention and detection
Salviol's IT fraud solutions have significantly enhanced their RAALS’ response to imagery fraud, particularly in the realm of deepfake detection for insurance and banking sectors. The company has implemented a comprehensive, multi-faceted approach to combat the rising threat of sophisticated image-related fraud. Besides technology, institutions must keep adopting their fraud awareness related to new forms of fraud and use of technology.
Reverse Image Search Integration: Salviol has integrated reverse image search capabilities into its RAALS platform. This powerful tool allows for the rapid identification of images that may have been used elsewhere online or stock photos being misrepresented as original content.
Metadata Examination: The system conducts thorough metadata analysis, unveiling crucial information about an image's provenance, including its creation date, origin, and potential modifications. This layer of scrutiny helps in establishing the authenticity of submitted images and provide additional leads to investigators.
AI-Powered Analysis: Leveraging AI RAALS performs intricate comparison analyses to detect even the most subtle inconsistencies in images. This advanced technique is particularly effective in identifying manipulated or artificially generated visual content.
By implementing RAALS, enhancing employee training, and updating fraud related policies, institutions can better protect themselves and their customers from the evolving threat of deepfake fraud. Continuous vigilance, adaptation, and collaboration between technology providers and financial institutions are crucial in maintaining trust and security in an increasingly digital world.
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1 - Company worker in Hong Kong pays out £20m in deepfake video call scam | Hong Kong | The Guardian