AI and Blockchain Synergies Mitigate Deepfake Risk in KYC

Compliance with anti-money laundering (AML) and Know Your Customer (KYC) laws and regulations is often a major concern for digital asset firms. Despite efforts to monitor and detect fraud, digital asset firms face significant challenges due to advances in technological threats, including generative artificial intelligence.

Gen AI can produce highly realistic deepfakes, fake documentation, and can almost instantly weave together a compelling life story to support the false information, for example, by peppering a person’s social media accounts with fake posts. For example, scammers recently used deepfake technology to simulate a video conference call that included the CFO of a multinational financial firm and other executives, and tricked one worker into wire transferring nearly $26 million to the scammers.

In short, the ability of next-generation AI to produce compelling deepfake sounds and images almost instantly could wreak havoc on existing governance systems designed to protect consumers.

Current KYC mechanisms are insufficient with the advancement of next-generation artificial intelligence

AML and KYC programs are essential for financial institutions to verify the identity of their customers and ensure compliance with laws aimed at combating money laundering, fraud and terrorist financing. However, many cryptocurrency companies have weak or porous KYC checksleading to an increased risk of fraud. According to Money bankCryptocurrency users lost nearly $4 billion to “scams, data theft and cyber attacks” in 2022 and about $2 billion in 2023.

Since digital asset companies typically do not have physical locations like traditional financial institutions, they must use KYC methods adapted for a remote environment. Commonly used KYC verification methods include:

• Taking a selfie holding a hand-written sign with the current date;
• Take a photo of the user’s driver’s license or other government-issued identification; or
• Recording a live video that answers security questions to confirm the user’s identity and “liveness.”

However, AI generation can bypass these current verification methods. For example, services like OnlyFake use AI to create fake IDs that have supposedly passed stringent KYC checks on major cryptocurrency exchanges like Binance and Coinbase. These fake IDs are generated using neural networks and can be purchased for as little as $15. Deepfake Offensive Toolkit or dot creates deepfakes by injecting virtual cameras and allowing users to swap their face with an AI-generated face to pass identity verification. According to this article from the VergeFinancial institutions’ KYC identity verification tests, which typically require users to look into their phone or laptop’s camera, are easily fooled by dot-generated deepfakes.

Using Gen AI in combination with Blockchain can mitigate Gen AI-enabled fraud

Blockchain and artificial intelligence are complementary technologies that can be effective in fraud detection and investigation, both individually and in combination.

Blockchain for verification

Decentralization, immutability, and rule-based consensus are some of the key features of blockchain technology that make it useful for identity verification and fraud detection. For example, transactions written on the blockchain are immutable (i.e., the data cannot be deleted or changed), which can prevent potential fraudsters from altering transaction data. Additionally, transactions written on public blockchains, such as the Bitcoin blockchain, are fully searchable and transparent, making it difficult for fraudulent activity to go unnoticed. Blockchains are also distributed in nature, making it more difficult for a single entity or a small group of entities to make unauthorized changes to data on the blockchain. Finally, data on blockchains can be cryptographically hashed, generating a unique fingerprint that is nearly impossible to recreate. This feature helps track fraudulent transactions because if someone tampers with data on the blockchain, the hash value would also change.

AI for detection:

AI can improve fraud detection by analyzing user behavior patterns and identifying anomalies in real time. Unlike blockchain technology, which is useful for auditing past transactions, AI can learn and adapt to potentially fraudulent behavior in real time. For example, advanced AI detection algorithms can analyze user behavior patterns and identify anomalies, flagging suspicious activity that deviates from normal usage. AI can quickly sift through mountains of data and identify subtle inconsistencies that often escape human detection. Machine learning models and AI-based behavioral analytics enable AI to analyze user interactions such as mouse movement patterns and typing style, which can add an additional layer of identity verification on top of the blockchain. AI’s ability to proactively monitor and detect fraud and blockchain’s ability to authenticate user identity and transaction validity are a powerful combination.

There is an urgent need to develop solutions as next-generation artificial intelligence advances

Cryptocurrency-related cybercrime is only increasing as AI-powered deepfakes become more believable and realistic. However, in the face of this growing threat, several startups have developed AI-powered blockchain tools to combat fraud and other illicit activities in the digital asset space.

For example, BlockTrace and AnChain.AI are two companies that leverage the synergies of blockchain and AI technology to fight cryptocurrency-related crimes. BlockTrace, whose mission is to help governments and private businesses fight cryptocurrency-related financial crimes, recently in pairs with AnChain.AI, a company that uses AI capabilities to combat fraud, scams, and financial crimes in digital assets. BlockTrace and AnChain.AI will provide solutions to enable national security agencies to use AI to investigate smart contracts, conduct intelligence on blockchain transactions, and provide cybersecurity insights to national security officials.

The industry is on the cusp of fully leveraging the potential of AI and blockchain to combat AI-enabled fraud, and there is much more to come given the breakneck speed at which AI is advancing.

Fuente