How AI and Tech Are Fueling a New Wave of Financial Fraud

Sophisticated Voice Scams Targeting the Elderly

A criminal network operating from Canadian call centers defrauded elderly US victims out of $21 million between 2021 and 2024. They exploited Voice over Internet Protocol (VoIP) technology to impersonate grandchildren and customized conversations using detailed personal data such as ages, addresses, and estimated incomes.

AI-Driven Voice Cloning Amplifies Fraud Risks

With the rise of large language models (LLMs), fraudsters can clone voices using just an hour of YouTube footage and a low-cost subscription. These AI tools enable highly convincing voice scams, increasing the success rate of deception. Phone scams are just one example of how criminals leverage technology to refine and scale their attacks.

Synthetic Identity Fraud and Credential Stuffing

Synthetic identity fraud now costs US banks $6 billion annually, making it the fastest-growing financial crime. Criminals fabricate fake identities, or "Frankenstein IDs," by exploiting personal data breaches. Automated credential-stuffing software allows testing thousands of stolen credentials rapidly across multiple platforms. AI-powered text-to-speech tools can even bypass voice authentication systems.

The Transformative Impact of Technology on Fraud

John Pitts, head of industry relations and digital trust at Plaid, states that technology has both catalyzed and transformed fraud. It has intensified existing fraud types and created opportunities for new, larger scale fraud schemes.

AI Multiplying Attack Vectors and Scaling Scams

AI tools enable fraudsters to increase the number of attack vectors exponentially. In advance-fee scams, where fraudsters promise large sums for upfront fees, AI helps identify victims faster and cheaper than before. AI-driven systems can conduct tens of thousands or even millions of simultaneous digital conversations, massively scaling fraud operations.

Further Reading

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This content was produced by Insights, the custom content arm of MIT Technology Review, and was fully human-written and reviewed.