From Faked Invoices to Faked Executives, GenAI Has Transformed Fraud

Generative artificial intelligence, encompassing technologies like deepfakes and advanced voice synthesis, has become a double-edged sword in payments and cybersecurity.

Last year, a finance worker in Hong Kong transferred $25 million to fraudsters after a video call with what appeared to be the company’s chief financial officer and other executives. The twist? Every participant on the call was a deepfake.

That defrauded business wasn’t alone. The PYMNTS Intelligence April 2025 Invoice-to-Pay Automation Tracker® Series, “Rising Risk: Confronting Modern AP Fraud Threats” found that 90% of firms in the United States reported being targeted by cyberfraud in 2024. Business email compromise attacks affected 63% of companies — a 103% increase from the previous year.

Still, the deepfake incident underscores a chilling reality. Generative AI has transformed financial fraud, making it more sophisticated and harder to detect. While businesses harness its capabilities for efficiency, cybercriminals exploit it to craft convincing fraudulent schemes.

GenAI’s Growing Role in Financial Deception

Today’s AI-driven attacks aren’t limited to phish-y emails. Fraudsters now employ voice cloning and deepfake videos to impersonate executives, tricking employees into authorizing large fund transfers. The accessibility of generative AI tools means that even low-level scammers can produce high-quality forgeries, blurring the lines between genuine and fake communications.

The report found that accounts payable (AP) departments have become prime targets for these advanced fraud techniques. Research indicated that 68% of organizations encountered at least one fraud attempt in 2024, with AP fraud manifesting in various forms, including phishing attacks, account takeovers and invoice fraud.

AP departments might as well have a target on their back. The traditional manual processes involved are ill-equipped to combat threats like generative AI. As fraudsters use AI to automate and scale their attacks, the reactive nature of manual fraud detection leaves businesses exposed.

In 2024, 86% of U.S. companies targeted by fraud reported financial losses, with nearly half losing more than $10 million. Beyond the immediate monetary impact, businesses face reputational damage, regulatory penalties and erosion of stakeholder trust.

At the same time, the psychological toll on employees who fall victim to these scams can’t be overlooked. The guilt and stress associated with being deceived by convincing forgeries can affect morale and productivity.

Countermeasures: Embracing AI for Defense

To combat the escalating threat, businesses are turning to AI-driven solutions. Advanced fraud detection systems use machine learning to identify anomalies in transaction patterns, flagging suspicious activities in real time. These systems can adapt to evolving fraud tactics, offering a proactive defense mechanism.

Integrating AI into AP processes can automate invoice verification, cross-referencing details with existing records to detect inconsistencies. By reducing reliance on manual checks, businesses can enhance accuracy and speed, minimizing the window of opportunity for fraudsters.

Technology alone isn’t a panacea; businesses must cultivate a culture of vigilance. Regular training sessions can equip employees with the knowledge to identify and report suspicious activities. Implementing strict verification protocols, especially for high-value transactions, adds another layer of security.

Collaboration is also key. Sharing information about emerging threats and successful countermeasures within industry networks can help organizations stay ahead of fraudsters.

In this high-stakes game of cat and mouse, complacency is not an option. As generative AI continues to evolve, so will the tactics of cybercriminals. Businesses must remain agile, continuously updating their defense mechanisms and staying informed about the latest threats.

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