81% of Finance Leaders Faced AI-Powered Fraud — How Deepfakes Are Changing Payment Security

Introduction

A finance manager receives a video call from someone who looks and sounds exactly like the CEO, asking for an urgent payment to a new supplier. An accounts team gets an email from a long-standing vendor with updated bank details. Both requests are fake — generated or enhanced by AI. In 2026, this is no longer a rare scenario. It is routine.

A survey of 230 senior finance leaders by Certos, the fraud prevention unit of Early Warning Services, found that 81% of their organisations had faced an attempted fraud involving AI-generated or AI-enhanced content in the past year. At the same time, banks are fighting back with AI of their own. This guide explains how AI-powered payment fraud works, how banks and fintechs are using AI to stop it, and what US businesses should put in place now.

The Problem: Fraud That Looks and Sounds Real

Traditional fraud often had tell-tale signs: poor spelling, odd email addresses, unfamiliar voices. Generative AI removes those signals. Criminals can now clone a voice from a short recording, generate realistic video, and write perfect emails in any company's tone. According to the Certos survey, 84% of finance leaders said AI-enabled fraud is harder to detect than traditional fraud.

The most dangerous gap is timing. While 87% of respondents believed they were prepared for more sophisticated AI fraud, only 50% felt confident they could identify such threats before money left the account. Once a payment has gone, recovery is slow and often impossible.

Why It Matters

Payment fraud hits every business, not just banks. Any company that pays suppliers, runs payroll or accepts card payments is a target. Finance leaders in the survey named payment diversion — fraudsters tricking a company into sending money to the wrong account — as the biggest threat (43%), followed by detection gaps (38%) and executive deepfake impersonation (21%).

It also changes how businesses choose financial partners: 93% of the leaders surveyed said AI fraud risk is changing how they evaluate banks and payment providers. For fintech companies, strong fraud protection is now a sales advantage, not just a cost.

How AI Fraud — and AI Defence — Work, Explained

How criminals use AI:

• Deepfake voice and video to impersonate executives on calls.
• AI-written phishing and invoice emails that copy a real supplier's style.
• Synthetic identities built from real and fake data to open accounts.
• Scaled social engineering — thousands of personalised scam messages at once.

How banks and fintechs use AI to fight back:

• Behavioural and transaction monitoring that spots unusual payments in real time.
• Deepfake detection that analyses voice and video for signs of manipulation.
• In-app scam warnings — the UK's Starling Bank, for example, rolled out an AI agent that checks for 10 types of scams, including deepfake and investment scams, to its five million customers.
• Payee verification that checks whether the receiving account really belongs to the person or business the sender intends to pay, before money leaves the bank.

Benefits of AI-Powered Fraud Prevention

• Real-time protection. AI can flag a risky payment in milliseconds, before it is sent.
• Fewer false alarms. Smarter models block more fraud while declining fewer legitimate payments.
• Scale. Monitoring every transaction becomes affordable, not just high-value ones.
• Customer trust. Visible protection makes customers and partners more confident.
• Competitive edge. For fintechs, strong fraud controls help win enterprise customers.

Real-World Examples

Corporate finance: a Fortune 500 CFO quoted in the Certos research summed up the fear: a convincing fake request slipping through and sending company money to the wrong place.

Consumer banking: Starling Bank's in-app scam intelligence agent shows how AI can protect customers at the moment they are about to pay.

A US mid-sized business: a distributor in Texas adds an automated check to its accounts payable system: any change to a supplier's bank details triggers a hold, an AI risk score and a call-back to a known phone number before the next payment runs. The system is built by a custom software development company in the USA and connects to its existing ERP.

Common Mistakes

• Trusting a familiar face or voice. Deepfakes make "I saw them on the call" unreliable.
• Changing bank details by email. Any payment detail change should be verified through a separate, known channel.
• No dual approval. Large or urgent payments should always need a second person.
• Relying on training alone. Staff awareness helps, but AI fraud is designed to beat humans — you need system controls too.
• Treating fraud tools as optional. For fintech products, missing fraud controls can block partnerships and deals.

Best Practices for US Businesses and Fintechs

• Verify every payee change by calling a known number — never one from the request itself.
• Require dual approval for new beneficiaries, large payments and anything marked urgent.
• Add AI anomaly detection to payments, payroll and account changes.
• Create a "safe word" or call-back rule for executive payment requests.
• Log everything so suspicious activity can be investigated quickly.
• Review your partners. Ask banks and payment providers what AI fraud protection they offer.

Many of these controls are software features: approval workflows, beneficiary-change holds, audit trails and risk scoring. As an AI development company in the USA, we work alongside our cyber security team to build them into the finance systems you already use. As a custom software development company in the USA, we design each control around your workflow, and our API development work connects them to banks and payment providers. Fintech teams in New York, Florida and across the country use the same approach to make fraud protection part of the product.

Conclusion

AI has given fraudsters better tools, but it has given defenders better ones too. With 81% of finance leaders already facing AI-powered fraud attempts, waiting is not an option. The businesses that stay safe combine simple process rules — verify, double-approve, call back — with AI systems that watch every payment in real time. For fintech companies across the USA, building that protection into the product is quickly becoming the price of entry.