
Criminals stole £24.3 million through AI-enabled investment scams between January and August 2026, using deepfake videos, manipulated images and false endorsements to make fraudulent investment opportunities appear genuine.
The figures, published by UK fraud reporting service Report Fraud on 27 October, cover more than 1,300 reports received during the eight-month period. People aged 60 or over were involved in 1,033 of those reports, accounting for nearly 80%.
The figures show how AI deepfake scams are giving criminals new ways to make familiar investment fraud more convincing. Fraudsters can use artificial intelligence to create realistic-looking advertisements, videos and online profiles that make fraudulent offers appear to have the backing of trusted people or organisations.
Report Fraud says criminals are using AI-generated or manipulated material in online advertisements and fake news articles. These can feature false endorsements from well-known public figures or trusted financial institutions, making an investment opportunity appear more credible than it really is.
A deepfake is an image, video or audio recording that has been generated or altered using artificial intelligence to imitate a real person. In an investment scam, criminals can use the technology to create a video that appears to show a public figure endorsing a financial product they have never supported.
Not every fake endorsement involves a deepfake, however. Some fraudulent advertisements use genuine photographs or video clips without permission, falsely suggesting that a public figure supports a particular company or investment.
The FBI has also warned that generative AI can help criminals produce convincing images, cloned voices, social media profiles and messages for financial fraud. These tools can make fraudulent promotions easier to create and more difficult for potential victims to recognise.
The scam often begins with a fake endorsement or investment advertisement. Someone who clicks on it may be asked to provide personal contact details. Criminals then make contact, posing as investment advisers or account managers and encouraging the person to put money into an apparently legitimate opportunity.
After an initial payment, victims may be shown what appears to be a growing investment balance on a professional-looking trading platform. The supposed profits are designed to build confidence and persuade them to invest more.
The deception can continue until the victim tries to withdraw their money. At that point, fraudsters may demand additional payments for supposed taxes, charges or withdrawal fees. These demands can leave victims losing even more money while trying to recover their original investment.
The Financial Conduct Authority (FCA) describes similar warning signs in its guidance on online trading scams, including fake investment websites, pressure to invest more and problems withdrawing money.
Of the more than 1,300 reports received by Report Fraud, 1,033 involved people aged 60 or over. That is nearly four in every five reports. The figures do not mean younger people are immune. They show that older people accounted for the largest share of reports in this particular group of AI-enabled investment schemes.
City of London Police Commander Ollie Shaw said: “The tactics criminals are deploying to commit investment fraud are becoming ever more sophisticated.”
The £24.3 million figure represents losses reported to Report Fraud between January and August 2026. It should not be treated as a complete total for every investment scam affecting people across the UK. The available figures also do not establish how many individual victims were involved.
Anyone considering an investment should check the firm independently before sending money. The FCA’s Firm Checker can help establish whether a company is authorised and has permission to provide the financial services it is offering.
A familiar company name, celebrity endorsement or professional-looking website is not proof that an investment is genuine. Criminals can copy legitimate branding and impersonate authorised firms. Be especially cautious if someone contacts you unexpectedly, promises unusually high or guaranteed returns, or pressures you to invest quickly.
Do not pay additional fees simply because someone claims they are needed to release your investment. If you think you have been targeted and have transferred money, contact your bank immediately. In England, Wales and Northern Ireland, reports can be made to Report Fraud online or by calling 0300 123 2040. In Scotland, contact Police Scotland on 101.
AI can make a fraudulent investment look more convincing, but it cannot make the opportunity genuine. Before sending money, verify the company, check its regulatory status and take time to seek independent advice.
More to Know About AI Investment Scams
- Scammers can impersonate authorised investment firms. The FCA warns that clone firms may copy a genuine company’s name, address and Firm Reference Number to make an unauthorised business appear legitimate.
- A genuine registration number does not prove who contacted you. Fraudsters can use the details of a real authorised firm while supplying their own website, email address or telephone number. Compare the contact details you received with those listed on the FCA’s official register.
- Check permission for the actual service being offered. A company may appear on the FCA register but still lack permission to provide a particular investment service. Check its specific permissions before proceeding.
- Not appearing on the FCA Warning List does not prove a firm is safe. The regulator says its list covers firms it knows about, and unauthorised businesses may not yet have been identified.
- Authorisation reduces risk but does not eliminate it. Checking a firm’s status is an important safeguard, but it cannot guarantee that an investment will be profitable or that no problems will occur.
Editorial Transparency
This article is based on the original Report Fraud announcement and published guidance from the Financial Conduct Authority and the FBI. Figures and statements are attributed to their original sources. The article also explains the limits of the reported figures and distinguishes confirmed information from wider context.




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