Criminals used deepfake videos, manipulated images and other AI-generated material to make fraudulent investment offers appear credible in more than 1,300 reports to Report Fraud between January and August 2026. City of London Police says reported losses totalled £24.3 million. People aged 60 or over accounted for 1,033 reports, nearly 80% of the total.

The cases typically began with a false endorsement by a public figure or trusted institution in an advert or fabricated news article. Victims who submitted their details were then contacted by people posing as investment advisers or account managers. Professional-looking trading platforms displayed supposed profits, followed by pressure to invest more and demands for further fees when victims tried to withdraw funds.

These are victim reports rather than a complete measure of UK losses, and the published total does not establish recovery rates. Report Fraud says each case in the dataset was reviewed to verify that AI or deepfake technology assisted the offence. The control challenge crosses advertising, identity, banking and platform governance. Effective intervention requires rapid sharing of endorsement signals, account and payment intelligence, and clear checks before a customer moves from an online advert into a high-pressure payment journey.


AI for Leaders: Governance, Risk & Why Strategy Must Come First
Is your organisation adopting AI without a defined strategy or governance? If so, you're not alone — and the consequences range from data breaches to reputational damage to safeguarding failures. AI is a strategic risk, not a silver bullet, and definitely not a magic data fairy. Without clear ownership, rules, and accountability, AI can proliferate across your organisation in ways that cost more — in time, money, and trust — than not using it at all. Speakers: Craig Clark, Director at Clark & Company Information Governance Services, and Stewart Tinson, Project Director, AI-360. You'll learn: Why "understand your why" must precede any AI rollout Which risks senior leaders most commonly overlook — from data leakage to safeguarding How to measure AI value through outcomes, not adoption metrics Why accountability for AI governance sits with the C-suite, not IT or compliance Key topics: AI strategy • Risk appetite • Data protection • Bias & fairness • Safeguarding • AI literacy • Governance models • Return on investment • Executive accountability • AI use case tiering For CISOs, CIOs, and senior leaders who need to govern AI responsibly — before it governs them.
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