According to new research from The Alan Turing Institute’s Centre for Emerging Technology and Security (CETaS), the increasing use of artificial intelligence by romance fraudsters is making scams more efficient and harder to detect.
The research found AI has introduced new efficiencies that enable fraudsters to easily create more convincing personas, automate large-scale outreach, and refine psychological manipulation.
AI is being integrated into romance fraud in myriad ways, such as the use of deepfakes to generate personalised dating profiles, and AI-generated audio and video to enhance deception.
Large language models (LLMs) are also assisting in improving the scripts used to deceive victims, with AI translation tools enabling scammers to engage victims in multiple languages.
The paper noted that, while human scammers are still required to guide AI-generated content and then correct any inconsistencies, introductions generated by AI significantly reduce the effort and time required to target potential victims.
However, while AI is helping to enable and scale up romance scam operations, LLMs can also be valuable in combatting fraud. Their ability to create convincing scams suggest that, in the future, they could detect scam messaging.
As with other instances of online criminality, techniques are developing at a pace that current defences aren’t keeping up with, as explored in a recent CETaS paper.
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“The use of AI in romance scams is developing quickly, helping criminals integrate new technologies into existing fraud networks with recent cases extracting millions from those seeking genuine connection,” said lead author Simon Moseley, CETaS visiting research fellow and principal data scientist at the Home Office.
“Often vulnerable victims are coming to psychological as well as financial harm through AI-assisted fraud. As romance scams grow in scale and sophistication, there has to be a greater focus on better detection capabilities and stronger safeguards.”
The paper is part of a broader CETaS research project examining the role of AI in online criminality.





