The impact of financial fraud is devastating to individuals and their families. It can undermine hard won business reputations and is increasingly affecting the bottom line. Plus, of course, one experience is often just the start. AI is helping criminals to become even better at targeting the vulnerable. Fraudsters share information. A financial platform’s vulnerabilities are rapidly exploited. The same individuals are often targeted multiple times across different institutions with a level of sophistication that they are not able to understand or resist.
Fraud is no longer confined to specific products or channels, and institutions that appear low risk in isolation can still be exposed to organised activity that only becomes visible through cross-sector intelligence sharing.
AI, deepfakes and cyber break-ins are contributing to the ever-increasing risk of financial fraud. As one UK financial platform experienced recently, customers were targeted with AI generated adverts using fake images of trusted, high-profile individuals. The crypto-friendly image increased trust and reduced customer suspicion and was followed up by sophisticated fraudsters then guiding customers through application processes involving crypto platforms and savings accounts. The highly effective psychological manipulation convinced customers to open and fund multiple accounts.
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In this case, the spike in activity over a two-week period was spotted by the building society, with several transactions intercepted. However, some customers lost access to funds, confirmed they had endured financial loss with other providers and experienced emotional distress. The criminal attack highlighted the importance of improved fraud detection and customer education; but it also challenged the financial institution’s belief that it was at low risk of being targeted.
And this is one of the most challenging concerns for an industry that has seen extraordinary changes in operating models in recent years. While Know Your Customer (KYC) requirements are increasingly demanding, the reality of today’s investment and lending models is a separation from customers: activity is online or via call centres, with limited face to face interaction. Ironically, while this shift in behaviour by both customers and criminals has compelled financial organisations to invest ever greater resources into anti-fraud activity, those operations still heavily reliant on face-to-face activity can underestimate the sheer scale of the risk now faced.
Misplaced trust
Smaller building societies, equity release providers, even credit unions, engage in high levels of personal, often face to face, contact with customers. This direct interaction inspires trust and increases their KYC confidence. But criminals are employing a level of sophistication that can swiftly sidestep traditional anti-fraud activity. Furthermore, these organisations are also on the front line when it comes to the rising tide of elder abuse. Family members and care workers exploiting the failing mental health or faculties of older individuals to fraudulently access their money costs the UK over £16bn annually, with this figure projected to rise to more than £25bn per year by 2050 if urgent action is not taken.
Fake documentation can be extraordinarily compelling. There are millions of synthetic identities in circulation in the UK alone with AI-enabled synthetic profiles blending genuine National Insurance details with faked biometrics and addresses to bypass verification checks. Website cloning, where fraudsters replicate legitimate sites to phish consumers, are becoming easier to create through AI tools and harder to eliminate. Even after takedown requests, spoofed domains continue to resurface. Advances in large language models built on autoregressive transformer architectures are also making fraudulent communications increasingly natural and persuasive. This is contributing to a rise in sophisticated vishing and social engineering attacks, where victims place misplaced trust in what appears to be a legitimate conversation with a trusted organisation or individual.
Even if these situations don’t affect the financial institution directly, when customers are tricked into sharing their credentials there is a knock-on impact on credit card fraud, identity theft and synthetic identities which lead to other forms of financial fraud. Furthermore, the personal contact model reduces customer wariness, predisposing individuals to trust any communication from or about that institution. When faced with the enormous sophistication of today’s fraudulent activity and the active targeting of individuals at their most vulnerable – at retirement or after the death of the partner – they are easy victims.
Industry collaboration
Anti-fraud technology is continually evolving. The latest generation of tools are using AI to do a deep dive into identity documents, using meta data to highlight anachronisms, for example. Constant vigilance to track trends in unexpected customer activity is vital – but it is also important to share this information. Proactively updating other financial institutions about suspicious activity can rapidly identify a new trend, allowing every institution to be on its guard.
This is particularly valuable for those organisations still reliant on legacy systems that do not support the real-time monitoring required for fast insight into emerging trends. Combining shared insight with AI assistants that can work through transaction history to highlight the repeated use of a name or address or a particular pattern in money movement is extremely powerful, allowing anti-fraud activity to be ever more targeted.
This collaborative approach also allows institutions to ensure their customer advice and education is rapidly updated in response to new criminal trends. It provides quick recognition that fraudsters are exploiting changes in regulation or tax planning, such as the recent changes to ISA allowances and the fears created by the addition of pension pots to Inheritance Tax, for example. It quickly highlights the targeting of start-up financial institutions – or those expanding into new areas or customer groups – by testing their systems for weakness and opportunity. Information sharing is the foundation for mitigating the risks now affecting every single financial provider.
Conclusion
Every financial institution is now vulnerable to fraudulent activity, irrespective of size, areas of business focus or depth of customer relationship. The levels of sophistication now being deployed by criminals are creating new risks. The way frauds are enacted are constantly evolving and without proactive information sharing and real-time monitoring, institutions will become ever more vulnerable; their customers ever more exposed. Every institution has a role to play. Increasing vigilance. Sharing information. Understanding their position within the broader financial ecosystem.
This is a fight that requires collaboration and cooperation. It is only by working together, sharing experiences and expertise, being open about both frauds that succeeded and methods of identifying and preventing fraud – from technology innovations to customer education and anti-scam tools – that the industry can face the threat head on and shift the dial to reduce the risk to both customers and the bottom line.
Dave Rossi, Managing Director at National Hunter
