As we enter ‘the most wonderful time of the year’ is it also the most fraudulent time of the year?
Can the combination of technology and human intervention limit the damage? Is this an area where AI can actually make a difference?
Recently I chaired discussions on fraud driven by social engineering or scams targeted at the elderly. I am always talking about the tech solutions and training that can help detect and protect financially vulnerable customers, so it seemed logical that my thoughts then turned to scams and fraud during the holiday season.
APP fraud is front and centre with the Payment Systems Regulator (PSR) who recently (October 2024) set guidelines for banks and financial institutions in regards to how they should handle fraud, especially with their more vulnerable customers (the Consumer Duty Act last year also got the attention of financial providers who have long ignored the impact their decisions have on those most in need of financial support).
Both regulations – action for protecting customers when the deed is done and action preventing it from ever even happening, especially during the holiday season where fraud rises significantly – are well overdue. This happens every year without fail. Why? The holiday season brings with it a spike in online transactions, giving fraudsters more opportunities to exploit vulnerabilities.
With AI entering the mainstream discourse and becoming a fixture into society’s lives, it’s only a matter of time for it to make a genuine impact on problems that only exist due to bad players exploiting the vulnerable. It is also prudent to mention that although AI is one route to changing the holiday fraud trend, it has also been the catalyst for increased fraud. According to a report by Signicat, 42.5% of all fraud attempts in the financial and payments industry now involve AI, of which nearly 30% of those attempts were successful.
So can AI help detect fraud for financial institutions? And if so, how can it help?
The short answer is yes, AI can help detect financial fraud; however, it will require a balance of AI and human action to prevent and fix fraud issues. Plus, by understanding how we detect fraud currently is key to understanding where AI will improve processes.
Currently, the key differences between traditional methods of fraud detection and AI-powered fraud detection are the adaptability of the models, the number of datasets, the cleanup of the data, its 24/7 monitoring capabilities, and the ensuing analysis.
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AI can cut through and better understand, at a quicker and higher rate of success, specific patterns of behaviour for each profile. It also flags, through various methods including biometrics, if someone is using a different system to access their financial data.
AI’s ability (through machine learning) to capture and analyze many data points – historical, location, biometrics, and even third-party data – to make a calculated score on the likelihood of fraud, gives it better scalability for the future. It can also use historical conversations through Natural Language Processing (NLP) and text analysis techniques to detect phishing or social engineering scams.
This is much more beneficial for financial institutions and their customers. Although there is an upfront cost to implementing AI at scale, the long-term cost-effectiveness is undeniable. Plus, the replacement of static rules and human bias with dynamic rules and preventative measures ensures that the customer’s assets are protected.
At the rate that AI is currently being implemented across everyday processes and workflows, it’s no surprise that AI is already being used and tested in various places to detect and rectify financial fraud (you can see this thorough piece by Skillwork on case studies around the world using AI successfully to detect fraud).
And throughout the holiday period, it will be telling to see if AI will improve or worsen the current £1.17 billion fraud issue in the UK, and what we can learn from it in 2025.
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