In the latest Chief Risk Officer (CRO) member network, Jaywing and UK Finance discussed the changing landscape of fraud detection.
After revealing that 41 per cent of all crime in England and Wales is now fraud-related, Diane Doodnath, Principal of Economic Crime at UK Finance, revealed that 70 per cent of this fraud is enabled online via social media. With the rising threat of fraud emerging from diverse sectors, Nick Sime, Head of Modelling at Jaywing, and I explored the House of Lords and Digital Fraud Committee's report, “Fighting Fraud: Breaking the Chain”.
The report emphasises the need for legislative reform and outlines some recommendations to combat the growing threat, including:
- slowing down the faster payments system for certain types of transaction to allow time for the review of fraud signals
- a new corporate criminal offence of ‘failure to prevent fraud’ across all sectors
- the introduction of a centrally funded consumer awareness campaign
At the heart of the report is the concept of data sharing. After outlining that only one per cent of law enforcement efforts are focused on economic crime, the paper states that “the private sector must be encouraged to combat fraud not only through facing the threat of corporate criminal liability or regulatory action, but also through the creation of a safe harbour for the sharing of data for the purposes of preventing fraud.”
20 years ago, many initiatives, like CIFAS, Detect, Hunter, SIRA and Foil, Jaywing’s fraud syndicate, had the common goal of sharing data to prevent this threat. These initiatives allowed firms to build models using a wider pool of data and gain a better understanding of complex fraud patterns.
However, data sharing has seen slow progress in recent times, particularly across industries, due to obstacles such as competition and data protection. The CROs expressed that a non-commercial organisation, like UK Finance, could play a vital role in facilitating data sharing between financial services, law enforcement agencies, and other industries, such as telecom and social media, to better prevent fraud, including scams instigated by social engineering.
The power of AI and machine learning technology
In addition to data sharing, firms must leverage the power of artificial intelligence (AI) and machine learning (ML) technology, which have proven to be highly effective tools in the fight against fraud. These techniques can not only be used to combat application and payment fraud but can also help fight social engineering scams through the real-time analysis of customer behaviour and identification of abnormal transaction patterns or login attempts. By combining cross-industry data sharing with sophisticated AI and ML technologies, firms can better understand and predict criminal patterns and behaviours and, in turn, prevent, or reduce the impact of fraud on their balance sheets and the UK economy.
During the event, some attendees expressed concern that the report, and fraud regulations more generally, don’t reflect any action that customers should take to protect themselves against suspicious activity, and that all the responsibility was on firms to educate and protect customers. With the Consumer Duty regulations fast approaching, it is likely that this responsibility will only grow.
It is clear that AI, ML, and data sharing are pivotal components of the solution. However, as the House of Lords’ report outlines, more education must also be done to increase consumers’ understanding of fraud and scams in order to truly win the fight, particularly with regards to social engineering scams.