29 Finance Monthly. Bank i ng & F i nanc i a l Se r v i ce s able to interact with users in a conversational way within a matter of seconds. Experts working in the finance industry have noted that the tool could be used for enhancing banks’ customer service or marketing efforts. Yet experts have also highlighted how ChatGPT can be a gateway to fraud. The chatbot can enable scammers from all over the world to craft emails that are so convincing they can get cash from victims without relying on malware or other unscrupulous techniques. Unsurprisingly, speculation is rising around what else the tool could enable - especially when developments are moving faster than regulation. The next question for the finance industry is how to proactively get ahead of the game and prevent fraud before it occurs. The answer lies in the same technology - AI. AI to the rescue It’s important for organisations to join up their defences. Having a robust, enterprise fraud framework in place will enable fraud to be identified and prevented across all channels. For example, through the deployment of AI, banks can analyse customerrelated and behavioural-based data, set up alerts and automate case management. This will help to create a holistic overview of fraud risk, as well as enhance accuracy. For years, banks tended to rely on rules-based technology to spot fraud risk. However, as fraudsters have got smarter these rules need to be continuously updated and tuned if they are to be effective. AI comes to the rescue here. The implementation of a model development framework will allow a business to import and execute rules via a real-time decision engine. Through the use of Machine Learning (ML), organisations can also be automatically alerted to any concerning changes in a person’s transaction history or behaviour - catching criminals in the act when masquerading as a customer. We are already seeing some organisations introduce adaptive machine learning techniques - which build on traditional ML to process large amounts of realtime, rapidly changing data - an approach which certainly needs to become more mainstream across the sector in order to catch fraud before it’s too late. AI-powered technology can also detect cases of false or synthetic identity in real-time, to ensure fraudulent activity is immediately stopped. For example, should a fraudster apply for a loan or credit, or seek to withdraw funds, using a fake identity this will be flagged and investigated. Similarly, AI allows organisations to stay one step ahead of fraudsters, producing a comprehensive fraud risk assessment - a targeted fraud landscape review with a focus on identifying current sources of fraud losses, process leaks and other pains. At SAS, we always test our AI models against challenger models and then optimise them as new data becomes available. When new scams arise, our systems immediately know. Customers are often left with limited options after falling victim to fraud, particularly if it occurs through a customer authorising a transaction themselves. More regulation could help here, but educating the public is of equal importance. With tools such as ChatGPT on hand, typos in emails are no longer the first indicator of a scam. The industry should look to invest significantly in both fraud detection and prevention technology if they are to avert a rise in fraud. “In the first half of 2022 alone, UK Finance revealed that criminals stole a total of through authorised and unauthorised fraud and scams.” £609.8M
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