AI and ML are valuable tools in preventing fraud by analyzing historical fraud data to identify recurring patterns and trends.
Fraud, especially its dynamic nature, is a major area of concern requiring significant time and resources to isolate from an enormous volume of transaction data generated by financial service institutions (FSIs).
As online transactions increase so is the increase in the velocity of fraudulent transactions. Can artificial intelligence (AI) and machine learning (ML) help FSIs deal with this enormous challenge? Increase the speed of accurate detection and even predict future fraudulent transactions.
At a panel discussion, Michael Michie, Artificial Intelligence Consultant, Simion Rutto, Group Head of Forensic and Security Services, Britam, Christopher Akolo, Regional Business Development Director, JuicyScore, Joel Onditi Group CEO and President, Pathways International touted AI and ML as the future of fraud prevention and detection in FSI that is here with us. The session was moderated by Carol Odera, Head of Content, dx5
These experts emphasized that AI, combined with real-time detection, can rapidly analyze vast volumes of data, enabling FSIs to identify anomalies in various aspects such as bank app usage, payments, and transactions. By leveraging datasets that capture a user’s typical behavioural patterns, AI can swiftly identify anomalies such as bank app usage, payments, and other transactions.
AI and ML are valuable tools in preventing fraud by analyzing historical fraud data to identify recurring patterns and trends. By recognizing these patterns, the experts said banks could proactively detect and prevent similar fraudulent activities in real-time.
The panel of experts also stressed the importance of training AI models using local data to maximize their effectiveness in detecting fraud orchestrated by local threat actors. They advocated for leveraging ML techniques to continuously learn from mistakes and improve the accuracy of AI models over time. By adopting these technologies and practices, FSIs can address the challenges posed by fraud and enhance their ability to detect and prevent fraudulent activities more timely and accurately.
The experts agreed that FSIs will continue to use AI and ML for the foreseeable future because of the technology’s ability to learn and improve their functions. The models can continuously adapt and improve by learning from new data and evolving fraud patterns which enables them to adjust accordingly to stay one step ahead.
