AI models are already delivering for financial firms

The finance industry has long been leading the field of data-driven innovation, and AI applications today range across virtually every domain, from risk management to customer service and user experience to improved efficiency, quality and speed of decision-making. For example, AI tools can enhance underwriting models by analyzing non-traditional data — such as online behavior or utility payments — thereby improving the assessment of credit risks and provision of credit access. In the context of fraud detection and anti-money laundering, machine learning models are capable of continuously monitoring transactional data to detect anomalies and suspicious patterns, thus improving accuracy and effectiveness of analytics tools to combat fraudulent transactions.

Overall, AI tools can strengthen regulatory compliance by enabling dynamic stress testing, portfolio analysis and real-time risk monitoring. At the same time, AI can boost operational efficiency. For example, in claims processing, AI models can flag high-risk claims early, empowering insurers to allocate experienced claims adjusters where they are needed the most. Building on this early identification of high-impact claims, GenAI can provide actionable recommendations (“next best action”), such as targeted intervention to reduce costs or duration of the claim, while streamlining low-risk claims for expedited settlements. For improved financial planning and portfolio management, robo-advisors use advanced algorithms to provide affordable, personalized investment advice based on a customer’s financial goals, risk tolerance and market conditions.