Morgan Stanley and Bank of America are focusing AI power on tools to make employees more efficient
“Keeping Humans in the Loop. The decision to deploy generative AI internally first, rather than externally, was in part due to generative AI’s most notable weakness: hallucinations….Deploying generative AI internally lessens the concern. It’s not used to autonomously serve a bank’s customers and clients but to assist bank employees, who have the option to accept or reject its advice or assistance.”
AI progress and adoption are accelerating – four factors banks should consider
“AI is already making substantial improvements in baking security and customer service. For instance, South State Bank implemented Tate, an AI-powered knowledge management bot that’s reducing employee search times from seven minutes to under 30 seconds. The Commonwealth Bank of Australia is also leveraging AI to scan over 20 million daily transactions, helping detect fraudulent activity and reducing customer wait time by 40%.”
Generative AI may shoulder up to 40% of workload, some bank execs predict
“About half of executives polled said their banks are actively piloting using generative AI in fraud detection and financial forecasting; 34% said that about cybersecurity. Fraud and cybersecurity are most common at the proof-of-concept stage (both 45%), followed by financial forecasting (20%).
About 78% are actively using generative AI or piloting its use for security or fraud prevention; 21% are considering it. A vast majority (85%) are turning to generative AI for data-driven insights or personalization.”
Why AI-Powered Verification Is Banking’s New Best Friend
“No discussion of the service economy would be complete without touching on artificial intelligence.We’re well past the proof-of-concept phase with AI, and Stratman said the advanced technology can help — and is being used by ValidiFI — to identify and combat fraud… ‘The machine learning and AI algorithms can analyze hundreds of thousands of transactional patterns that can then be used to mitigate fraudulent activities’ so that client firms can approve more transactions with a greater sense of the security of the transaction, he added.”
Building an AI Stack for Banking on AWS
“Gen AI/ML Center of Excellence (COE): COEs for the enablement of gen AI/ML applications and operations are a popular and effective way to build operational skills and disseminate best practices. As discussed in Designing a Cloud Center of Excellence there is no fixed pattern, beyond what works for your organization. They provide the most value when advocating for the use of gen AI and providing expert advice on ‘how’ to implement successful, defined governance and approval processes. They can also establish security and compliance standards—sharing best practices and evaluating new tools and approaches for delivery. COEs support the development of a gen AI environment that can scale the technology while reducing operational costs and risks. This frees the business to focus on the delivery of prioritized use cases.”