AI is being applied in a range of client facing and internal processes – ranging from customer experience, sales and marketing, fraud detection, risk management, data management and trading operations. Based on regulatory requirements, banks have to make sure the models are "explainable". There are multiple control checks that are being put in place to review risks associated with ML based decision making. New approaches are being tried with Privacy-Enhancing Computation to collaborate across financial institutions. With advancement in technology, data starved ML initiatives are finding a new lease of life based on data pooled by multiple industry participants.
Login to this session as Gokulraj shares interesting insights on the adoption of AI in Financial Services with a full spectrum of aspects banks need to address in their AI/ML journey.