Artificial intelligence and machine learning are emerging as the most defining tech-marvel in this new wave of financial services. The technology, along with the abundance of data, has given way to several innovative FinTech business models. Several promising players now use AI to solve some of the major problems for customers in the banking and financial services industry – think chatbots, PFM, robo-advisors, and so on.
Banks are never the ones to be left behind when it comes to tech adoption. With digital transformation and customer experience as the top most priority, banks are now banking on AI to deliver the next-gen service to their customers. Some of the most powerful banking and financial institutions are looking to seek partnerships, investments, and in-house developments to take advantage of application potential of machine learning and AI.
There is a variety of use cases and application-areas for AI in financial services. Whether you think of a conversational interface, software robots, recommendation engines, automated AML checks, behavioural analytics & profiling, real-time fraud detection, insightful trading, etc. – AI has a huge array of use cases. However, all these use cases can be categorised into four major categories: Front-Office (customer-Focused), Back-Office (operation-focused), Regulatory Compliance, and Trading/Portfolio Management.