ML use cases in financial services
The Financial Services Industry (FSI), one of the most technologically savvy industries, is a front-runner in ML investment and adoption. Over the last several years, I have seen a wide range of ML solutions being adopted across different business functions within financial services. In capital markets, ML is being used in front, middle, and back offices to support investment decisions, trade optimization, risk management, and transaction settlement processing. In insurance, carriers are using ML to streamline underwriting, prevent fraud, and automate claim management. And banks are using ML to improve customer experience, combat fraud, and make loan approval decisions. Next, we will discuss several core business areas within financial services and how ML can be used to solve some of these business challenges.
Capital markets front office
In finance, the front office is the business area that directly generates revenue and mainly consists of...
