As an ML practitioner, it is essential for me to develop a deep understanding of different businesses to have effective conversations with business and technology leaders. This should not come as a surprise since the ultimate goal of any ML solutions architecture is to solve practical business problems with science and technology solutions. Therefore, one of the main areas of focus for ML solutions architecture is to develop a broad understanding of different business domains, workflows, and relevant data. Without this understanding, it would be challenging to make sense of the data and design and develop practical ML solutions for business problems.
Specifically, we will cover the following topics :
The Financial Services Industry (FSI) has always been at the forefront of technological innovation, and ML adoption is no exception. In recent years, we have seen a range of ML solutions being implemented across different business functions within financial services. For example, in capital markets, ML is being used across front, middle, and back offices to aid investment decisions, trade optimization, risk management, and transaction settlement processing. In insurance, companies are using ML to streamline underwriting, prevent fraud, and automate claim management. While in banking, banks are using it to improve customer experience, combat fraud, and facilitate loan approval decisions. In the following sections, we will explore different core business areas within financial services and how ML can be applied to overcome some of these business challenges.
We will specifically discuss the following topics:
In finance, the front office is the revenue-generating business area that includes customer-facing roles such as securities sales, traders, investment bankers, and financial advisors. Front office departments offer products and services such as Merger and Acquisition (M&A) and IPO advisory, wealth management, and the trading of financial assets such as equity (e.g., stocks), fixed income (e.g., bonds), commodities (e.g., oil), and currency products. Let’s examine some specific business functions in the front office area.