Machine learning is being rapidly adopted for a range of applications in the financial services industry. The adoption of machine learning in financial services has been driven by both supply factors, such as technological advances in data storage, algorithms, and computing infrastructure, and by demand factors, such as profitability needs, competition with other firms, and supervisory and regulatory requirements. Machine learning in finance includes algorithmic trading, portfolio management, insurance underwriting, and fraud detection, just to name a few subject areas.
There are several types of machine learning algorithms, but the two main ones that you will commonly come across in machine learning literature are supervised and unsupervised machine learning. Our discussion in this chapter focuses on supervised learning. Supervised machine learning...
