To reduce the workload of securities lending desks and enhance client returns, asset servicing companies are employing sophisticated machine learning algorithms developed in-house. Such companies offer securities lending programmes to pension funds, insurers and asset managers that use sophisticated artificial intelligence software to raise efficiency in pricing corporate bond loans.
The self-optimising algorithms at the heart of this artificial intelligence (AI) technology improve themselves with each iteration especially when they are able to work on large data sets, and lending programmes equipped with such technology are already seeing enhanced returns and reduced risks, which help bring them into line with leading players in the market.
For securities lending operations, machine learning and AI will be a key part of the business going forward, not just in the securities lending space but across all front and back office operations. Straight-through processing (STP) automation was the industry’s buzz phrase years ago, and indeed automation rates are still an important efficiency metric, however, machine learning has little in common with the former. Machine learning is a process based on powerful algorithms that constantly improve themselves in order to achieve better results each time. There are many everyday examples of machine learning in action, from natural language processing in speech recognition to YouTube’s video recommendation engine.
For the asset manager, the only noticeable impacts on the day-to-day business of machine learning in securities lending are ...