State Street and its research arm State Street Associates have collaborated to optimize their securities lending business through the deployment of an internally developed machine learning model.
The project’s goal was to identify when general collateral securities would transform into hard-to-borrow securities, which have greater demands and earn higher fees.
The events and few are far between, according to Yasser El Hamoumi, assistant vice president, trading and algorithmic strategist (securities finance) at State Street and who presented at the AI in Finance Summit in Midtown Manhattan.
However, lending hard-to-borrow securities represent 60% of the revenue SSA earns from securities lending while making up 20% of its loans by volume, added co-presenter Travis Whitmore, a quantitative researcher at SSA.
The full article is available at https://www.marketsmedia.com/state-street-and-ssa-optimize-securities-lending-with-ai/