Goldman Sachs: Machine Learning-powered Watchlist Screening Tool
Winner of Celent Model Risk Manager 2021 Award for Data, Analytics, and AI
To support the bank’s high growth ambitions from its consumer banking business and fulfil its mission of building a digital bank of the future, Goldman Sachs needed a watchlist screening solution that would be efficient in minimizing the number of hits and effective in catching blacklisted individuals while being scalable enough to support a fast-growing client base. The bank recognized the potential of machine learning-powered screening solutions and, after a due diligence of third party solutions available in the market, decided to build an in-house tool for screening consumer banking customers. The solution provides major business benefits, including a one hundredfold reduction in alert volumes and an estimated US$30 million cost savings achieved through headcount reduction due to optimal alert generation.
Click on the video link below to watch a conversation between Farzad Mashayekhi, Managing Director at Goldman Sachs, and Arin Ray, Senior Analyst with Celent's Risk practice; Celent Risk research members can download the PDF of a detailed case study.