How AI is changing operations: From settlement optimisation to automating risk monitoring
Tony Brownlee,
Jesse Sommerfeld and
Kyle Hansen
Additional contact information
Tony Brownlee: President, Kingland, USA
Jesse Sommerfeld: Head of Data Science, Kingland, USA
Kyle Hansen: Head of AI Engineering, Kingland, USA
Journal of Securities Operations & Custody, 2020, vol. 12, issue 2, 102-115
Abstract:
Banking executives continue to evaluate new ways to incorporate artificial intelligence (AI) into the middle and back office to improve efficiency, mitigate risk and reduce cost. Even with these efforts, a Business Insider report1 estimates the aggregate potential cost savings from AI applications at US$248bn by 2023 in the middle and back office. In this paper, the authors discuss two uses of AI that are experiencing investments from firms: settlement optimisation (maximising daily resolved trades by using AI to optimise the order that transactions are settled) and automating risk monitoring (using natural language processing to systematically review and filter content relevant to a specific risk-monitoring purpose).
Keywords: settlement optimisation; text analytics; risk monitoring; natural language processing; text summarisation; content collection; robotic process automation; event logging (search for similar items in EconPapers)
JEL-codes: E5 G2 K22 (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:aza:jsoc00:y:2020:v:12:i:2:p:102-115
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