Bespoke OTC derivatives continue to be an important risk management tool for portfolio managers, yet remain a headache for middle office teams. But burgeoning AI technologies, including document parsing and intelligent exception management, are poised to solve these operational challenges.
It’s no secret that clean, reliable data (and a lot of it) is crucial when implementing learning technologies. Within asset management operations, however, gathering ‘good data’ is met with significant roadblocks. As a result, OnCorps’ data scientists were forced to get creative when thinking about how to successfully design, train, and implement AI algorithms within fund operations.
Psychology research has proven that the human brain can handle only a certain amount of information before cognitive performance begins to decline. OnCorps’ research team thought to apply this behavioral theory to an oversight environment to test how well humans are able to process large amounts of data and identify errors.
After analyzing over a decade of NAV errors and their root causes, OnCorps’ data science team created a comprehensive, algorithmic approach to overseeing granular accounting data to identify potential NAV-impacting anomalies.
The OnCorps team was asked to build an AI platform that would reduce as many hours as possible by error checking a complex and lengthy semi-annual financial statement.
