Generative AI-Assisted Taxonomy Development for a Global Investment Bank

Enterprise Knowledge 05 Feb 2024
The Challenge A multinational financial institution with a century-long legacy, celebrated for pioneering financial solutions and shaping the global economic landscape, relied on unstructured data for risk management. With a vast array of risks to consider, and a wealth of insights generated by risk analysts, relying on text-based risk descriptions that proved to be limited in creating consistent reporting and tracking of risk over time. The risk analysis process consisted of risk assessors, employing natural language to articulate risks as they were identified and reported. However, due to the diverse vocabularies and writing styles prevalent across various departments and geographies, the utilization of these risk descriptions posed a considerable challenge in reusability and making them machine readable. Even when integrated with existing taxonomies, the varying language hindered the efficient aggregation and analysis of non-financial risks on a global scale.