Recent research by ORX has underscored a significant trend among financial institutions: the integration of Generative AI (GenAI) technologies to enhance data-driven risk management strategies. A global survey, which included some of the largest banks and insurance companies, revealed that nearly 45% of these firms are currently using mainstream GenAI assistants, with an equal percentage planning to deploy Large Language Models (LLMs) for operational risk applications within the next 18 months.

Adoption of GenAI Tools

Helen L’Abbate, Deputy Director of Research and Information at ORX, expressed optimism regarding the adoption of GenAI, noting that it offers valuable support in human decision-making. GenAI helps firms connect datasets, automate tasks, and improve decision-making in areas such as risk frameworks, taxonomies, and policy inquiry responses. This integration not only enhances efficiency but also provides valuable insights for firms aiming to manage risks more effectively.

The survey highlights that financial institutions are leveraging GenAI tools in various ways, including knowledge discovery, drafting code and documents, and improving internal communication channels. Among the most widely adopted GenAI tools, OpenAI’s ChatGPT leads the pack, used by 35% of respondents. Microsoft Copilot follows at 22%, Amazon Q at 13%, and Google Gemini at 7%. These tools are particularly beneficial for automating time-consuming tasks such as document summarization, preparing data for analysis, and creating responsive chatbots that provide quick access to risk-related information.

Large Language Models (LLMs) in Risk Management

While LLMs are still in the early stages of deployment in live production environments—currently used by only 14% of firms—the survey points to a promising future for these models. A substantial 77% of respondents indicated plans to incorporate LLMs into their operations in the near future. This reflects a growing belief that LLMs can significantly enhance operational risk management by offering better data analysis, improving decision-making processes, and ensuring more accurate risk assessments.

Moreover, the role of data in risk management cannot be overstated. An overwhelming 95% of firms acknowledged the critical importance of data as a foundation for effective risk management. Many of these firms are moving towards centralising their operational and non-financial risk (ONFR) data to streamline workflows and ensure better data accessibility across departments.

Conclusion: The Future of GenAI in Financial Risk Management

The integration of GenAI in financial institutions marks a turning point in how these organisations handle risk management. By combining artificial intelligence tools with traditional human expertise, financial firms can enhance decision-making, improve operational efficiency, and respond more effectively to evolving risks. The continued adoption of GenAI technologies, especially LLMs, is expected to provide even greater capabilities, making risk management more agile and data-driven in the coming years.

For more information, see the full reports on ORX’s findings and Finextra’s coverage of these trends.