The yin and yang of third party risk management and operational resilience

Article

As businesses increasingly rely on third-party vendors for critical services and innovation, the challenge of managing third-party risk becomes ever more complex. Traditional tools and processes often fall short, making way for generative AI as a potential game-changer.

Aug 23, 2024

Charles Forde, Chief Operating Officer, NFPE Investment Banking and Global Markets, Nomura

The yin and yang of third party risk management and operational resilience

The views and opinions expressed in this content are those of the thought leader as an individual and are not attributed to CeFPro or any other organization

The reliance on third parties necessitates advanced risk management strategies, as traditional tools and processes often fail to address the complexities and scale of modern operations.
Generative AI offers significant advantages for third-party risk management by improving data analysis, risk prediction, and real-time monitoring, yet it brings its own set of risks such as data privacy issues and system vulnerabilities.
Effective integration of AI in risk management requires a careful balance of human oversight and AI capabilities, with thorough testing and validation to prevent over-reliance and ensure ethical use.
To mitigate potential AI risks, organizations should implement stringent data security measures, ensure regulatory compliance, and maintain a 'Responsible AI' approach involving cross-disciplinary collaboration.