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