Beyond the Checkbox (Ep. 3): How the Right Tech Stack Can Drive Effective TPRM
Episode Summary
In this episode of Beyond the Checkbox, hosted by Matt Kelly, the discussion centers on third-party risk management (TPRM) and the challenges companies face in this domain. Carl Rydbeck, Head of Product Management at Certa, joins the conversation to dive into the intricate issues surrounding TPRM. The dialogue begins with the complexities businesses encounter due to evolving regulations and the lack of unified risk management processes. Carl emphasizes the interconnectedness of these challenges and highlights how outdated manual processes further complicate the TPRM landscape.
As the conversation progresses, Carl outlines essential technological capabilities that modern TPRM programs must possess. These include automated risk assessment, compliance tracking, and continuous monitoring of third parties. He stresses the importance of moving beyond mere onboarding of new suppliers to focus on the ongoing surveillance of existing ones. Carl identifies continuous monitoring as a particularly daunting task for companies due to the vast amount of data and the need for automated systems to proactively surface risks.
The episode also explores the role of artificial intelligence (AI) in enhancing TPRM programs. Carl explains the complementary roles of generative AI and traditional deep learning techniques in automating data gathering, risk analysis, and process design. He highlights the significance of integrating TPRM systems with other business applications to avoid data silos and improve efficiency. Carl concludes by discussing the crucial role of clearly defined responsibilities within organizations to ensure the smooth operation of TPRM programs, emphasizing the balance between best practices and customization to meet specific organizational needs.
Key Insights
The Evolving Landscape of Third-Party Risk Management
The landscape of third-party risk management (TPRM) is increasingly complex due to rapidly evolving regulations and the absence of unified risk management processes within many organizations. These changes require businesses to constantly update their TPRM strategies to stay compliant, which is a moving target that complicates the implementation of effective processes. Outdated manual processes exacerbate these challenges, making it difficult for companies to keep up with the dynamic risk environment. The key to overcoming these hurdles lies in adopting automated, scalable technologies that can adapt to regulatory changes and streamline risk management processes. By integrating these advanced technologies, organizations can better manage third-party risks and maintain compliance in a constantly shifting regulatory landscape.
The Importance of Continuous Monitoring in TPRM
Continuous monitoring is crucial for effective third-party risk management, as it involves the ongoing surveillance of third-party relationships to detect changes or emerging risks in real time. This task is particularly challenging for large companies with extensive third-party networks, as it requires managing and analyzing vast amounts of data. Manual monitoring is impractical due to the sheer volume of data and the need for timely risk identification. Implementing automated systems that proactively surface risks is essential for maintaining a robust TPRM program. By focusing on continuous monitoring, organizations can ensure they are promptly alerted to any changes in their third-party risks, enabling them to take proactive measures to mitigate potential issues.
Integrating Artificial Intelligence in TPRM
Artificial intelligence (AI) plays a transformative role in third-party risk management by automating data gathering, analyzing risks, and discovering insights. AI techniques, including both generative AI and traditional deep learning, enhance the efficiency and accuracy of risk assessment processes. These technologies facilitate the categorization and clustering of risks, making it easier to identify potential issues and streamline TPRM workflows. Additionally, AI can extract relevant information from existing documents and contracts, reducing the need for manual data entry and improving the overall effectiveness of TPRM programs. By leveraging AI, organizations can enhance their ability to manage third-party risks and ensure compliance with evolving regulations.
Beyond the Checkbox (Ep. 3): How the Right Tech Stack Can Drive Effective TPRM
Episode Summary
In this episode of Beyond the Checkbox, hosted by Matt Kelly, the discussion centers on third-party risk management (TPRM) and the challenges companies face in this domain. Carl Rydbeck, Head of Product Management at Certa, joins the conversation to dive into the intricate issues surrounding TPRM. The dialogue begins with the complexities businesses encounter due to evolving regulations and the lack of unified risk management processes. Carl emphasizes the interconnectedness of these challenges and highlights how outdated manual processes further complicate the TPRM landscape.
As the conversation progresses, Carl outlines essential technological capabilities that modern TPRM programs must possess. These include automated risk assessment, compliance tracking, and continuous monitoring of third parties. He stresses the importance of moving beyond mere onboarding of new suppliers to focus on the ongoing surveillance of existing ones. Carl identifies continuous monitoring as a particularly daunting task for companies due to the vast amount of data and the need for automated systems to proactively surface risks.
The episode also explores the role of artificial intelligence (AI) in enhancing TPRM programs. Carl explains the complementary roles of generative AI and traditional deep learning techniques in automating data gathering, risk analysis, and process design. He highlights the significance of integrating TPRM systems with other business applications to avoid data silos and improve efficiency. Carl concludes by discussing the crucial role of clearly defined responsibilities within organizations to ensure the smooth operation of TPRM programs, emphasizing the balance between best practices and customization to meet specific organizational needs.
Key Insights
The Evolving Landscape of Third-Party Risk Management
The landscape of third-party risk management (TPRM) is increasingly complex due to rapidly evolving regulations and the absence of unified risk management processes within many organizations. These changes require businesses to constantly update their TPRM strategies to stay compliant, which is a moving target that complicates the implementation of effective processes. Outdated manual processes exacerbate these challenges, making it difficult for companies to keep up with the dynamic risk environment. The key to overcoming these hurdles lies in adopting automated, scalable technologies that can adapt to regulatory changes and streamline risk management processes. By integrating these advanced technologies, organizations can better manage third-party risks and maintain compliance in a constantly shifting regulatory landscape.
The Importance of Continuous Monitoring in TPRM
Continuous monitoring is crucial for effective third-party risk management, as it involves the ongoing surveillance of third-party relationships to detect changes or emerging risks in real time. This task is particularly challenging for large companies with extensive third-party networks, as it requires managing and analyzing vast amounts of data. Manual monitoring is impractical due to the sheer volume of data and the need for timely risk identification. Implementing automated systems that proactively surface risks is essential for maintaining a robust TPRM program. By focusing on continuous monitoring, organizations can ensure they are promptly alerted to any changes in their third-party risks, enabling them to take proactive measures to mitigate potential issues.
Integrating Artificial Intelligence in TPRM
Artificial intelligence (AI) plays a transformative role in third-party risk management by automating data gathering, analyzing risks, and discovering insights. AI techniques, including both generative AI and traditional deep learning, enhance the efficiency and accuracy of risk assessment processes. These technologies facilitate the categorization and clustering of risks, making it easier to identify potential issues and streamline TPRM workflows. Additionally, AI can extract relevant information from existing documents and contracts, reducing the need for manual data entry and improving the overall effectiveness of TPRM programs. By leveraging AI, organizations can enhance their ability to manage third-party risks and ensure compliance with evolving regulations.
