Analyst Insight: The Gartner® Market Guide for IT Vendor Risk Management Solutions

5 Ways to Leverage AI in Third-Party Risk Management

Use these tips to maximize the benefits of AI in your TPRM and supplier risk management programs.
Brad Hibbert
Chief Operating Officer & Chief Strategy Officer
July 25, 2023
Blog ai tprm 0723

AI and Third-Party Risk Management

Organizations increasingly rely on diverse third-party relationships and intricate supply chains to deliver goods and services to their customers. This complexity requires companies to manage a proliferation of third-party vendor and supplier risks while complying with an evolving regulatory landscape. However, even as third-party risk management (TPRM) programs continue to mature beyond annual risk assessments towards more comprehensive and continuous insights, traditional approaches are struggling to keep pace with the scale and complexity of modern business ecosystems.

The adoption of artificial intelligence (AI)-related technologies can help. AI's transformative capabilities offer unparalleled opportunities to streamline TPRM and supplier risk management (SRM) processes.

In this post, we delve into the profound impact of AI on TPRM and SRM, exploring how its advanced data analysis, predictive abilities, and automation drive enhanced risk mitigation strategies, foster better decision-making, and pave the way for a more resilient and competitive future.

Key Factors Behind the Demand for AI-Driven Third-Party Risk Management

The growth of AI-driven TPRM is fueled by several key factors:

Sophistication and volume of threats demand broader data insights and data-driven analytical models

Organizations must contend with a growing array of third-party risks, including data breaches, cyber-attacks, geopolitical tensions, and environmental concerns. The need to address these multifaceted threats demands a proactive and adaptive approach to TPRM and SRM that accounts for the overwhelming influx of data from multiple sources. Organizations therefore are recognizing that traditional risk management approaches are no longer sufficient to address the risks they face.

Consequently, there is an increased demand for broader data insights and data-driven models to strengthen TPRM and SRM practices. Companies are compelled to adopt cutting-edge technologies, such as AI-driven analytics and predictive modeling, to detect patterns and emerging risks.

Increasing complexity in the regulatory landscape

Globalization has given rise to intricate supply chains and extensive networks of third-party relationships, each bringing unique risks and compliance requirements. Regulatory bodies worldwide are continuously tightening their grip on risk management practices, imposing stricter governance requirements and heightened accountability. Most guidelines are overlapping at best, and unclear at worst, leading TPRM teams to leverage AI to harmonize regulatory mandates to simplify reporting.

Talent scarcity creates barriers to program success and sustainability

The scarcity of talent is undeniably a significant barrier to the success and sustainability of TPRM and SRM programs. The specialized skillset required for effective risk assessment, continuous monitoring, and strategic decision-making is in high demand, leading to a dearth of qualified professionals.

However, amidst this challenge, AI emerges as a powerful solution to bridge the talent gap and bolster risk management capabilities. By leveraging AI-driven analytics, data processing, and predictive modeling, organizations can:

  • Augment their existing third-party risk management teams and achieve more efficient and accurate third-party risk assessments.
  • Streamline data collection and third-party risk monitoring processes, freeing up valuable time for risk managers to focus on strategic tasks.
  • Detect patterns and analyze vast data sets to enable early identification of potential third-party risks, enabling organizations to proactively mitigate them before they escalate.

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5 Ways to Use AI in TPRM and Supplier Risk Management

Embracing AI technology not only enhances the effectiveness of TPRM and SRM programs, but also ensures long-term sustainability by enabling organizations to stay ahead of evolving risks. As a complement to human expertise, AI empowers businesses to build more resilient supply chains and safeguard their operations in an increasingly complex and interconnected world.

Here are a few ways to maximize your organization’s usage of AI in third-party risk management:

1. Reveal hidden patterns and trends with analytics

AI has revolutionized TPRM and SRM by processing vast amounts of data from diverse sources. Through sophisticated data analytics, AI provides deeper insights into potential risks and uncovers hidden patterns and trends. Real-time monitoring and alerts enable proactive risk identification, empowering risk managers to take swift and informed actions in response to emerging threats.

AI's ability to analyze data at scale ensures a comprehensive understanding of complex supply chains and third-party relationships, paving the way for more effective risk assessment and mitigation strategies.

2. Improve risk forecasting with predictive modeling

AI's predictive modeling capabilities are a game-changer for risk managers. By analyzing historical data and market trends, AI can forecast potential risks before they materialize, enabling organizations to prepare and implement preventive measures. The ability to anticipate supply chain disruptions, supplier performance issues, and regulatory changes strengthens the resilience of the organization and minimizes the impact of potential risks. This forward-looking approach enables businesses to proactively adapt to dynamic market conditions and make better-informed decisions.

3. Streamline processes with AI automations

AI-driven automation streamlines TPRM and SRM processes, reducing the manual workload for risk managers. Routine tasks, such as data collection, risk scoring, and compliance monitoring, can be automated, freeing up valuable time for risk managers to focus on strategic planning and decision-making. The increased efficiency and accuracy of AI-driven processes ensure that risk managers can respond quickly to changing circumstances, making risk management more agile and responsive.

4. Improve quality of decision-making with AI insights

AI-generated insights provide risk managers with data-driven information, improving the quality of decision-making. By leveraging AI's analytical capabilities, risk managers can evaluate risks objectively, minimizing the influence of subjective biases.

Data-driven decision-making ensures that risk mitigation efforts are based on evidence and analysis, leading to more effective risk management strategies. AI also facilitates the visualization of complex data, enabling risk managers to communicate risk insights more effectively to stakeholders.

5. Improve supply chain resilience and competitive advantage with AI-supported risk management

Proactive risk identification, predictive risk assessment, and efficient risk mitigation strategies fortify supply chains against potential disruptions. Organizations equipped with AI-driven risk management capabilities are better prepared to navigate uncertainties and market challenges, positioning them as leaders in risk-aware and resilient supply chain management.

By gaining a competitive advantage through AI-supported risk management, organizations can differentiate themselves in the market, build stronger relationships with stakeholders, and ensure long-term sustainability in an increasingly dynamic and risk-prone business landscape. By leveraging the wealth of data and AI-driven insights, organizations can navigate the complexities of their business landscape with heightened agility and foresight, leading to improved risk management outcomes and a stronger competitive edge.

Next Steps: Request a Demo of the Prevalent TPRM Platform

As organizations increasingly rely on interconnected supply chains and third-party relationships, the need for comprehensive risk insights and timely decision-making becomes imperative. The exponential growth of data from diverse sources offers an opportunity to leverage AI and advanced analytics, enabling deeper risk assessments, predictive capabilities, and real-time monitoring. The rise in regulatory scrutiny and the surge in sophisticated threats further necessitate data-driven and AI-driven approaches to risk management.

For more on how you can leverage the power of AI in your TPRM program, contact Prevalent today or request a demonstration of the Prevalent Third-Party Risk Management Platform.

2014 04 10 Headshot Brad Suit
Brad Hibbert
Chief Operating Officer & Chief Strategy Officer

Brad Hibbert brings over 25 years of executive experience in the software industry aligning business and technical teams for success. He comes to Prevalent from BeyondTrust, where he provided leadership as COO and CSO for solutions strategy, product management, development, services and support. He joined BeyondTrust via the company’s acquisition of eEye Digital Security, where he helped launch several market firsts, including vulnerability management solutions for cloud, mobile and virtualization technologies.

Prior to eEye, Brad served as Vice President of Strategy and Products at NetPro before its acquisition in 2008 by Quest Software. Over the years Brad has attained many industry certifications to support his management, consulting, and development activities. Brad has his Bachelor of Commerce, Specialization in Management Information Systems and MBA from the University of Ottawa.

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