AI Use Cases in Third-Party Risk Management (TPRM)

Businesses are increasingly connected to their suppliers' networks and rely on their data for daily operations. Most transactions now occur at machine speed, and there are mountains of unstructured information coming from vendors, suppliers and service providers at different times and in a wide variety of formats. All of it needs to be sifted through and correlated to assess risk.

It seems not humanly possible to master third-party risk management as the landscape is too complex and it changes rapidly.  Third-party risk management (TPRM) programs are turning the spotlight on acute risks highlighted by our hyper-connected and increasingly AI-powered world.

Incidents like the CrowdStrike global outage stopping banks, airlines and even hospitals in their tracks for hours on end, and the half-billion people affected by the Ticketmaster breach have raised the threat stakes. Leaders begin to consider the catastrophic outages that could bring their organizations to their knees. 

Strategic Use of AI: Organizations should leverage AI to optimize their third-party ecosystems, detect risks swiftly, and capitalize on new opportunities for growth. Collaboration among stakeholders and experts is essential to develop holistic models that integrate systems and processes.  This is how it's done:

AI's Role in TPRM: AI can significantly enhance TPRM by:

• • Analyzing Risks Quickly: AI can sift through vast amounts of unstructured data from vendors and suppliers to compare, correlate, analyze, and identify risks in seconds as opposed to months. It can detect, for example, which vendors comply or do not comply with your internal IT, security or contracting standards, surface them in minutes and recommend ways to close gaps before adverse events occur.
  • Enhancing Resilience: AI can monitor and analyze processes to identify weak links and suggest improvements, For example, when sensors indicate that a threshold is nearing a critical point, actions can be taken to reduce the load or switch from one vendor to another, similar to the fail-over mechanisms used in many infrastructure systems., such as smart eco-cities using AI and IoT.
  • Improving Efficiency: AI can streamline processes by eliminating unnecessary steps, allowing your teams to achieve results more quickly.  It can signal anomalies and correlate information with speed and accuracy.  It can also monitor entire domains within your ecosystem, ensuring that your vendors address network issues and close vulnerabilities before they are exploited. While a human in the loop is still necessary, it will be used strategically alongside AI, which acts as an intelligent co-pilot.

Strategically adopting AI can help organizations improve risk detection, optimize risk management, and streamline business processes, positioning them for future success.

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Source:  Venky Yerrapotu, Forbes Technology Council