AI Can Support Third-Party Vendors and Supplier Risk Management Challenges

Although Artificial Intelligence (AI) has been around for quite a while, the adoption and evolution of AI-related technologies has dramatically improved over the past year.
AI can provide organizations with an easier way to manage third-party vendors and supplier risks and ensure compliance in this complex regulatory environment.

Third Party Vendors: Opportunities and Challenges

Organizations increasingly rely on third party vendors to deliver a wide range of products and services, because it is far more efficient and cost-effective than producing everything in-house. Unfortunately, this procedure also opens up the organization to an array of vendor and supplier risk exposure.

Complex global supply chains make it incredibly difficult to have clear visibility into the security and risk management practices of an increasing number of third parties.

Most importantly, how do the company’s security and compliance management teams mitigate risks they have zero visibility into?  It is a challenging but important responsibility because cyber criminals are increasingly attacking third party vendors in the supply chain to compromise sensitive data, apply ransomware and disrupt operations.

As third-party threats become increasingly sophisticated, it is taking more time for organizations to identify and eliminate third-party risk. There are several reasons for this shift:

  • The Volume of Data continues to increase, originating from an ever-growing number of sources. The vast quantities of data require more time and effort to analyze and review.
  • Risk Analysis Processes require extensive documentation, depending on the department managing the vendor and the risks they want to manage. Risks may be financial, operational, compliance, reputational, or information technology related, which significantly expands the type of documentation – and expertise – needed for analysis.
  • Regulatory Compliance Requirements may be unclear, but they are also increasingly rigorous, complicating remediation and reporting

Third-party risk management is now facing critical compliance challenges to companies in this highly regulated environment. As many organizations continue to face budgetary and resourcing and staffing concerns, their security and compliance leadership must continuously implement improvements to the efficiency of their third-party risk management (TPRM) program. This is vital to reduce the risk of breaches and cyber-attacks, minimize potential business impacts and protect the organization’s critical data, operations, and reputation.

AI Can Streamline Third-Party Risk Management (TPRM) Processes

Here are specific ways AI can improve third-party risk vendor and supplier challenges. 

  1. Automate the collection and analysis of risk data from a wide range of sources.  AI can automate the collection and analysis of data from a wide range of sources, such as financial statements, security logs and security certifications. AI can then predict future risks based on historical data from those items and current trends. This reduces the time and effort required to manage third-party risks and improves the quality of decision making.
  2. Provide context to simplify risk analysis and compliance reporting — Complying with a complex array of regulations can be a significant challenge for compliance, security, and audit teams, who often lack clear guidance on how to address risks. Frequently, the processes identified for validating controls are also inconsistent, further complicating the process. But while enormous quantities of data are time consuming for humans to analyze and process, professionally trained AI systems can automatically analyze vast quantities of risk data to provide context and identify patterns and trends. An AI solution makes it simpler for compliance and audit teams to evaluate risks and controls and generate guidance and remediation recommendations.
  3. Automate manual tasks to help risk managers be more initiative-taking. Risk managers traditionally spend a considerable amount of time sifting through spreadsheets, manually entering data, and generating reports. This makes it challenging to strategize, analyze emerging risks, and engage in long-term planning. Because AI collects and analyzes historical data and current trends, it can support projections of future risks. This will increase security and compliance professionals’ productivity and effectiveness to forecast, evaluate and mitigate enterprise risks. The result is faster, more accurate and data-driven decisions regarding risks related to third-party vendors and suppliers.

What to Focus on with AI TPRM

It has become clear over the last year that AI, particularly the large language models (LLMs) that have dominated the news, does not necessarily provide a perfect solution to every problem. Organizations leveraging AI tools must be aware of some of the potential risks and be certain that they are addressed.

  • Whether it comes from statistical anomalies, bad input, or ill-suited learning model data, AI can deliver an invalid interpretation as fact (and do it with confidence). This is known as hallucination. To address this risk, AI TPRM solutions must ensure that the data used to train the model is based on real third-party risk data — it must be accurate, diverse, and representative of real-world scenarios. Such solutions must continually fine-tune their models to ensure that they continue to improve by learning context and nuances specific to third-party risk. 
  • When AI systems are built using biased learning model data, the responses will inevitably be equally biased. Bias can be difficult to detect, therefore it is critical to use training data that is diverse and representative of the real-world population. It is essential to continuously update and retrain AI models to incorporate new data and mitigate potential bias. Human reviewers are an important way to identify bias in AI-generated content and decisions and assess the performance of the solution, which means solution providers must conduct regular audits of these AI models.

Managing third-party vendors and suppliers has always been a challenging aspect of risk management. From due diligence to compliance review to ongoing monitoring, risk managers are overwhelmed with demands on their time and attention.

An appropriately developed, trained, and maintained AI Solution for TPRM can automate routine tasks and provide advanced analytical tools to enable Risk Managers no longer to be burdened with labor intensive tasks, but instead focus on strategic activities and that benefit the entire organization.

Modevity Vendor Risk Management as a Service supports organizations by mitigating varied company and regulatory risks and utilizes powerful database technology, AI, and vendor assessment automation with continuous monitoring – to provide real-time reports for the identification of risks when conducting business with vendors across varied departments or operations.

Contact Information

Thomas J. Canova

Co-Founder, Chief Marketing Officer

Modevity, LLC



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