In today’s interconnected business world, organizations rely on a vast web of third-party vendors, suppliers, and partners. While these relationships are essential for growth and innovation, they also introduce significant security and compliance risks. A staggering 74% of organizations have experienced a third-party security incident in the past year, and the average cost of a data breach caused by a third party is a whopping $4.24 million. These statistics make it abundantly clear: traditional third-party risk management (TPRM) approaches are struggling to keep pace with the ever-evolving threat landscape.
Enter Artificial Intelligence (AI), poised to revolutionize TPRM. The global third-party risk management market is expected to reach a staggering $11.34 billion by 2028, with AI playing a central role in this growth. By leveraging AI’s analytical prowess and automation capabilities, organizations can significantly strengthen their TPRM posture.
The Growing Complexity of TPRM
Beyond the sheer volume of third-party relationships (the average organization has over 500), several factors are making TPRM increasingly complex:
- The Shadow Supply Chain:Many organizations struggle to map their entire network of third-party relationships, creating a blind spot known as the “shadow supply chain.” This lack of visibility makes it difficult to quantify and mitigate associated risks. Imagine a marketing agency unknowingly using a sub processor for data storage located in a jurisdiction with weak data privacy laws. A seemingly innocuous service like social media management could expose sensitive customer data through a hidden connection in the supply chain.
- Converging Risks:The lines between physical and cyber threats are blurring. A cyberattack on a power grid can cause widespread blackouts, while a compromised transportation system can disrupt entire supply chains. These interconnected risks necessitate a holistic approach to TPRM. Consider a scenario where a hacked freight management system redirects shipments containing hazardous materials, causing environmental damage and safety hazards.
- ESG Factors:Environmental, Social, and Governance (ESG) factors are gaining prominence. Organizations must now consider sustainability practices, labor rights, and ethical sourcing within their TPRM framework. Consumers are increasingly demanding supply chain transparency. A fashion retailer could face reputational damage if discovered to be using sweatshop labor through a third-party manufacturer.
- The Rise of AI:While AI offers immense benefits, its integration into the vendor ecosystem introduces new risk dimensions. Issues like algorithmic bias, explainability of AI decisions, and potential for intellectual property (IP) loss need to be addressed. An AI powered recruitment tool used by a staffing agency might exhibit bias against certain demographics, leading to discrimination lawsuits. Additionally, a compromised AI model developed by a third-party vendor could expose sensitive data or disrupt critical business processes.
Balancing Security and Business Agility
Effective TPRM requires a multipronged approach that balances security with business agility. Here are some key considerations:
- People:Security teams need to adopt a more collaborative approach. Educating stakeholders in business-friendly language and building strong relationships with internal partners (finance, legal, procurement) are crucial. Security briefings shouldn’t focus solely on technical jargon; instead, they should translate risks into business impacts, highlighting potential financial losses, reputational damage, and operational disruptions. Security champions within business units can also play a vital role in fostering a culture of security awareness.
- Process:A comprehensive TPRM process requires identifying all stakeholders across departments (finance, legal, procurement, IT, etc.), creating a standardized workflow that streamlines onboarding and ongoing monitoring, and ensuring vendor friendliness. The process should be efficient and not overly burdensome for vendors to avoid hindering business relationships. Collaboration tools and automation can streamline communication and information sharing throughout the TPRM lifecycle.
- Technology:AI provides powerful tools to automate tasks, identify and assess risks effectively, and make data driven decisions. Organizations should invest in AI powered TPRM solutions that integrate seamlessly with existing workflows.
AI offers a suite of tools to transform TPRM:
- AI powered Due Diligence:AI can quickly assess a vendor’s security posture, financial health, and ESG practices, streamlining the onboarding process and identifying potential red flags early on. By analyzing public records, industry reports, and social media data, AI can uncover hidden risks that might be missed in traditional due diligence processes.
- Risk Assessment Tools:AI can analyze vast amounts of data from various sources (contracts, financial statements, industry reports, news articles, threat intelligence feeds) to identify and prioritize potential risks posed by third parties. AI can also uncover hidden connections within the supply chain, providing a more holistic view of potential vulnerabilities.
AI in Action:
AI is transforming how organizations manage risk across their vendor ecosystems. Here are some real-world examples showcasing the power of AI in action:
- Financial Institutions:Predictive models leverage historical breach data to identify vendors most susceptible to data breaches. By analyzing vulnerabilities exploited and stolen data types, these models enable proactive risk mitigation measures, such as additional security audits or enhanced data encryption requirements.
- Manufacturing Companies:AI goes beyond basic risk assessments. Tailored risk mitigation plans can be crafted for each vendor based on factors like industry, size, location, and data access levels. This allows for a more nuanced approach to managing risk across a diverse vendor landscape. Enabling new opportunities for technology specific to manufacturing environments never accessible before like IT/OT in a comprehensive way measuring risk across the total landscape of the business.
- Healthcare Providers:Ransomware attacks are a major concern for healthcare organizations. AI powered predictive models can analyze historical attack data, including exploited vulnerabilities and data types encrypted, to identify high-risk vendors. This allows for targeted mitigation measures, such as increased cybersecurity awareness training for vendors with high access to sensitive patient data.
- Financial Services Companies:Continuous monitoring is crucial for identifying potential issues early on. AI powered systems can monitor a vendor’s financial health, security posture, and regulatory compliance in real-time. Additionally, these systems can scan news and social media activity for red flags that might indicate potential security incidents. Battling complex regulatory and financial crimes scenarios that can be spread across complex operating environments from call centers to online customer portals.
The Benefits of AI powered TPRM:
By leveraging AI, organizations can reap significant benefits for their TPRM programs:
- Improved Efficiency and Effectiveness:Automating tasks and leveraging data analytics streamlines the TPRM process and leads to more informed decisions.
- Reduced Costs:AI saves time and resources by automating manual tasks and optimizing risk mitigation strategies.
- Increased Visibility and Control:AI provides a holistic view of third-party relationships, enabling better risk identification and mitigation.
- Enhanced Compliance:AI powered compliance tools help organizations to do continuous and automated compliance saving significant time and resources.
- Monitor suspicious activity:AI can continuously monitor partner data access patterns, network traffic, and threat intelligence feeds to identify potential incidents early on, allowing for a swift response.
Four Key Takeaways for a Strong TPRM Program
- Embrace Business Agility: Ensure that your TPRM strategy supports fast-paced business operations while maintaining security.
- Connect Stakeholders: Build workflows that connect all internal stakeholders and foster collaboration to decouple dependencies.
- Leverage AI: Implement AI-driven solutions to automate and streamline risk management processes.
- Train and Empower Teams: Equip teams with the flexibility and skills needed to adapt to changing risk landscapes.
AI is not only a tool but a strategic partner in navigating the complexities of modern third-party risk management. By embracing AI-driven solutions, organizations can protect their extended business ecosystem and future-proof their operations against evolving threats.
About the Author
Phani Dasari is the Chief Information Security Officer of HGS, a leader in providing digital-led CX and IT services for hundreds of world class brands. As the CISO at HGS, Phani plays a pivotal role in safeguarding the organization’s global information assets. His leadership encompasses a wide range of security operations focused on strengthening data security, ensuring compliance with regulatory requirements, fostering a security-conscious culture, and developing and executing incident response and recovery strategies to minimize disruptions to the business.
To learn more about HGS, please visit hgs.cx
