Embracing AI: Revolutionizing Third-Party Risk Management in the Modern Business World

Businesses are continually striving to enhance operational efficiency, remain competitive, and manage overheads. To accomplish this, many have opted for increased engagement with third-party entities such as suppliers, vendors, and consultants. The underlying goal is to allocate more valuable tasks to in-house teams, share risk, improve cost-efficiency, and ultimately gain a competitive advantage.

Nonetheless, this increasing reliance on external parties is accompanied by its unique set of challenges. With new privacy regulations compelling businesses to identify and control any risks arising from third-party engagements, the traditional, contractual security measures are proving inadequate.

To illustrate the hurdles facing businesses in their third-party risk management efforts, let’s consider the outcomes of recent interactive sessions we held, which involved diverse representatives from various industries and business sizes. They revealed several shared struggles:

  • Process Inefficiency: Existing third-party security measures are predominantly manual, complex, and time-intensive. Vendor communication often requires repeated follow-ups, causing delay in service and product procurement and subsequently affecting consumer experiences. Additionally, inconsistent vendor assessment questionnaires further complicate the process, often leading to vendor dissatisfaction due to irrelevant queries.
  • Operational Silos: Third-party security and procurement are intricately connected yet often work in isolation due to different reporting lines. The absence of collaboration between these teams can lead to the overlooking of crucial security provisions in vendor contracts, creating enforcement challenges. Multiple vendor entries across the organization also burden the security team and potentially result in confusion.
  • Inconsistent Assessments: With the increasing number of vendors and new regulatory mandates requiring reassessments, maintaining consistency across vendor evaluations is becoming challenging for organizations. As documentation increases, it is difficult to scrutinize all vendors effectively and equally.

The Promise of AI in Third-Party Risk Management

As organizations strive to manage the cybersecurity risks posed by third-party interactions, they already possess several solutions and a wealth of data. What’s missing, however, is a mechanism to consolidate these disparate data sources and automate mundane tasks. Enter Artificial Intelligence (AI) – the technology that promises to revolutionize third-party risk management.

On a foundational level, an AI digital worker could serve as the first point of contact for the third-party security process. It could address basic inquiries from internal teams and streamline the onboarding process of new vendors. With sophisticated AI functionalities and Natural Language Understanding (NLU), this digital worker could simplify the vendor validation process by eliciting task-specific information from users.

The digital worker would then route this entry to the third-party security team for comprehensive scrutiny. Furthermore, it could handle contractual queries and tackle issues discovered during the vendor assessment phase.

The AI digital worker’s role could extend to manage direct vendor communications. Advanced digital workers are now capable enough to ask tailored follow-up questions based on the vendor’s services, previous issues, and experiences with similar vendors. This leads to a highly personalized questionnaire that aligns with the unique vendor relationship.

Building a Business Case for AI in Third-Party Risk Management

Investing in AI for third-party risk management should address both qualitative and quantitative aspects. Given the vast number of third-party entities and the associated data, managing risks effectively has become a daunting task for even the most established risk management programs.

Introducing an AI digital worker not only increases efficiency but also provides immense value in processing large datasets, generating actionable insights, and shifting focus from repetitive tasks to key risk areas. A compelling business case for AI would emphasize the ROI, highlighting the anticipated benefits from streamlined workflows, automated efficiencies, reduced overheads, and a simplified approach to long-term third-party relationship management.

In essence, deploying AI digital workers in third-party risk management can lead to reduced operational costs, enhanced risk mitigation, and decreased overhead expenditure. Furthermore, the saved resources can be diverted to further develop the organization’s third-party security program.

In upcoming posts, we will delve into the specific advantages of AI in third-party risk management. We aim to provide organizations with the necessary insights and data to build a robust business case for integrating AI digital workers into their third-party risk management landscape.

Third-Party Risk Management is difficult if the right software isn’t in place to manage your organization’s data. Learn more about Third-Party Risk Management on Connected Risk™ here, or by filling out the form below to learn more about it from one of our qualified solutions experts.

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