Exploring the Use of Artificial Intelligence for Vendor Risk Management – de la Vega and Fonseca
Abstract:
In today’s rapidly evolving digital landscape, the need for more effective vendor risk management (VRM) methods to address complex cybersecurity threats is critical and urgent. The increasing reliance on third-party services in the finance industry has significantly heightened cybersecurity risks, exposing vulnerabilities and attack vectors that have become more pronounced with integrating external applications and service providers As supported by numerous studies, the inefficiency in monitoring and mitigating risks is a pressing concern. The proliferation of advanced technologies has opened new avenues for attacks and increased the interconnectivity of digital devices, including IoT, cloud computing, and mobile tech, thereby expanding the scope of potential vulnerabilities. This urgency demands more cohesive and complex traditional risk management processes. The finance industry’s increasing reliance on third-party providers to enhance operational efficiency, digitization, and customer convenience has the potential to transform the industry significantly. A large-scale study found that a significant percentage of popular financial websites depend heavily on third-party services such as Domain Name Service (DNS), Content Delivery Network (CDN), and Controlling Authority (CA) providers, with dependency rates ranging between 15% and 80%, depending on the service and region. This growing dependency underscores the critical need for updated legal frameworks to manage the associated risks, including civil and criminal liabilities and financial risks. These regulatory changes are crucial to ensure the industry’s resilience in the face of evolving cyber threats.
PMI Talent Triangle: Ways of Working
PDUs: 0.75
