Revolutionizing Third Party Risk Management Using Generative AI and RAG
Shrey Arora, Vidyavati Ramteke · 2024
This integration of Generative AI and Retrieval Augmented Generation (RAG) will open new frontiers in Third Party Risk Management (TPRM) by making the creation of both risk assessments and compliance checks more accurate, efficient, and scalable. Quite naturally, TPRM is one area wherein organizations must engage in processes to make sure risks emanating from vendors and partners are duly mitigated. Traditionally, the TPRM process has been manual and time-consuming. With the functionality of Generative AI, autonomy in creating relevant content and automation in compliance significantly reduce the labor of these processes. With RAG integrated, the model improves the quality of AI responses through real-time grounding in authoritative data sources, reducing the risk of providing outdated or incorrect information. This dual approach will make sure organizations manage a growing number of third-party relationships with greater precision and timeliness. Indeed, the proposed AI-driven framework will minimize human error and reduce operational costs, besides being scalable to adapt to dynamic regulatory changes-thus offering a competitive advantage in third-party risk management.