Risk scoring large volume of documents with AI 🇬🇧 🇪🇸 🇧🇷

Third Party Risk Management (TPRM) is a crucial function for any organization that depends on external resources to support or carry out business operations. Traditional TPRM involves collecting security artifacts, reviewing documentation to ensure expected controls are in place, and making recommendations to business stakeholders. This process is often manual and labor-intensive, taking weeks to complete. The introduction of AI has the potential to revolutionize TPRM by automating many of these tasks, significantly reducing the time and effort required.

In this talk, we will explore how AI can automate various aspects of TPRM. AI can efficiently handle document analysis, swiftly parsing through vast amounts of data to identify relevant information and highlight potential risks. AI can assess the completeness and accuracy of documentation against predefined control frameworks, eliminating the need for manual checks.

AI can automate the scoring of third-party risks. Instead of manually evaluating each vendor against a set of criteria, AI can rapidly analyze data and provide a risk score based on historical data and predictive modeling. This ensures a consistent and objective assessment of third-party risks.

AI can handle basic mathematical tasks such as calculating risk metrics and aggregating data to provide a comprehensive risk profile. This not only speeds up the process but also reduces the likelihood of human error.