Rising Third-Party Risk: Public Data Combined with Advanced AI is the Answer
In the last 12 months, 87% of F1000 companies suffered a third-party breach, with financial implications of up to $1B for a single incident. Organization’s need to advance their third-party risk management practices to remain compliant and avoid reputational and financial damage. A modern, effective approach is essential.
Network with your peers and join Brian Gumbel (President & COO, Dataminr), Dave DeWalt (CEO, NightDragon), & Clark Smith (Global Head of Engineering & Architecture, Citi) for a discussion on how AI models, combined with public data, can help organizations advance their third-party risk identification and continuous monitoring.
Using real-world examples we’ll cover best practices to:
- Up-level third-party risk strategies by ingesting and using public data
- Incorporate advanced AI models to optimize and automate how large volumes of public data are processed to identify external threats
- Combat and mitigate growing third-party threats with AI and public data