Insight

Third-party risk management: The road to AI

The business case for artificial intelligence (AI) to be used in third party risk management (TPRM) programs

Tarun Sondhi

Tarun Sondhi

Principal, Advisory, KPMG US

+1 703-286-8239

Greg Matthews

Greg Matthews

Partner, FS Regulatory & Compliance Risk , KPMG U.S.

+1 212-954-7784

Jonathan Dambrot

Jonathan Dambrot

Principal, Cyber Security Services, KPMG U.S.

+1 908-361-6438

Jilane Khakhar

Jilane Khakhar

Director, Advisory-Forensic, KPMG US

+1 212-954-1181

Anu Sandhu

Anu Sandhu

Specialist Director, Solution Management, KPMG US

+1 646-344-3052

Maribeth Timony

Maribeth Timony

Director, Solution Relations, KPMG US

+1 781-771-1765

Using AI to get consistent and effective TPRM

Businesses often rely on third parties to compete in a global marketplace, which can lead to challenges with risk monitoring. Current infrastructure constraints can also keep them from the continuous oversight required for effective TPRM in fast-changing conditions.

AI algorithms can help organizations access data and analyze results in real time. The question isn’t “whether” to incorporate AI into an arsenal of TPRM tools, but rather “how, specifically?” or “where first?”. Read this paper to learn:

  • 4 big operational considerations
  • 7 common concerns for integrating AI functionality into TPRM models
  • 8 questions to ask external TPRM AI providers
Third party risk management: The road to AI
What combinations of AI tools for TPRM, organizational capital, and risk strategy might best bridge the gap between vision and reality?
The application of AI to TPRM is never just a pure technology play. It can only improve and sustain programs that have solid processes and qualified people behind them.
Jilane Khakhar, Director, KPMG Forensic Services