Log in / My SOA

AI-Based Synthetic Medical Claims Data Generation: A Practical Guide for Actuaries

Published May 29, 2026

Author(s)

Shea Parkes, FSA, MAAA; Zihua She; Jianxi Su, PhD, FSA; Xiao Wang, PhD

Overview

This report presents a practical framework for actuaries to leverage generative Artificial Intelligence techniques to create realistic, privacy-preserving medical claims data. The report proposes a chain-type generative framework for mirroring the hierarchical structure of healthcare data.

Key Findings

This report demonstrates an actuarial application of AI methods for modeling and generating synthetic medical claim data. A flexible, chain-based framework is proposed, which enables the identification and customization of generative models tailored to diverse data types.

Synthetic data generation techniques offer a transformative path for overcoming long-standing challenges related to privacy and data access. This report represents a meaningful step toward responsible data sharing, accelerating methodological advances, and fostering impactful applications in underwriting, health policy design, and beyond.

FAQ

Question: What does this research demonstrate about using AI methods?

Answer:
The Society of Actuaries Research Institute’s Actuarial Innovation and Technology Committee developed this report to demonstrate an actuarial application of AI methods for modeling and generating synthetic medical claim data.

Suggested Citation

Shea Parkes, FSA, MAAA; Zihua She; Jianxi Su, PhD, FSA; Xiao Wang, PhD; AI-Based Synthetic Medical Claims Data Generation: A Practical Guide for Actuaries, Society of Actuaries Research Institute, 2026.

Materials

AI-Based Synthetic Medical Claims Data Generation: A Practical Guide for Actuaries

Project Source Code

Acknowledgements

The SOA would like to thank the members of the Synthetic Medical Claims Project Oversight Group for their support, guidance, direction, and feedback throughout the project:

  • Priya Dwarakanath, FSA, FIA, MAAA
  • Greg Fann, FSA, MAAA
  • Ka Wah Michael Fung, FSA, CERA
  • Xinyi Hu, ASA, MAAA
  • Sarah Lopez
  • Shisheng Qian, FSA, CERA
  • Norm Storwick, FSA, MAAA

At the Society of Actuaries Research Institute:

  • Joe Alaimo, ASA, ACIA
  • Korrel Crawford, Sr. Research Administrator

Questions or Comments?

Give us your feedback! Take a short survey on this report. Take Survey

If you have comments or questions, please send an email to Research-AIT@soa.org