Streaming Network Analysis and Claim Velocity Scoring: Real-Time AI Frameworks for Insurance Fraud Detection and Prevention

Authors

  • Fei-Fei Li Professor of Computer Science, Stanford University

Keywords:

streaming network analysis, claim velocity scoring, real-time ai frameworks, insurance fraud detection, machine learning

Abstract

The insurance industry is plagued with an onslaught of fraudulent claims. In 2020 alone, U.S. insurance carriers collectively lost 7% to 10% of earned premiums due to fraud, costing an estimated $80 billion. As a result, one of the biggest priorities for many carriers is innovating their fraud detection and prevention methods. Instead of waiting for the claim to be paid and then seeking restitution, insurance carriers would greatly prefer to preemptively stop the payment from going out.

Downloads

Published

31-12-2025

How to Cite

[1]
“Streaming Network Analysis and Claim Velocity Scoring: Real-Time AI Frameworks for Insurance Fraud Detection and Prevention”, J. Computational Intel. & Robotics, vol. 5, no. 2, pp. 44–51, Dec. 2025, Accessed: Jun. 04, 2026. [Online]. Available: https://thesciencebrigade.com/jcir/article/view/730