AI-Driven Risk Control for Health Insurance Fund Management: A Data-Driven Approach

EasyChair Preprint 13719, version history

VersionDatePagesVersion notes
1
July 1, 2024
12
2
August 6, 2024
15

In the revised version, we addressed the reviewers' comments by clarifying data normalization, providing details on data dimensions and sample sizes, and including illustrative examples. The abstract has been restructured for clarity, and the introduction now presents relevant statistics on health insurance fraud, outlines the research gap, and specifies study objectives. We updated the literature review with recent publications and a critical analysis of existing methods. Additionally, we enhanced the methodology section with explanations for algorithm choices and ethical considerations. The results now include comparative performance metrics, a detailed analysis of false positives and negatives, and sensitivity analyses. Finally, the conclusion explicitly states how research objectives were met and offers directions for future work.

Keyphrases: AI, Health Insurance, feature engineering, machine learning, model optimization, risk control

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@booklet{EasyChair:13719,
  author    = {Pengfei Lin and Yixin Cai and Huasen Wu and Jinghe Yin and Zhaxi Luorang},
  title     = {AI-Driven Risk Control for Health Insurance Fund Management: A Data-Driven Approach},
  howpublished = {EasyChair Preprint 13719},
  year      = {EasyChair, 2024}}