Machine Learning Underwriting

Machine Learning Underwriting is a computational underwriting framework that employs machine learning algorithms to automate and refine risk assessment in property insurance by identifying complex, non-linear patterns in heterogeneous data sources, thereby distinguishing it from traditional rule-based or statistical underwriting models.

16

Publications

407

Citations

27

Authors

27

Institutions

Publications per year

2017–2026

12

Authors

27

  1. MJ
    Mark Jansen

    University of Utah, United States

    2 publications · 49 citations

    2

    h-index

  2. AS
    Amin Shams

    Fisher College, United States

    2 publications · 49 citations

    2

    h-index

  3. HN
    Hieu Nguyen

    Foreign Trade University, Vietnam

    2 publications · 49 citations

    2

    h-index

  4. SK
    Sushant K. Singh

    Duy Tan University, Vietnam

    1 publications · 12 citations

    1

    h-index

  5. TJ
    Tiffany Jiang

    Stanford University, United States

    1 publications · 13 citations

    1

    h-index

1–5 of 27

Venues

  1. SSRN Electronic Journal

    Repository · 2 publications · 33 citations

    2

    h-index

  2. Management Science

    1 publications · 38 citations

    1

    h-index

  3. Journal of Banking & Finance

    1 publications · 19 citations

    1

    h-index

  4. Journal of risk and financial management

    JRFM · 1 publications · 38 citations

    1

    h-index

  5. Procedia Computer Science

    1 publications · 19 citations

    1

    h-index

1–5