Severity Regression Models

Severity Regression Models is a statistical modeling framework within claims modeling that specifically quantifies the expected magnitude of insurance claims by regressing claim severity on predictor variables, distinguishing it from frequency models by focusing on the economic impact of individual claims rather than their occurrence count.

13

Publications

743

Citations

37

Authors

19

Institutions

Publications per year

2017–2026

5

Authors

37

  1. EW
    Edward W. Frees

    University of Wisconsin–Madison, United States

    2 publications · 156 citations

    2

    h-index

  2. JT
    Ju Taek Oh

    Korea Transport Institute, South Korea

    1 publications · 30 citations

    1

    h-index

  3. XS
    X. Sheldon Lin

    University of Toronto, Canada

    1 publications · 22 citations

    1

    h-index

  4. LX
    Lichen Xu

    Zhejiang University, China

    1 publications · 38 citations

    1

    h-index

  5. YK
    Young‐Jun Kweon

    Virginia Transportation Research Council, United States

    1 publications · 212 citations

    1

    h-index

1–5 of 37

Venues

  1. Risks

    2 publications · 151 citations

    2

    h-index

  2. North American Actuarial Journal

    NAAJ · 2 publications · 37 citations

    2

    h-index

  3. Astin Bulletin

    2 publications · 28 citations

    2

    h-index

  4. Transportation research procedia

    TRPRO · 1 publications · 62 citations

    1

    h-index

  5. Health Services Research

    HSR · 1 publications · 25 citations

    1

    h-index

1–5