Concepedia

Fraud Risk Segmentation

Fraud Risk Segmentation is a risk classification framework that categorizes entities or transactions according to their likelihood of involvement in fraudulent activities, distinguished by its specific focus on identifying and prioritizing fraud-related risks within a broader risk management context.

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Publications

26

Citations

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Authors

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Institutions

Publications per year

2017–2026

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Parents

Publications

1

1–3 of 1

Authors

1

  1. CO
    Cyril Onwubiko

    Global Security Intelligence (United Kingdom), United Kingdom

    1 publications · 26 citations

    1

    h-index

  2. KC
    Kenneth C. Cox

    Washington University in St. Louis, United States

    1 publications · 123 citations

    0

    h-index

  3. RJ
    Ronald J. Brachman

    AT&T (United States), United States

    1 publications · 123 citations

    0

    h-index

  4. SG
    Stephen G. Eick

    AT&T (United States), United States

    1 publications · 123 citations

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    h-index

  5. GW
    Graham Wills

    University of Wisconsin–Madison, United States

    1 publications · 123 citations

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    h-index

1–5 of 1

Institutions

0

  1. AT&T (United States)

    Bedminster, United States

    1 publications

    123 citations

  2. Alcatel Lucent (Germany)

    Stuttgart, Germany

    1 publications

    123 citations

  3. Amirkabir University of Technology

    Tehran, Iran

    1 publications

    31 citations

1–3 of 0

Venues

  1. Computers & Security

    1 publications · 26 citations

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    h-index

  2. Data Mining and Knowledge Discovery

    1 publications · 123 citations

  3. Expert Systems with Applications

    1 publications · 31 citations

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