Fraud Link Analysis

Fraud Link Analysis is a computational method that identifies suspicious relationships and hidden networks in financial transaction data by analyzing associative patterns among entities to detect potential money laundering activities.

12

Publications

651

Citations

35

Authors

23

Institutions

Publications per year

2017–2026

4

Authors

35

  1. PS
    Philip S. Yu

    University of Illinois Chicago, United States

    3 publications · 141 citations

    3

    h-index

  2. LA
    Leman Akoglu

    Carnegie Mellon University, United States

    2 publications · 189 citations

    2

    h-index

  3. TE
    Tina Eliassi‐Rad

    Lawrence Livermore National Laboratory, United States

    2 publications · 189 citations

    2

    h-index

  4. VV
    Véronique Van Vlasselaer

    KU Leuven, Belgium

    2 publications · 189 citations

    2

    h-index

  5. ZZ
    Zhongfei Zhang

    Binghamton University, United States

    2 publications · 112 citations

    2

    h-index

1–5 of 35

Venues

  1. Management Science

    1 publications · 168 citations

    1

    h-index

  2. Artificial Intelligence and Law

    AIL · 1 publications · 47 citations

    1

    h-index

  3. Computers & Industrial Engineering

    1 publications · 44 citations

    1

    h-index

  4. Journal of Money Laundering Control

    1 publications · 97 citations

    1

    h-index

  5. Chemical engineering transactions

    CET · 1 publications · 18 citations

    1

    h-index

1–5