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
Parents
12
GOTCHA! Network-Based Fraud Detection for Social Security Fraud
Véronique Van Vlasselaer, Tina Eliassi‐Rad, Leman Akoglu et al. · Management Science · 2016 · 168 citations
A framework for data mining‐based anti‐money laundering research
Zengan Gao, Mao Ye · Journal of Money Laundering Control · 2007 · 97 citations
Business, Data Science, Crime +14
Applying data mining in investigating money laundering crimes
Zhongfei Zhang, John Salerno, Philip S. Yu · 2003 · 94 citations
Business, Criminology, Data Science +13
Rebecca S. Portnoff, Danny Yuxing Huang, Periwinkle Doerfler et al. · 2017 · 63 citations
1–5 of 12
35
3
h-index
2
h-index
2
h-index
2
h-index
2
h-index
1–5 of 35
23
KU Leuven
Leuven, Belgium
2 h-index
8 publications
903 citations
Binghamton University
Binghamton, United States
2 h-index
2 publications
112 citations
IBM (United States)
Armonk, United States
2 h-index
2 publications
112 citations
Stony Brook University
Stony Brook, United States
2 h-index
6 publications
861 citations
Rutgers, The State University of New Jersey
New Brunswick, United States
2 h-index
5 publications
693 citations
University of Southampton
Southampton, United Kingdom
1 h-index
5 publications
840 citations
Universidade de Brasília
Brasília, Brazil
1 h-index
2 publications
24 citations
Northeastern University
Boston, United States
1 h-index
1 publications
168 citations
1–8 of 23
1 publications · 168 citations
1
h-index
AIL · 1 publications · 47 citations
1
h-index
1 publications · 44 citations
1
h-index
1 publications · 97 citations
1
h-index
CET · 1 publications · 18 citations
1
h-index
1–5