14 citations · 40 across the 14 of their papers we have counts for
9 papers · 1 filter
GARG-AML against Smurfing: A Scalable and Interpretable Graph-Based Framework for Anti-Money Laundering
Bruno Deprez, Bart Baesens, Tim Verdonck +1
Purpose: We introduce GARG-AML, a fast and transparent graph-based method to catch `smurfing', a common money-laundering tactic. It assigns a single, easy-to-understand risk score…
Network Analytics for Anti-Money Laundering -- A Systematic Literature Review and Experimental Evaluation
Bruno Deprez, Toon Vanderschueren, Bart Baesens +2
Money laundering presents a pervasive challenge, burdening society by financing illegal activities. The use of network information is increasingly being explored to effectively com…
INFLECT-DGNN: Influencer Prediction with Dynamic Graph Neural Networks
Elena Tiukhova, Emiliano Penaloza, María Óskarsdóttir +3
Leveraging network information for predictive modeling has become widespread in many domains. Within the realm of referral and targeted marketing, influencer detection stands out a…
Influencer Detection with Dynamic Graph Neural Networks
Elena Tiukhova, Emiliano Penaloza, María Óskarsdóttir +5
Leveraging network information for prediction tasks has become a common practice in many domains. Being an important part of targeted marketing, influencer detection can potentiall…
Social network analytics for supervised fraud detection in insurance
María Óskarsdóttir, Waqas Ahmed, Katrien Antonio +4
Insurance fraud occurs when policyholders file claims that are exaggerated or based on intentional damages. This contribution develops a fraud detection strategy by extracting insi…
The Value of Big Data for Credit Scoring: Enhancing Financial Inclusion using Mobile Phone Data and Social Network Analytics
María Óskarsdóttir, Cristián Bravo, Carlos Sarraute +2
Credit scoring is without a doubt one of the oldest applications of analytics. In recent years, a multitude of sophisticated classification techniques have been developed to improv…