Relational Graph Neural Networks for Fraud Detection in a Super-App environment

07/29/2021
by   Jaime D. Acevedo-Viloria, et al.
2

Large digital platforms create environments where different types of user interactions are captured, these relationships offer a novel source of information for fraud detection problems. In this paper we propose a framework of relational graph convolutional networks methods for fraudulent behaviour prevention in the financial services of a Super-App. To this end, we apply the framework on different heterogeneous graphs of users, devices, and credit cards; and finally use an interpretability algorithm for graph neural networks to determine the most important relations to the classification task of the users. Our results show that there is an added value when considering models that take advantage of the alternative data of the Super-App and the interactions found in their high connectivity, further proofing how they can leverage that into better decisions and fraud detection strategies.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
02/19/2021

Supporting Financial Inclusion with Graph Machine Learning and Super-App Alternative Data

The presence of Super-Apps have changed the way we think about the inter...
research
11/05/2021

Feature-Level Fusion of Super-App and Telecommunication Alternative Data Sources for Credit Card Fraud Detection

Identity theft is a major problem for credit lenders when there's not en...
research
05/15/2019

GMNN: Graph Markov Neural Networks

This paper studies semi-supervised object classification in relational d...
research
04/12/2021

Enhancing User' s Income Estimation with Super-App Alternative Data

This paper presents the advantages of alternative data from Super-Apps t...
research
03/06/2019

Relational Pooling for Graph Representations

This work generalizes graph neural networks (GNNs) beyond those based on...
research
11/22/2022

Predicting Biomedical Interactions with Probabilistic Model Selection for Graph Neural Networks

A biological system is a complex network of heterogeneous molecular enti...
research
09/06/2022

Being Automated or Not? Risk Identification of Occupations with Graph Neural Networks

The rapid advances in automation technologies, such as artificial intell...

Please sign up or login with your details

Forgot password? Click here to reset