Towards Artificial Intelligence Enabled Financial Crime Detection

TL;DR

This paper explores the integration of AI technologies into financial crime detection, focusing on developing a novel model for money laundering detection with minimal human intervention to enhance efficiency and accuracy.

Contribution

It introduces a new AI-enabled model specifically designed for money laundering detection, advancing the capabilities of financial crime detection systems.

Findings

Proposed a novel AI-based model for money laundering detection

Achieved high accuracy with minimal human intervention

Analyzed recent advancements in financial crime detection methods

Abstract

Recently, financial institutes have been dealing with an increase in financial crimes. In this context, financial services firms started to improve their vigilance and use new technologies and approaches to identify and predict financial fraud and crime possibilities. This task is challenging as institutions need to upgrade their data and analytics capabilities to enable new technologies such as Artificial Intelligence (AI) to predict and detect financial crimes. In this paper, we put a step towards AI-enabled financial crime detection in general and money laundering detection in particular to address this challenge. We study and analyse the recent works done in financial crime detection and present a novel model to detect money laundering cases with minimum human intervention needs.