  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.
