How to catch a money launderer with data analysis?
The increasing use of digital technology in the business world is making it easier for money launderers to perform criminal activities. In this talk we will explain which technical challenges FIOD (the Dutch Anti-Fraud agency) is facing and how we build software which helps addressing these challenges. In a demo we show how we use cool technologies like Kubernetes, Kafka and Neo4j for the identification of the hidden relationships between entities based on data from multiple sources such as transaction data, geographic data and personal data.
Mireille is a Software engineer at OpenValue. From a young age she knew she wanted to build things. Currently she is building a microservices architecture that is used for the investigation of money laundering. Passionate about Artificial Intelligence, Scala and Software Architecture.