Financial Crime World

Combatting Financial Crimes with Machine Learning: A Collaboration between ING Bank and Academia

The Netherlands Antilles, a region known for its high-risk environment for financial crimes, is working to combat the threat of money laundering. Researchers at ING bank are joining forces with academics to develop innovative machine learning models that can detect and prevent financial crimes.

A Complex Challenge

Detecting financial crimes presents a multifaceted challenge from an AI perspective:

  • Imbalanced Datasets: The dataset used in this project is extremely imbalanced, making traditional supervised machine learning approaches unsuitable.
  • Financial Network Complexity: The sparsity of financial networks complicates the AML task, as criminal groups often use intricate patterns to transfer money between different financial entities.

Providing Transparency

Regulators require banks to provide explanations for every reported client. This means that the AML model must not only assess the probability of a client engaging in money laundering activities but also provide supporting evidence for its decision.

ING’s Partnership with Academia

ING is committed to incorporating machine learning technology into its systems to automate the detection of money laundering. As part of this initiative, the bank will:

  • Provide access to its data and analytics platform
  • Enable researchers to develop effective models that can be integrated into ING’s existing systems

Collaboration for a Robust AML System

The collaboration between ING and academics aims to create a robust and transparent AML system that can effectively detect financial crimes in the Netherlands Antilles. This project has the potential to make a significant impact on national security and contribute to the global fight against money laundering.

  • Key Benefits:
    • Improved detection of financial crimes
    • Enhanced transparency for regulators and clients
    • Increased efficiency in AML processes
  • Potential Impact: The success of this project could set a new standard for AML systems globally, making it an important step towards combating financial crimes worldwide.