# The GANfather: Using Malicious GenAI Agents to Combat Money Laundering

DevFeed: [The GANfather: Using Malicious GenAI Agents to Combat Money Laundering](<https://devfeed.tech/articles/the-ganfather-using-malicious-genai-agents-to-combat-money-laundering-26300.md>)

Original publisher: [Read original article](<https://medium.com/feedzaitech/the-ganfather-using-malicious-genai-agents-to-combat-money-laundering-1666908113fc?source=rss----e11168e7fe6b---4>)

Author: Ricardo Ribeiro Pereira

Published: 2024-10-04T13:49:42Z

Content type: article

Language: en

Sources: [Feedzai](<https://devfeed.tech/sources/feedzai.md>)

Topics: [Generative AI](<https://devfeed.tech/topics/generative-ai.md>), [synthetic-data](<https://devfeed.tech/topics/synthetic-data.md>), [Machine learning](<https://devfeed.tech/topics/machine-learning.md>), [AI Development](<https://devfeed.tech/topics/ai-development.md>), [data](<https://devfeed.tech/topics/data.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [banking](<https://devfeed.tech/tags/banking.md>), [data](<https://devfeed.tech/tags/data.md>), [feedzai](<https://devfeed.tech/tags/feedzai.md>), [financial-sector](<https://devfeed.tech/tags/financial-sector.md>), [gans](<https://devfeed.tech/tags/gans.md>), [genai](<https://devfeed.tech/tags/genai.md>), [generative](<https://devfeed.tech/tags/generative.md>), [generative-ai](<https://devfeed.tech/tags/generative-ai.md>), [legacy](<https://devfeed.tech/tags/legacy.md>), [machine-learning](<https://devfeed.tech/tags/machine-learning.md>), [money-laundering](<https://devfeed.tech/tags/money-laundering.md>), [research](<https://devfeed.tech/tags/research.md>), [synthetic](<https://devfeed.tech/tags/synthetic.md>), [synthetic-data](<https://devfeed.tech/tags/synthetic-data.md>), [transactions](<https://devfeed.tech/tags/transactions.md>)

## AI overview

Feedzai describes a method that uses Generative AI to create synthetic data simulating realistic money-laundering activity. The generated examples are intended to support machine-learning approaches to detection and help identify vulnerabilities in banks' defenses, addressing the limited availability of labeled data.

## Source excerpt

Digital systems have become deeply integrated into many aspects of modern life, particularly within the financial sector. While digital banking simplifies day-to-day operations for clients, it also creates new opportunities for malicious actors to exploit these systems. As a result, money laundering has grown particularly prevalent due to this digital expansion. Banks are required to monitor for money laundering activities and issue alerts when suspicious transactions are detected. Typically, monitoring is performed by rules-based legacy systems. A better approach would be to use Machine Learning models, but these usually require labeled data to train, which are mostly unavailable in this use case. To tackle this problem, we employ advanced Generative AI (GenAI) techniques to generate synthetic data that simulates realistic money laundering activities. These synthetic examples help us identify vulnerabilities and strengthen the defense mechanisms used by banks and other financial institutions In this blog post, we will explore the method developed by Feedzai, which leverages GenAI to tackle the challenges of detecting and preventing money laundering in today's digital landscape. This blog post is the first of a series dedicated to the work done on GenAI by Feedzai Research in the last few years. Problem Statement First, let's briefly introduce the concepts behind money laundering and the difficulties that banks face when trying to prevent it. Money laundering is the process of concealing the origins of illegally obtained funds. Criminals cannot directly spend "dirty" money without risking exposure of their illegal activities. Therefore, they want to disguise the origins of funds before using them. Money laundering typically involves three stages: Placement: the money is introduced into the financial system, often in small amounts spread across various banks. Layering: the money launderer moves the funds through a series of transactions, typically across multiple fin