/ETH-AML

Primary LanguageJupyter NotebookMIT LicenseMIT

Blockchain Anti-Money Laundering Auditing Tool for Digital Assets

Overview

In the wake of rapid technological advancements, digital assets have emerged as a pivotal force, reshaping the financial landscape and gaining unprecedented traction. As these assets permeate the banking sector, they give clients a new way to connect their digital wealth with regular banking infrastructure. However, this fusion brings forth dozens of regulatory challenges, especially concerning compliance and anti-money laundering measures. Addressing these complexities, this work introduces an innovative automated auditing tool designed to streamline and enhance the onboarding process for digital assets. Developed in collaboration with a renowned Swiss bank, our proposed proof-of-concept offers an efficient and comprehensive analysis of clients’ digital assets, ensuring they align with regulatory standards. By bridging the divide between the digital and traditional banking realms, our solution presents a forward-looking approach to modern banking, reinforcing both its efficiency and integrity in the face of evolving digital asset trends.

Features

  • Modular Design: Includes various analysis modules such as Associated Wallets, Blacklist Check, Exchange Analysis, Proof of Funds, NFT Analysis, ERC20 Tokens, Smart Contract, and Mixers & Bridges.
  • Comprehensive Analysis: Automates the onboarding checks, reducing manual labor and improving accuracy.
  • Flexibility: Customizable modules to fit specific audit requirements.
  • API Integration: Utilizes APIs from GraphSense, Etherscan, Binance, and Coinbase for data retrieval and analysis.

Getting Started

Prerequisites

  • Python 3.8+
  • Jupyter Notebook
  • Access to the specified APIs

Installation

  1. Clone the repository: Based on the contents of your bachelor's thesis, here's a short README template for your GitHub project:

markdown

Automated Digital Asset Audit Tool

Overview

This project introduces an automated tool for auditing digital assets, designed to streamline the onboarding process for banks by addressing regulatory challenges in compliance and anti-money laundering measures. Developed in collaboration with a renowned Swiss bank, this proof-of-concept (PoC) provides an efficient and comprehensive analysis of clients' digital assets to ensure regulatory compliance.

Features

  • Modular Design: Includes various analysis modules such as Associated Wallets, Blacklist Check, Exchange Analysis, Proof of Funds, NFT Analysis, ERC20 Tokens, Smart Contract, and Mixers & Bridges.
  • Comprehensive Analysis: Automates the onboarding checks, reducing manual labor and improving accuracy.
  • Flexibility: Customizable modules to fit specific audit requirements.
  • API Integration: Utilizes APIs from GraphSense, Etherscan, Binance, and Coinbase for data retrieval and analysis.

Getting Started

Prerequisites

  • Python 3.8+
  • Jupyter Notebook
  • Access to the specified APIs

Installation

  1. Clone the repository:

git clone https://github.com/dragmakex/ETH-AML.git

Usage

  1. Open the Jupyter Notebook to access the modular analysis tools.
  2. Customize and run the modules as needed to perform digital asset audits.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

  • Special thanks to the supervisors and collaborators at ETH Zürich and UZH Blockchain Center for their guidance and support.
  • Appreciation to the involved Swiss bank for the collaboration opportunity.
  • Very thankful to GraphSense/Iknaio for their assistance and for providing access to their platform, which was instrumental in developing this project.