Financial-Security-Fraud-Detection-Analysis-and-Anti-Money-Laundering-Model

NYU Tandon, CSGY-6513-D: Big Data, End Semester Project

Project:

The project is a novel attempt to strengthen financial security measures by combining machine learning techniques with Big Data technologies. This project focuses on performing complex pattern analysis and building an AML system that can accurately distinguish fraudulent financial transactions from legitimate ones in response to the growing challenges presented by sophisticated money laundering tactics.

Dataset:

IBM Transactions for Anti Money Laundering (AML)
https://www.kaggle.com/datasets/ealtman2019/ibm-transactions-for-anti-money-laundering-aml/

How to Run the Notebook:

• Check if the dataset is in the same directory as the notebook and run respective notebooks.

Results:

• Performed complex pattern analysis and temporal analysis.
• Implemented Logistic Regression and gradient-boosted tree models.

Future Work:

• Implement better feature engineering techniques.
• Explore better models and run hyperparameter sweeps.