“Fraud Detection in Financial Transactions Using Pyspark on Databricks”

Abstract - In the era of digital finance, detecting fraudulent transactions is a major concern for financial institutions. Fraudulent activity not only results in monetary losses but also erodes customer trust. This project proposes a scalable and efficient system for fraud detection in financial transactions using PySpark on the Databricks platform. The core idea is to leverage the power of distributed data processing with PySpark to train machine learning model capable of identifying potential fraud. Key Words: Fraud Detection, Pyspark, DataBricks, Random Forest Classifier