ITECH5500: Predictive Model Utilising Big Data Analytics Report

This report delves into the application of predictive models and big data analytics for identifying and mitigating fraud, particularly in the context of credit cards and online banking. The research explores the growing challenges posed by fraudulent activities and investigates the effectiveness of predictive models, including data mining and big data techniques, in addressing these issues. The study reviews existing literature, highlighting the importance of predictive analytics in forecasting trends and behaviors, while also examining the role of big data in analyzing collected data to detect fraud. The research aims to evaluate the significance of big data technology in predictive analytics and proposes a framework for fraud detection, ultimately contributing to the development of more effective strategies for preventing financial fraud. The report emphasizes the need for advanced analytical frameworks, such as those utilizing Hadoop, to efficiently process and analyze large datasets, ultimately improving the accuracy and reliability of fraud detection systems.