Big Data Analytics plays a crucial role in detecting and preventing financial fraud. Financial institutions face increasing threats from sophisticated fraud schemes, necessitating innovative detection methods. Big Data Analytics enables the analysis of vast datasets, including transaction and user behavior data, to identify anomalies and assess risks. Real-time processing is essential for swift fraud identification. Challenges include data quality, privacy, and the need for scalable infrastructure. Case studies show successful implementations, such as PayPal and HSBC, which use machine learning and real-time analytics to detect fraud. Emerging technologies like blockchain and AI are expected to enhance fraud prevention strategies. The paper emphasizes the importance of ethical use of data, transparency, and collaboration in the financial industry. Future trends include the integration of deep learning, blockchain, and edge computing to improve fraud detection. Security and ethical considerations are vital to ensure the responsible use of Big Data Analytics in financial fraud detection. The review concludes that Big Data Analytics is transformative in enhancing fraud prevention and strengthening the financial ecosystem.Big Data Analytics plays a crucial role in detecting and preventing financial fraud. Financial institutions face increasing threats from sophisticated fraud schemes, necessitating innovative detection methods. Big Data Analytics enables the analysis of vast datasets, including transaction and user behavior data, to identify anomalies and assess risks. Real-time processing is essential for swift fraud identification. Challenges include data quality, privacy, and the need for scalable infrastructure. Case studies show successful implementations, such as PayPal and HSBC, which use machine learning and real-time analytics to detect fraud. Emerging technologies like blockchain and AI are expected to enhance fraud prevention strategies. The paper emphasizes the importance of ethical use of data, transparency, and collaboration in the financial industry. Future trends include the integration of deep learning, blockchain, and edge computing to improve fraud detection. Security and ethical considerations are vital to ensure the responsible use of Big Data Analytics in financial fraud detection. The review concludes that Big Data Analytics is transformative in enhancing fraud prevention and strengthening the financial ecosystem.