Over the last few years, the rise of digital transactions and information has caused a large-scale increase in complex forms of financial fraud. Traditional methods for identifying fraudulent behavior are often not sufficient in detecting advanced and large-scale frauds. This paper discusses how the use of Big Data Analytics may improve and enhance the detection of Financial fraud through real-time monitoring, pattern matching and predictive analytics. This paper also provides a review of some major techniques, challenges, and applications for Financial Institutions to utilize Big Data tools so that it could enhance fraud detection accuracy and operational efficiencies. Finally, this paper discusses possible future trends and makes recommendations for Financial firms to use as they seek to utilize Big Data in their fraud prevention efforts.