ABSTRACTThe information faster, avoiding any potentially embarrassing situations. Big

ABSTRACTThe banking industry has evolved over the past decade, when it comes to operations and service delivery. Surprisingly though, most banks have failed to utilize the information within their own databases. Switching to Big Data will allow them to process this information faster, avoiding any potentially embarrassing situations. Big Data is huge step towards the development of banking industries, and will propel it into the 21st century.Big data analytics is authorizing Banks to analyze large amount of data they gather during financial transactions and others as well. Cyber crime specialists are now using big data tools to identify the potential threats and detect cyber crime incidents like credit card frauds and rectify such threats. Big data can help the banks prevent cyber-thefts, improve regulatory compliance, detect credit card fraud by understanding customer behaviour and detect criminal nature. In order to ensure high quality data collection throughout its lifecycle , every organisation follows a process identified as Data Governance .This means the data can be trusted and that people can be made accountable for any adverse event that happens because of low data quality. INTRODUCTIONThe Big Data can not be easily stored, manipulated or analysed with traditional methods like spreadsheets, relational databases or common statistical software due to its main characteristics”the three V’s “Volume : The data is called Big data because its big to work on our computer.Velocity : The data is coming very fastVariety: Different types of data stored structured business data to unstructured data. Banking is a massive industry, which possesses various facets which includes; credit card lending companies, retail banks, and investment management companies. All of these companies approach the issue of fraud detection and prevention in a different manner. Among these businesses, a business that suffers the most is the credit card lending companies.Big Data, either acquired from internally generated data or some source is to be used in the manner that is in sync with the organizational vision and mission. The banks should be able to use this data to meet their predetermined objectives which can be either to reduce cost, minimize the time taken in the processing, provide security and confidentiality to their customers, keep growing the bank profitability by providing targeted customer advice, prepare themselves for the future and most importantly protect their brand. All these and others factors and variables should ultimately lead to the better decision making in the organization.Fraud detection is one of the most evident uses for Big Data Analytics.With rapid advancement in the digital world, usage of credit cards has also increased significantly. Compared to traditional approaches, Big Data Analytics provides an efficient cyber security context by separating the patterns generated by authorized users from those generated by suspicious or fraudulent users.Another advantage of Big Data in banks is to know The Customer and Customer retentionAs customers are increasing in digital banking, financial institutions have opportunities to better understand and serve them. Seeing how a customer moves through their website or adopts the latest apps can provide tremendous insight.As banks move toward understanding customers in the digital world, Big data helps banks to combine the small data view with large data approaches to get a better understanding of their customers.Using big data and technology, the banks may be able reap some of the following benefits also:§ Find out the root cause of issue and failures§ Determine the most efficient channel for a particular customers§ Identify the most important and valuable customer  § Analyse the risk and the risk profiling§ Customised products and customised marketing communication§ Optimise human resources In this report, a brief survey is made about few application of big data in banks to detect the frauds related to credit cards by analysing large set of data and Customer retention.