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Globalization deleting the barriers between countries and locations from the market is no longer boundaries to arrive at the markets in any nation. Today's executives of business are challenged with high competition, high customers' anticipation, and expectation, increasing costs of materials and labour, and short product life cycles. In such an environment unsteady, companies need to scan continuously for opportunities and risks and make decisions quickly for business based on data availability (Jeble & Patil, 2018). The development of information technology and the internet provide a massive amount of data produced in various fields. Big data is used to describe this phenomenon in the digital world (Wu et al., 2018). Quantity of data increased every year, and the low price of data storage and computing make significant data adoption (BDA) desirable for companies as a tool to get a competitive advantage (Sanchez and Ramos, 2019). Big data is more accurate and robust than the traditional techniques used in analytic in the past. Adopting big data help managers to make better decisions based on evidence rather than anticipation (McAfee et al., 2012).
According to Jeble et al. (2018), big data helps managers in making forecasts in better ways, make smarter marketing- decisions, and help business managers to use big data for better managerial & marketing practices. Big data play a significant and vital role in the banking sector: Banks have a vast quantity of data. There are several accounts preserved with a considerable number of deals and information; traditional technologies cannot preserve the clients' and different deals because BD (Big data) is extensively used in the banking and exchange sector, preserving all the data related to this sector. Also, big data gives many advantages to the bank sector; it helps in card fraud detection and provides an early warning for securities fraud. The Securities Exchange and Commission are using big data to reveal financial market endeavours and actions by using network analytic and natural language processors; this helps to catch illegal buying and selling activity in the financial markets (Goyal et al., 2017). According to Goyal et al. (2017), the great opportunities of the benefits of big data come from various risks of managing the data accurately, and this data is essential for financial services companies that consist of information about clients' accounts. The significance of big data in the business and marketing activities and the future business survival related to the capability and competence to understand and exploit big data for a competitive purpose (Grover et al., 2018).
There is also competition in the banking industry over increasing customer reach with online-based tools. Banks offer personalized product offerings through online banking, mobile banking, and ATMs. Efforts to reduce risk in banking transactions and increase access to reach a broader customer base require access to an enormous amount of data as well as the ability to process this data to draw meaningful conclusions that can be used for decision-making (Zhong et al., 2016; Breed and Verster, 2019; Rana, 2019). big data analytics prepares to play an essential role in boosting the banking industry's growth and mitigate the amount of risk. Banks mainly use big data analytics for marketing analytics, risk management, fraud, and strategy formulation (Wamba et al., 217).