At a time when banking is getting commodified- the mining of Big Data gives huge opportunities to be a step ahead from the opposition. Each banking transaction is a small piece of data, so the business sits on a vast reservoir of data. The Banking business produces an enormous volume of data on a daily basis. To separate itself from the competition, banks progressively embracing big data analytics as a major aspect of their core strategy.

Analytics in Banking

Analytics will be a vital advantage for the banks. One of the primary benefits that conventional banks have is the massive amount of financial data they hold about their large number of clients. They likewise have the structure and funding to exploit it. The applications for data and analytics in banking are endless. They can utilize data for noteworthy personalization, empowering them to offer products and services tailored towards individual customers in real-time.

Data will likewise imply that banks would be able to estimate the risk of offering a loan to a client. Predictive analysis models can break down customers’ credit history, loan or credit applications, and other information to survey whether the customer will make their payments on time later on. They can likewise consolidate client criticism with social media comments and other unstructured data to create a complete client profile, thereby minimizing exposure to risk around non-payments.

Big Data Technology

By utilizing the data science to gather and examine Data, banks can enhance, or rehash, almost every part of banking. Data science enables better marketing, enhanced transaction processing, customized wealth management advice and a lot more – the potential is endless. A huge proportion of the current Big Data projects in banking rotate around clients – driving sales, boosting retention, enhancing service, and identifying needs so that the correct offers can be served up at the right time.

The banking industry has unrestricted access to a ton of individual data of their clients. The available data has a lot of possibilities when used by the banking sector successfully. The banks right now can track client exchange in real-time. Through the available data, the bank can fragment the client in light of various parameters, for example, total assets; the client preferred credit cards among others.

The segmentation of clients has enhanced the banking industry’s marketing sector. The bank would now be able to build up a marketing system to channel it to specific market niches. The altered marketing strategies have expanded market reach in the banking sector and extended the client base of banks.

Improve Operational Effectiveness

The three critical inquiries in utilizing big data analytics for product and service definition and the vital customer segmentation is where are banking users originating from, where are they now and where are they going. Firms must construct a predictive model which helps the operations team to interpret, with the client at the center of the business logic, and which prompts specific actions. The thought is to define services adjusted to client needs and interests, by considering customer conduct and the channels where banking users show the most commitment.

Firms must still fully explore the use of big data in the banking industry. The expenditure on big data is expected to elevate as an increasing number of banks completely embrace big data analytics. The phase of the banking industry will change when the industry fully uses the broad application of big data.

The client experience is likely to change in the future. The effectiveness of bank operation, real-time sharing of data will enhance service delivery and consumer satisfaction in the banking industry. Without a doubt, the eventual fate of the banking industry depends on big data analytics.


Written By: Mr Rajiv Prasad