In today’s data-driven world, data analytics in banking play a crucial role in informed decision making to drive organizations forward, improve efficiency, increase returns, and in turn achieve business goals. For the uninitiated, data analytics is the process of discovery, interpretation, and conveying meaningful insights from the data to help in the decision-making process……
According to the latest Worldwide Semi-Annual Big Data and Analytics Spending Guide from one of the top research firms, worldwide revenues for big data and business analytics will go up to more than $203 billion in 2020. The applications for data analytics are significantly growing day by day because of various innovations in the field. Out of this $130 billion market share, the banking sector leads revenues with a contribution of $17 billion in 2016.
In the Banking and Financial Services sector, through data analytics, institutions can monitor and assess large amounts of customer data and create personalized/customized products and services specific to individual consumers.
For example, when a customer buys a vehicle, the bank sends promotional offers of insurance to cover the customer’s vehicle. In the future, such applications could be expanded even further. One way this could happen is if a customer got a large bill, the bank could offer an EMI conversion or a loan to cover the cost.
Some of the areas where banking and financial institutions are increasingly using data analytics include:
- Fraud detection
- Managing customer data
- Risk modelling for investment banks
- Personalized marketing
- Lifetime value prediction
- Real-time and predictive analytics
- Customer segmentation
- Customer spending patterns
- Transaction channel identification
- Customer feedback analysis and application
The importance of data analytics in the banking and financial services sector has been realized at a greater scale and most of the established banks have already started reaping the benefits.