Role of data in banking technology

Posted by Lisa Williams on January 14th, 2021

Since the banking industry embraced digital technology as its primary means of customer interaction, banking customers have generated huge volumes of digital transactional data. The good thing about digital data is that it can be accumulated, aggregated, and maintained effectively. However, the mere storage of data will not bear any fruit until and unless it is analysed. The thorough analysis and in-depth reporting of the data of each customer are termed as big data analysis. The banking industry can rightly be considered one of the pioneers of big data management. 

The question is what does banking analytics achieve, which helps banks maximize their profitability? Here are a few of those achievements. 

1.Risk management strategy

Banking analytics can help banks develop individual profiles of each customer, constituting their history and current transactional information. This data would help identify the risk involved with each customer by observing their financial behaviour. Eventually, this would help the banks decide whether the customer is worthy of loans or not. In case the customer is worthy, up to what amount can the bank provide loans without risk? This activity of risk identification required hours of document analysis by banking personnel before the advent of banking analytics and modern banking technology. 

2.Sales automation

Almost every bank spends a proportion of its budget on marketing the benefits of its features and policies. Now, it is a concern for the marketing team of banks that several features would interest only a specific set of customers. However, since marketing is mostly a common medium, every customer is provided with the information. When a customer finds information irrelevant, they feel spammed, which seriously affects their trust in the bank. The solution to this problem is personalized advertising. In this, a customer is given the information he or she is genuinely interested in. Banking analytics has made this possible by identifying customer needs and clubbing them based on their needs. The marketing team can now broadcast different messages for different segments. 

3.Product innovation

A benefit of banking analytics is that it can predict customer behaviour based on the changing patterns of its interaction with the banks. The information can be used to design new products and services. This is an example of how technology eliminates the risk of product innovation going wrong.