ArticlesBig DataBusiness IntelligenceCustomer IntelligenceCustomer ServiceFintechTechnologyThe Role of Data Analytics in Digital Banking System Transformation

Herry ParindraMay 7, 2019



Adoption of digitalization now becomes a fundamental part of the banking system since currently, people have rapid access to banks due to online banking. Cashless transactions have become as easy as a minute click on the tip of a finger at any place and any time. To improve performance, banks require data analytics to create a better service for enhancing the customer experience. Data analytics also can drive-up sales and enable the team to feel more distinguished.

In history, banks solely targeted on product and sales, while customer services and experiences were out of notice. However, nowadays things are ever-changing considerably. Technology has changed the way customers, individual or organization, act across each business so all lifestyle activities currently leave a digital track. No surprise that banks adopt digitalization to equip faster service resolution, competitive rates, and easy-to-use web site or mobile apps. For example, we have helped one of Indonesian oldest Bank in providing companies with a Marketplace & Payroll Application to enhance their customer’s businesses.

Banks strong position is truly supported by the huge customers’ data that are accumulated through historical transactions. They are able to access a full view of every customers’ monetary life and lifestyle preferences by leveraging the data. With the increasing adoption of digital channels and social media, banks require a 360-degree view of their customers’ lives and supply a segment-of-one customer experience.

Below are a few examples of how data analytics enablement made an impact on the banking industry:

  1. Customer spending patterns identification
    Customer’s historical data is an important factor for banks to identify data for wider analysis. Banks can set some keys to assessing risks, conduct screening for a loan, evaluate hypothec, or financial products offer such as insurance, and more.
  2. Customer transaction classification
    Banks have valid data when their customers withdraw all of their money, or just taking a little and save the rest in their account. This information is useful to classify which customers are available for bank’s product approaching and offer a good rate of short-term loans or other products.
  3. Customer profiling
    Banks can create a customer segmentation or customer blacklist from the complete data record on customer spending patterns, and, this segmentation can help banks implement evaluation of the cash flow and a good financial plan for better customer financial management.

Banks change from traditional face-to-face customer relationships to digital relationships. Faster client journeys during sales, service, and problem resolution can help banks aware of the maximum lifetime value of their customers. That is why, banks need to identify prospective customers and market to analyze customer capability to pay off loans, pay insurance, and more. Banks ought to work to ensure that all functions work together with a view of the customer status to provide constant customer experience across all lifecycle stages.

WGS has a great experience with the finance and banking industry in Indonesia and beyond, we’re confident that we can be a good assistance to discuss data analytics and improve your banking services to meet your goal.


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