Improved Digital Banking through Data Analytics

The banks have not seen the savings they expected as a result of the shift to digital products and services. Leading consultant to some of the biggest US banks shares a step-by-step guide on how to use smarter analytics for customer data in order to reduce costs and increase customer satisfaction.

Authors are experts in their field and only write about topics where they have experience. Toptal experts who are also in the field review and validate all of our content. 

By Mohamed Zarrugh


Mohamed is an expert in finance who has worked as a consultant for JPMorgan Chase, Wells Fargo and other companies. He transformed operations and saved the companies up to $180 million per year. He is an expert in strategic planning, process improvement, and performance management.



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Financial institutions are saving money by using digital banking instead of maintaining brick-and-mortar locations. Legacy banks in the US have been shrinking branch networks for over a decade. COVID-19, a pandemic that affected many countries, led to the closure of even more physical services. This accelerated the move towards digital banking. Customers can now access their accounts, products, and services via a website or app.

The digital banking industry has been growing steadily in recent years, particularly during the COVID-19 epidemic. This trend is expected to continue. This growth will likely be accelerated by improving customer experience through deeper and more granular analytics.

It is not surprising that banks spend more on technology than ever before, with the goal of improving service and customer experience. Financial institutions are not reaping the full benefits of their digital investments due to increased call center spending to address mounting customer concerns.

2020 survey from the management consulting firm Capital Performance Group found that, from the end of 2019 to December 2020, online banking activity–including transactions and other interactions–increased as much as 30% and mobile banking activity surged as much as 80%. It also showed that the contact center volume had increased by as much as twofold at some institutions. A survey by Cornerstone Advisors revealed that customers were calling their banks more often because they couldn’t find the answers to their questions online or their financial institutions didn’t offer virtual support.

These statistics highlight the unfortunate truth that many of the digital products and services banks have been offering for years–from payment systems like Zelle to authentication–still fail to meet customer expectations, often because using them doesn’t feel intuitive enough. Zelle has also been plagued with issues concerning disputes, including those relating to fraud and unauthorized transactions.

As an advisor for several of the United States’ largest commercial banks, I have seen first-hand the challenges of digital transformation. The data banks have is not being used to develop strategies that will drive customer retention. data analysis is not robust enough in most institutions to provide the information needed to better understand user needs and to determine how to best meet them. When recording and listening to calls for quality assurance, support teams use petite sample sizes. The sample size was 1% or less at one bank I worked. Extrapolating results can lead to misleading results.

To solve these problems, banks must develop more comprehensive, holistic customer data analytics for all phone calls. They must then use the patterns they discover to create and enhance digital functionality that meets customers’ needs. This article will walk you through my steps to help banks achieve this.

Create a Strategy Team

A team of analysts and product specialists from the bank will be formed to increase customer satisfaction and adoption. This team will have full access to all data collected by all channels and products. The team is necessary because the amount of data available to analyze, aggregate and draw conclusions is too large for one person. This team must also work closely with the department heads to implement its findings at the enterprise level.

This team should be subdivided into smaller cross-functional teams for each product. In my work for a commercial bank, I would tell each group how many calls they could eliminate by implementing specific features or functions so that it could prioritize their work. For this calculation, I used our proprietary platform for customer journey analytics to analyze user flow and friction. Tealeaf and Google Analytics are both similar tools you can use to achieve the same goal.

Establish your goals and identify the categories of data.

Second, you need to identify and gain access to all the different data sources available across platforms and functions. In a typical legacy banking institution, data sources are divided into two categories and many subcategories. As an example, I used the following tools when I created teams at banks:

Businesses and Products

  • Retail accounts, including checking and savings
  • Credit Cards
  • Mortgages
  • Automobile finance
  • Wealth Management

Contact Points

  • Calls to the contact center
  • Contact center interactive voice response (IVR) communications
  • Retail branches: In-person interaction
  • ATM Interactions
  • Desktop Application
  • Mobile application
  • Outbound notifications/alerts

My analytical work focused on the call statistics of contact centers. This is where you should focus your attention. The vast majority of customer service requests come from call centers. Banks no longer accept email for customer support because it is too expensive. Chat is replacing email, but it only accounts for a small part of customer service interactions at top banks. Less than 5% in the institutions I visited. A live agent call is also costly for banks due to the volume of requests. This is what I will focus on when I describe my process.

After identifying and accessing data sources, financial institutions can start establishing key metrics that will help define the project’s scope, which can be used to set up the strategy for solving problems. These are the goals we set at the banks I worked with:

  • Improved customer experience, measured by net promoter score. This is a crucial indicator of customer satisfaction and assesses the likelihood that people will recommend a company across all channels.
  • Digital adoption and engagement can be increased.
  • Contact centers are not adding value to your business.
  • Reduce the number of low-margin basic banking transactions at branches.
  • Reduce risks and improve efficiency across all service operations.

The data revealed that digital is the most popular channel for customer interaction. In the banks I worked at, however, it was surprising that highly active digital users were more likely to ask for support than those who used traditional or less active digital banking. Digital banking resulted in more than double the number of calls and inquiries in contact centers compared to conventional banking.

Understanding Why Customers Call

After identifying data categories and goals, the team should consider the types of queries that will allow it to assess the nature and circumstances surrounding customer support requests. We asked the following questions at the banks I worked with.

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