Co-authored by Dr. Eric G. Krause

The proliferation of customers across the world and their “on-the-go” lifestyle has triggered a sharp rise in digital banking – one that is virtual and remote, and void of the traditional personal touch that was once the cornerstone of in-branch banking.

The familiarity and human connect of a trusted financial advisor was an integral part of the banking journey for the customer – a vessel to realize their financial aspirations and fulfill their personal goals. The banking experience today for a majority of the customers of the digital era is anchored around the screens of their desktop and smartphones.  So how can the unique touch, relationship, and engagement be reinstated and sustained at an intimate level for the banks of today?


Our take on Personalized Mobile Banking

The current market landscape leverages mobile banking as a complete information source, where customers can choose to check their balances, go to the expense analysis tools and then independently adjust their budgeting strategies.  There is limited personalization.

The advancements in artificial intelligence, machine learning, and natural language processing make personalized financial advice a real possibility.  

With the advent of open banking, aggregating a combined financial view of the customer’s balances and financial history is possible. This also provides an excellent source of new data for banks. Moving beyond this, generating personalized insights on the customers spending can enrich the value proposition and bring banks a step closer towards re-establishing customer bonds.

The example as illustrated below is one of many ways to do that. Let’s assume the application has categorized the expenses for electricity, and it is 10% more than usual. Further comparison with other electricity providers shows that the customer could switch and save around $125 per month.


An example of personalized financial insights



These insights, however, would not be as useful without a reward and reinforcement functionality, where after the switch or the adjusted electricity usage the customer is shown the amount of savings realized. Closing the loop and advising the customer to use those savings for a personal savings goal goes even further by showing the warmth and care of the bank for the things that matter most to the customer.


An example of personalized financial insights


We all spend money on things we could forgo or we round up the prices in our calculations but rarely use the small amounts that we could spare in a meaningful manner. What if the application, leveraging intelligent automatic savings could aggregate the amount and put it aside for the customer towards their savings goals?

But banking is not only about saving money. Millennials like to have a new phone every year, we like to shop online, but, the account balance struggles to keep pace. What if by the smart leveraging of intelligent computer vision technology we could scan a product in an online shop, and then see whether we can afford to buy it in the near future or pay for the product with installments? Won’t that be a nifty little tool?

This wealth of data facilitates prediction of important life changes among customers. Moving to a new apartment involves sending the security deposit through your bank account. Changing employers means getting a salary from a different entity. These can be leveraged by banks to provide personalized insights on what’s most relevant to the customer based on her or his major life event.


What does this mean for banks?

Customer equity is the total lifetime value of each customer multiplied by the number of customers. The customer lifetime value is the sum of the revenue generated by the customer minus the acquisition costs multiplied by the retention rate discounted to the present day. By leveraging such use cases three key components can be affected:

  • More customers through more advocacy
  • Better retention rate through increased customer satisfaction
  • Higher profits through capturing a bigger share of wallet

While what’s available in the market today is still relatively low on the maturity scale, this is an opportunity for innovative banks to shape the market of the future.  

Co-authored by Dr. Eric G. Krause

Dr. Eric G. Krause

Dr. Eric G. Krause

Partner, Infosys Consulting

Eric has more than 19 years of experience in the banking industry and heads up our financial services sector in Germany. He joined Infosys Consulting in 2014 from PricewaterhouseCoopers where he was an advisory partner and prior to that, has held various senior management positions at Capgemini and KPMG. Eric started his career as a banker, working for HVB/UniCredit and Dresdner Kleinwort Benson, before moving to consultancy. He holds a doctoral degree from Universität St. Gallen (HSG), CH.

Gevorg Karapetyan

Gevorg Karapetyan

Senior Consultant

Gevorg has more than 8 years of experience in digital transformation and Consulting. He currently focuses on AI-powered digital banking platforms for our German Financial Services practice. He specializes in strategy and digital product design leveraging AI/machine learning and automation. He complements our financial projects with strategic approach development including our proprietary 32E innovation and design approach and supports our innovation hub team with use cases for “Next in Banking”.  He holds an MSc. from the Goethe University in Frankfurt and a Licence from IAE Jean Moulin Lyon 3 University.  

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