There are many advanced analytics use cases in banking spaces. Advanced analytics is used in credit decisions, fraud detection, predictive analytics, marketing, etc. In this blog, we will see how some of the top-notch private banks like HDFC Bank, ICICI Bank are making the most out of analytics. Advanced Analytics is a gateway for them to build an INR 5000 Crores book for Banks per 1 Crore customer base. On the other hand, there are still many banks that have not yet been able to capitalize on this opportunity due to several reasons like:

• No quantification of the advanced analytics benefits
• Lack of skill, knowledge, and expertise
• Data security concerns
• Legacy systems
• Resistance to change

In this blog, we will focus on the big picture, i.e. monetary benefits of analytics like book building of INR 5000 crores per 1 crore customers.

 

Case-Study: HDFC Bank Credit Card Cross-Sell

Let’s analyze the HDFC Bank Credit Card book growth using information available in the public domain. A back-of-the-envelope calculation shows that HDFC Bank is growing its credit card book by Rs. 7619 Crores per 1 Crore of Saving Account customers. Shown below is the detailed calculations using the data available in the public domain.

• Aug 2019 Economic Times article titled “HDFC Bank crossed the Rs 50,000 crore-mark outstanding on its credit card book.” Key points from the article are:
  • HDFC Bank crossed the Rs 50,000 crore-mark outstanding on its credit card book.
  • Credit card customer base of 12.5 million (1.25 crores)
  • Average outstanding per customer = Rs. 50000 crore / 1.25 crore customers = Rs. 40000 per customer
  • Bank expects to double the Credit Card base in 1 year, i.e acquire 12.5 million credit card customers
  • Expected per month acquisition of credit card customers = 1 million

 

• SAS Case study – More than 70 percent of HDFC Bank’s credit card portfolio is now from cross-selling
  • Therefore 700000 (= 0.7 * 1 million) credit card customers are acquired by cross-selling
  • Annualized number of Credit Card acquisition from cross-selling = 700000 * 12 = 8.4 million

 

• Expected Growth in Credit Card Book
  = 8.4 million customers * Rs. 40000 average outstanding per customer
  = Rs. 336000 million
  = Rs. 33600 Crores

 

• Reference: HDFC Bank Investor Presentation
  • Overall Customer base as on Mar 2019 = 49 million
  • Assuming 90% of the base has a Savings Account relationship.
  • SA Customer base = 49 million * 0.9 = 44.1 million (4.41 crores)

 

• Credit Card Book Growth per 1 Crore Customers
  = Rs. 33600 Crores / 4.41
  = Rs. 7619 Crores

 

Savings Account is Goldmine

Goldmine means a source of great wealth or profit or any desirable thing. This definition of goldmine holds very true for the Savings Account base of banks. Why?

• The savings account base is a readily available base for the bank to sell many other products like Loans, Investment, Insurance, etc.
  • Loans: the customer may need a loan for education, personal needs, buying a home, vehicle, vacation, marriage, etc (Education Loan, Home Loan, Car Loan, Business Loan, etc)
  • Investment: a customer may want to invest or save for the future (Mutual Funds, Fixed Deposits, etc)
  • Insurance: the customer may want to insure themselves, their property, or their near-dear ones (Health Insurance, Term Insurance, Vehicle Insurance, etc)
  • Services: looking for convenience and easy payment services (eWallet, Credit Card, Net Banking, ATM, etc)

 

• The savings account base is the largest customer base for any bank. As such, the opportunity to sell is also huge.
• The cost of building the book by cross-selling to existing customers (organic growth) is less than one-fifth of the cost compared to building the book from new customer acquisitions (inorganic growth).

 

In true sense, the existing customers are a treasure trove, a goldmine if mined properly.

 

Goldmine, if mined properly

Acquiring a new customer is five times or more expensive than selling to an existing one. However, the revenue growth and cost-saving benefits from existing customers can be realized only by selling the right product to the right customer at the right time. Let us understand this with an example:

Example: MyBank wants to grow its Mutual Funds portfolio

Let us assume you are working in a Bank and the Chief Marketing Officer suggests that he wish to run a campaign to promote a financial product, Mutual Fund Investment Product. Based on business filters, you have an eligible contactable base of 1,000,000 customers in your database.

Given:
The cost of targeting each customer through Email, SMS, and IVR is Rs. 10/-
It is expected that the campaign will lead to 0.5% incremental conversion vis-a-vis no campaign
The expected revenue per customer who purchases the product is Rs. 2500/-

Cross-selling without mining Strategy: The contact information of the customers is readily available within the bank’s system. Bank can simply bombard all the customers using low-cost channels like Email, SMS, IVR calls,  etc to generate leads. The pitfall of this strategy is that we may target many wrong customers who are not potential for mutual fund investment (more dust than gold). Shown below is the Return-on-Marketing-Investment (ROMI) calculations:

 

Cross-selling with Mining Strategy: The transaction details of the customer can tell a lot about the customer and his needs. Using data analytics, a bank can easily identify the customers who are potentially looking for some investment in Mutual Fund and run a focused below-the-line (BTL) campaign.

 

 

How to Mine? 

The buzzwords Business Analytics / Data Analytics has been around for quite a few years. The senior management of all the banks clearly understands the benefits of analytics. If asked a question – “Does your organization make use of Data Analytics?” The answer will be an emphatic YES. However, in closed corners, most of the bankers are still not confident about – How do we best implement Data Analytics? How to Mine?

These questions are supposed to be answered by the Analytics Department of the organization. But unfortunately, many organizations are unable to set up the analytics practice. The key challenges in setting up the analytics practice are:

• Lack of skill, knowledge, and expertise.
• Investment in setting up the analytics practice

 

I personally feel that finding data science skills is much easier. You have many possible solutions:

• Outsource
• Hire a few Data Science resources at a premium to set up the analytics practice
• Get skilled Freelancers to set up the team
• Get your internal IT / BIU / Functional Teams trained on Data Science

However, the challenge is the budgetary allocation to set up the analytics practice. For this, the CXO’s of the Bank has to take a leap of faith and invest in the setting up the Analytics Practice.

I hope this article on “Advanced Analytics – Gateway for Banks to build INR 5000 Crores (INR 50 billion) Book per 1 Crore (10 million) customers” has provided you the confidence to take the plunge in investing your time and money in Data Analytics.

 

Recommended Reading: 

• Story on How Banks Lose their Valuable Customers
• Credit Risk Scorecard
• Analytics Fusion of Science and Art

References: 

1. Bobs Guide – Bank yet to fully adopt advanced analytics
2. Harvard Business Review – The Value of Keeping the Right Customers
3. Aug 2019 Economic Times news article – HDFC Bank crossed the Rs 50,000 crore-mark outstanding on its credit card book.
4. SAS – More than 70 percent of HDFC Bank’s credit card portfolio is now from cross-selling
5. HDFC Bank – Investor Presentation