Introduction Infinity bank was one of the 10 largest banks in the UK with over 1800 retail branches. However, due to the change in the nature of the banking industry since the 1980’s Infinity bank had seen a consistent drop in its profitability. Deregulation of the industry had been one of the major changes that had taken place during this time which had increased the competition in the industry. Even though Infinity had followed other major banks in responding to this challenge by cutting costs, closing branches and making use of information technology, its results were far worse than others.
Since retail banking was a major source of their costs as well as revenue, they conducted a branch efficiency review which pointed out issues with underperformance and wastage of resources. Another issue that cropped up was that branches did not know which the most profitable products were. After conducting their first costing activity to understand product profitability they found out that Current accounts, which was their main product, were highly unprofitable. Mortgages and Credit Cards on the other hand were profitable. Details of the customer segments are given in Table 1.Order now
This led them to devise a strategy called the “Supermarket Strategy” which made branch manager responsible for their own P&L and be rewarded for selling profitable products. Product Combinations| Accounts(in Millions)| Current Account only| 3. 70| Credit Card only| 0. 50| Mortgage only| 0. 11| Current Account + Credit Card| 4. 20| Curent Account + Mortgage| 0. 39| Credit Card + Mortgage| 0. 05| All 3: CA + CC + M| 0. 31| Total Customers| 9. 26| Table 1: Customer Segment Details However, some managers believed that this strategy would not work and that hey needed to sell unprofitable products like Current Accounts to customers in order to build relationships which would lead to the selling of more profitable products later. Accordingly, a customer profitability study was done with a sample of a 1000 customers for each product category and cross-holdings. In the light of this data will the “Supermarket Strategy” work for Infinity Bank? Analysis of Customer Profitability Data While it is good to have Customer and Product profitability data, the real value can only be extracted from this data if it can be used to devise a consistent strategy, control systems and operating procedures.
Keeping this in mind, it is very important to analyze the Infinity bank customer profitability data to see whether the proposed “Supermarket Strategy” is really the way to go for them. One way that we can analyze this data is to analyze the distribution of profitability. To do this, we can use the Stobachoff curve (Storbacka, 1998). This curve gives us a graphic view of how many customers are actually profitable. To plot this curve, we order the profitability data from highest to lowest. We then plot the cumulative profitability percentage on the Y-axis and the cumulative customer percentage on the X-axis.
Figure A: Interpretation of Stobachoff’s Curve (Raaij, Vernooij, Triest, 2003) Looking at this curve can give us an idea about what percentage of customers are subsidizing others and what are the kinds of risks associated with it. This is summarized in Figure A. The four quadrants are divided by the level of subsidizing effect and the dependence on customers. In the case of Infinity Bank, this curve was plotted for each of the 7 customer segments mentioned in Table 1. These are shown below. 1. Current Accounts Only| 2. Credit Cards Only| 3. Mortgage Only| 4.
Current Accounts and Credit Cards| 5. Current Accounts and Mortgages| 6. Credit Cards and Mortgages| 7. Current Accounts, Credit Cards and Mortgages| The Stobachoff curve for Current account customers is shown in Figure 1. If we look at this curve we see that only about 20% of the customers who hold only current accounts are profitable. They contribute 20% to the profitability of current accounts. The rest 80% of these customers are making a 120% of the losses. This kind of a situation looks really bad on paper. But of course, statistics only tell half the story.
If Infinity managers were to base their decisions solely on this number then they should probably fire most of their current account holders. This issue will be analyzed further on in the paper when we discuss the recommendations. The story is completely different in the credit cards only segment in Figure 2. As we can see, around 95% of the customers contribute to nearly 170% profitability. There are 5% customers who cause 70% decline in profits. If we put these numbers in the context of Figure A, we see that this curve fits the top right quadrant where a small number of customers are highly unprofitable.
So there is room for action. If we look closely at the data, we find that these small numbers of customers are the ones who defaulted on payments. So the bank needs a strategy to ensure that defaults do not affect the segment profitability to such an extent. It’s important to note that in Figure 3 which shows the curve for just mortgages, one single customer which is 0. 1% of the dataset causes a decrease in profitability of 20%. This is a significant figure and highlights the risk of default in mortgages. Another significant result we can see is from the Current accounts and Credit Card Segments shown in Figure 4.
As we can see here, 75% of the customers are responsible for generating 130% of the profit and the rest are driving the profitability down. Again, a lot of the losses are driven by the defaults on Credit Cards. This is similar to the Credit Card only segment. As we discussed earlier, the point of doing this analysis is to see the vulnerability of the customer base and see the degree of subsidization. We can see by these graphs that there is a high degree of subsidization in the Current accounts segment, so much so that the profitable customers are not generating enough profits to cover for the loss making ones.
The interesting thing here is that customers who have mortgages either alone or along with other products are consistently profitable with very few incidences of losses. This might lead us to believe that Supermarket Strategy would work for Infinity with a focus on selling highly profitable mortgage. We will discuss more about this in the recommendations section. Can this data also give some insight into why current accounts are so unprofitable? Even though averages can be misleading, they can provide some insight.
To find some information why current accounts are so unprofitable I took averages of the costs and revenues for profitable and unprofitable customers. What is evident from this data is that because unprofitable customers keep a lower average balance in their accounts and are more expensive to serve, they tend to drive the revenues down. Also, if the sample is an indication of the real pattern amongst consumers then just 30% of the current account customers are somewhat profitable. Profitable| Unprofitable| Average Service Cost – ? 51| Average Service Cost – ? 101| Average Balance – ? 142| Average Balance – ? 1046| Average Income – ? 65| Average Income – ? 32| Table 2: Difference between Profitable and Unprofitable Current Account Customers Another thing that can be looked at is the scatter plot of profitability and revenue. This can help judge which customers are actually profitable instead of just adding large revenue and not profitability. This plot for current accounts is shown below. Figure B: Revenue vs. Profitability Scatter Plot What can be seen from this graph is that for the same revenue earned by current account holders, there is a remarkable difference in profitability.
This means that there is variability in the kind of service that different holders require hence adding to costs. Now that we have seen from the data that current accounts holders are dragging the profitability down, what can be done about it? Recommendations Should Infinity bank fire the unprofitable customers?? The problem with using the given data as the basis for getting rid of unprofitable customers is that customer profitability analysis (CPA) is just analyzing historical data and giving insights into that.
Undoubtedly, the information it provides is very important, but “a true valuation of the customers would include future expected contributions, both direct and indirect” (Raaij, Vernooij, Triest, 2003). As defined by Kotler in 1974, customer lifetime value “is the present value of the future profit stream expected over a given time horizon of transacting with the customer” (Kotler, 1974). In banking customer lifetime value can hardly be overestimated. In case of Infinity Bank, there is not enough data that has been collected which could tell what the lifetime value of the customer is.
For example, it might be that even though current accounts are loss making, they act as a great way to acquire a customer for future sales of profitable products. If that is the case then firing current account holders will be the wrong decision. Again the data given is not clear enough about the demographic of the customers. It would be very helpful to do a proper CPA which takes a lot more data into account and also accounts for other factors such as Age, account holding duration, location/branch etc.
If these factors are taken into account, we will surely get a lot more insight into the unprofitability/profitability of current accounts. An implementation of a CRM/Business Intelligence system would go a long way in providing the bank with information needed to do a better analysis of customer profitability. Having a good CRM system in place will also ensure a better understanding of the customer. This will mean that when giving out credit cards and loans the bank can be quite certain about the risk of default relating to the customers.
One thing that is not taken into account at all here is the cost of customer acquisition. It may be easy to fire a whole lot of customers because they are unprofitable, but to get new customers in the preferred segment might be really costly. This cost has not been accounted for in the data given and may prove really important in Infinity bank’s case. An interesting thing to pursue in terms of getting unprofitable customers to be more profitable is to offer them incentives like attractive interest rates on mortgages and credit cards.
This strategy might work better than firing them because of the lifetime value issue. Of course, a better study may reveal that customers who buy profitable products after x years are not really profitable. The bank can start charging them higher rates/fees in these cases. Conclusion So would the Supermarket Strategy work? In light of the analysis done and the recommendations made, I believe Supermarket Strategy might not work that well. The strategy was implement based on product profitability data and did not take into account customer profitability.
The major issues that might arise from the strategy would be issues of managers concentrating of short term P&L rather than long term relationship building which is very important in the banking business. It would also bring up issues of trying to force products down the customers’ throat which might not work well with their customers. As the data shows us, even though credit cards and mortgages are profitable products, defaulters can bring down the profitability of any product line. We saw in the case of credit cards that 5% of the customers brought down profitability of the entire segment by 70%.
Similarly, in case of mortgages, just one customer brought down the profitability by 20%. Right now, Infinity’s exposure to such customers is low with mortgages and credit cards amounting for a small percentage of business. With Supermarket strategy in place managers would be pressurized to sell more of these products to meet targets and the quality of the customers (in terms of credit ratings) might go down. If that is the case, the risk of defaulters would increase manifolds and this can cause an overall decline in profitability instead of an increase as Infinity’s managers envision. References
Cognos:An IBM Company. (2008) Customer profitability in real-world banking. Haenlein, Michael, Kaplan, Andreas M. & Beeser, Anemone J. (2007) A Model to Determine Customer Lifetime Value in a Retail Banking Context. European Management Journal, 25 (3), 221-234. Kotler, Philip. (1974) Marketing during periods of shortage, Journal of Marketing 38 (3) pp. 20–29. Krakhmal, Vira. (2008) Customer Profitability Accounting: A Constructive Case Study from the Hotel Industry. CAUTHE 2008 Conference. . Available from: http://www. griffith. edu. au/conference/cauthe2008/refereed-papers/RP023. df . Noone, Breffni & Griffin, Peter. (1999) Managing the long-term profit yield from market segments in a hotel environment: a case study on the implementation of customer profitability analysis. International Journal of Hospitality Management, 18 (2), 111-128. PricewaterhouseCoopers. (2009) Customer and product profitability analysis – Creating new insights to improve company performance. van Raaij, Erik M. , Vernooij, Maarten J. A. & van Triest, Sander. (2003) The implementation of customer profitability analysis: A case study. Industrial Marketing Management, 32 (7), 573-583. Ini