• Philipp Annasohn
  • Published: 31 May 2019

For decades banks have tried to broaden and deepen their client relationships. In some areas, such as building a product universe that can satisfy clients’ investment needs, these efforts have succeeded. Other areas, such as using data-backed insights, have not been adopted across the board. However, this is a cost effective and highly beneficial approach that best-in-class institutions have started to pursue. In this article, we share how banks can turn their data into valuable insights.

Sales organizations can use the concept of ‘Client Lifetime Value’ (CLV) to quantify the profit drivers of the bank’s client relationships. Adapted for the banking industry, the simplest form of CLV can be noted as:

CLV = business volume x time with firm x profit margin

Product costs aside and assuming positive product margins, any increase in business volume and retention time increases CLV. Hence, two simple drivers are left. Ideally, there would be an industry concept that addressed both drivers in the same direction, i.e. by any development action, clients would be inclined to both increase the intensity they bank with a firm and become more loyal.

Luckily, there is such a concept that withstands empirical testing:

The main / secondary bank concept. It says that people with several bank relationships usually see one of their banks as their ‘main’ bank. ‘Main bank’ studies conducted can be summarized as follows:

i) Main bank clients are more loyal (i.e. less likely to switch banks)
ii) The clients’ loyalty is not ‘bought’ with special conditions
iii) Main bank relationships grow quicker than secondary bank relationships

These findings tie in with the CLV model above by addressing both drivers of CLV we identified as levers of sales organizations: business volume and retention time.

However, two questions remain:

1. Is the main / secondary bank ‘concept’ still applicable today, or has something fundamentally changed in this post-Lehman Brothers era?

2. Can the differences in profitability between secondary and main bank relationships be calculated and are differences significant enough that it is worthwhile for banks to use ‘main bank clients’ as a design target?

After having conducted a real-life analysis, both questions can clearly be answered with YES.

Quantification of benefits of main bank relationships

As mentioned, the idea that main bank clients are interesting profitability wise has been out there for years. However, one problem for banks was that there is no consensus what a main bank relationship constitutes. Views differ internally between segment managers, product managers and relationship managers. To avoid confirmation bias, we conducted an analysis based on clients’ self-identification as being a secondary or main bank client.

When clients’ yearly revenues were compared for both groups (separately for different client segments), the extent of the difference in revenues between main and secondary bank client relationships was surprising: Net present values over five years were in the region of $10,000 for a mass affluent customer, $30,000 for core affluent / high net worth customers.

The key question following this promising initial assessment for banks is: Are there patterns or common factors in main and secondary bank clients that can be managed / addressed by a central sales organization or are differences fully individual between clients? Our analysis showed that there are indeed such factors and that the differences between main bank clients and secondary bank clients we found are surprisingly simple:

In other terms, banks that succeed in winning clients to source these few products from them benefit significantly. Banks can therefore promote these products and convince clients to show the behavior identified as ‘crucial’. The incentive used by banks goes far beyond the individual prices of these products. In some extreme cases, a bank could offer these products for free and still benefit financially.




Andrea Hoffmann

Partner, Capco Switzerland
Email: andrea.hoffmann@capco.com


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Loyalty programs at banks fail to produce loyal customers. The main reason for this is that banks rely on simplistic loyalty mechanisms based on human knowledge, while leaders in the field, such as Netflix and Amazon, use data and recommendation engines. In this paper, we share a proven customer segmentation and analysis model, which demonstrates a simple and effective approach to data-driven customer development and enhanced revenues.