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In Memoriam Retail Bank Loyalty: Divorce, churn and HANA.

There was once a great quote about people being more likely to get divorced than change banks.  Execs at retail banks loved this quote as they saw it as a reflection of their stellar relationships with customers. Consumers, on the other hand, knew that it was the pain of changing banks that created inertia, rather than any warm, sticky feeling of loyalty for a particular bank.   But things change and we can see a bizarre coincidental parallel between trends in divorce and in retail bank churn which should make banking exes a little less fond of this quote.

Divorce rates are high in the Western World, but it hasn’t always been so.  Up until the mid 20th Century a combination of social, financial and process complexity factors actively deterred divorce. Sure, there are case studies where individuals declared that they could exercise the divine right of Kings’ and secure a divorce, but this was the exception.

Today,  each one of these factors had been countered resulting in higher rates of divorce and,  in a strange parallel, social, financial  and process changes have also reshaped theworld of banking customer churn.

Let’s think of social stigma as “creditworthiness”.  When my father applied for his home loan in 1950 conversation with the bank manager started with “I’ve been your customer for 30 years…”  In those days changing banks inferred that you were not a good bet. Now independent agencies monitor creditworthiness and duration of custom counts for nothing.

The practical process of leaving a bank has also been simplified, as a result of regulatory pressure and the onus in now on banks to do all of hard work.

Financially, staying with the same bank yields few benefits.  If we look at what banks term “linked-account” offers for existing customers, few have market leading rates.  No, best buy rates are reserved for  the disloyal, the  so called “rate tarts”. Similarly, the argument for keeping all of your savings in one place for security has obvious risks in the light of the collapse of Northern Rock, Landsbanki etc.


So, its bad news on both fronts: Divorce rates are up and there are few reasons for customers to remain loyal to their bank.  Retail bank execs can no longer use the divorce analogy and the only platitude left in their Bag of Management Wisdom is the one about gaining a new customer being X times more expensive than retaining an existing one. This isn’t a great message to take to the board. So, what’s a retail banking exec to do to retain their corner office? 

The exec sees two options:  The easy option is to focus on new customers and hope that the board believes that “churn is inevitable in today’s banking world” and that nobody really looks at cost to asset ratios when valuing a bank.

The more difficult option is to work to retain customers. To do this the bank will need to analyse both macro factors such as best buy rates and fee levels as well as customer-specific factors, such as customer experience, but not in the way it does now.   An annual Voice of the Customer survey and reviewing competitors’ rates as part of the product development cycle are not timely enough to impact on loyalty.  Banks need to track leading indicators of churn. When we consider that a good sized retail bank, such as HSBC, has around 89m customers, keeping an eye on customers offers a significant challenge.  

From a technical perspective getting insight about churn propensity relies on high frequency analysis of big data, held in multiple systems.  This sounds like the perfect use case for an In Memory database.

By moving to an In Memory approach retail banks can monitor customer behaviour and experience across core banking applications, CRM applications and even communications channels to identify patterns that indicate an increased churn propensity.  What banks do from this point depends on their customer strategy,  but could involve assigning a personal advisor to assure that any glitches in  the customer’s experience are visibly rectified, or even offering premium products to encourage retention. 

In summary, we know that churn now has little down side for customer but that the technology exists to enable banks to track and intervene when churn risk increases.  The key question then shifts away from insight (I know that your thinking of leaving me), towards action (what can I do to stop you from leaving?)  Perhaps this second question is too difficult for banks to address? Perhaps, in contrast with other B2C industries that have ploughed fortunes into customer loyalty schemes, banks just think the grass is greener on the other side of the fence, finding  new customer far more attractive than existing customers? They love showering rate tarts with never ending cycles of loss leading, best buy products to tempt them to engage in a momentary dalliance before the tarts flit off  to the next best buy. At this point we need to categorically point out that the divorce analogy ended in paragraph four, though perhaps our banking exec could  hang on to their corner office  a little longer if they took a little relationship counselling.

See SAP Business Transformations latests white paper on the impact of In Memory Computing on  Banking Analytics at:

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