Information management strategy lags the development of technology in most industries, and banking is no exception. We have seen the march of progress towards customer intelligence from initial customer identity management in the late 1980s through consolidated customer position snapshots (Customer Information Files or CIFs), retail velocity metrics (recency, frequency monetary or RFM), customer value | profitability metrics, to monitoring customer behaviour.
Many of these techniques were adapted from consumer retail product marketing, particularly packaged goods and telecommunications, rather than retail banking. The result has been success mixed with unfruitful investment because the technology was pushing ahead of industry management thinking. Examples of technology-push in banking are not hard to find: investments in ERP, SCM, and the CRM boom stand out in recent history.
One of the later entrants on the scene has been Transaction Trigger Analytics. First championed by banks in Australia (notably NAB,) it was discovered that parsing through transaction files overnight could result in identification of significant changes in customer accounts which, when acted on within 24 hours, could change customer behaviour. By detecting a significant deposit, for example, the bank could contact the customer to ensure all is well and offer any new services that the customer might require, such as investment advice. This technique is used primarily to keep new money in the bank or to keep old money from leaving.
Their experience proved the business case for transaction trigger detection convincingly - ROI was very high. At the same time regulatory pressure to sift through transactions looking for money laundering events made daily transaction analysis a necessity.
The only problem is that transaction files do not represent customer behaviour very well. They reflect accounts changes, but from a company perspective (or more accurately an account management system perspective) which we believe is quite different than the customer perspective. Customer behaviour can be far more complex than what shows in a transaction file. For example, a significant deposit transaction could arise from a tax refund; sale of a property or business; transfer of an investment account; liquidation of investments; relocation of an account between locations and so on.
Research has discovered that over 1/4 of banking balance changes result from internal flows of money within a customer's existing relationship (see article in Banking Strategies). This means that the transaction triggers will be false positives nearly half the time. Why ? because for every significant internal "plus" there is a corresponding "minus" so each side of an internal transaction appears to be a signirficant transaction event trigger. Transaction triggers can generate false leads about half of the time, draining staff time, program credibility and, worst of all, annoying customers with pointless dialogue.
Bankers need to define customer behaviours in the context of their business relationships. Know what customers really do and model these customer behavioural events, then apply detection mechanisms to find and route real customer behaviour changes to your customer service staff. Better quality leads to improvements in efficiency, effectiveness and satisfaction for customers, employees and shareholders simultaneously.
- David B. McNab
PS Best of the new year to all.
