If you run a payments business, the retail bank deposit base is a natural and appropriate place to look for cards prospects. Indeed, when credit risk issues come to the forefront as they have in the current economic environment, the bank’s customers tend to be a “safer” bet than de novo cards growth. So why don’t more banks do this effectively?
It is self-evident that banks thrive when both side of the balance sheet are healthy. Yet there is an invisible entry on the asset side of the ledger that is a significant enabler of portfolio profitability but whose value often goes unrecognized by banks. This "invisible" asset? Data. The richest and most powerful data about customers is that underlying the payments business, and are assets in and of themselves.
Aligning and integrating customer needs with relevant products and services is critical, both for top line revenue growth, and for the bottom line. And this need for relevance extends well beyond cards and into the retail bank, including lending, insurance and investments, and deposits.
The head of the retail side of the business, on the other hand, has branches to run, home and auto loans to sell, training to conduct, incentives to pay and so on. Objectives for cards are not usually embedded in the retail bankers’ scorecards, and indeed may run counter to their objectives – particularly if products like personal loans reside on the retail side.
So what’s a payments leader to do? Continue to go hat-in-hand to the retail bank, asking for leads?
As a consumer, you are what you buy. Not only that, but you will be what you will buy.
Consumers who use plastic use it in a variety of ways, as evidenced by the many patterns of transaction recency, frequency and volume found in a bank’s datamart. And these patterns can be used to create highly useful segmentation schemes, defining customers in terms of their spending behavior and, through inference (using consumer personas, based on demographic information on household income, marital status, presence of children, home ownership, etc.), describing who they are and what they need.
But description of this nature is just the starting point. The sheer volume and velocity of data, specifically as it is captured and organized at the merchant category level, create remarkable levels of predictive power. Events such as changes in usage levels, account attrition (both explicit and silent), and even changes in purchasing behavior across categories can be modeled quite effectively, again enabling profit-driving treatments and interventions.
These higher order insights and predictions can enable cards issuers to help their retail bank colleagues by identifying customer needs that go beyond payments.
Trigger-based marketing is not new. However, taking the notion a step further, there are cognitive events that occur when consumers make purchases that not only manifest themselves in current transaction behavior, but may also reveal a future need.
An example :
In this case, the consumer’s preparation for the new school year, purchasing clothes and books for middle-school aged children, may trigger an underlying – even subconscious – thought about future education needs, including university. A bank with this transaction-driven intelligence can respond to a need consumers may not even have consciously identified for themselves.
As described in the example, the meta event now becomes the basis for a discussion with an entirely different frame. The use of the transaction data to describe customer segments and predict their future needs, becomes the basis for marketing across the retail bank.
In this scenario, no longer does the cards business plead for access to the deposit base, but comes to the table with more leverage and prepared for a very real exchange of value. And this for the benefit of the entire organization.
The Author is working as the senior vice president and region head of Asia/Pacific, Middle East and Africa MasterCard Advisors
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