Armed with this knowledge, the bank representative validates the customer’s identity and suggests a new credit card, this one with travel rewards. The result is positive all around. The customer is happy the bank is so attuned to her needs, and the bank has given the customer one more reason to be loyal and expand her business in the future.
While a handful of banks might have the ability to replicate that scenario, the reality is that the banking industry has been slow to adapt to changing expectations and new ways of serving customers.
That’s in contrast to industries such as retail and travel, which are leading the way in customized marketing, loyalty programs and real-time offers. These industries are also exploring ways to monetize customer data.
Clearly, banks aren’t clothing or hotel chains and it’s challenging to figure out how to leverage the volumes of customer data they have while also working through regulatory, privacy, security and reputational issues. They need to be careful not to spark a backlash or incur expensive fines.
Banks know more than they think
While they have to be sensitive to these issues, banks shouldn’t lose sight of their advantages. They have a much fuller view of customer spending than individual retailers, who know what the customer purchased from them but not what the customer bought from others. They also have a vast trove of transactional information that spans product and service providers. They know how much their customers are spending and saving; what they are saving for, investing in, or purchasing; and the circumstances (paychecks, bonuses, seasonality) that might be driving their investments, savings and spending. This empowers banks to identify trends and patterns, target groups and micro-groups with common profiles, and personalize their products, services, marketing and customer service to their customers.
Some banks and service providers are also overlaying the bank data with information at the SKU (stock-keeping unit) level, enabling them to analyze and predict specific customer preferences and behavior.
While most banks are not yet collecting or fully exploiting the available data, it is essential in helping them become more customer-centric and to help detect fraud, among other purposes.
For example, a customer may frequent the same businesses, such as dry cleaners, grocery stores or gas stations, while doing errands on the weekend. But what if the routine changes and a series of small purchases is followed by a very large purchase, which can be an indication of criminal activity?
One possibility is that the customer’s credit or debit card is being used without his knowledge. But a long-term view of the customer’s behavior tells a different story. For the past five years, this particular customer has bought a lot of high-end clothing, typically in mid-August and early spring. The large transaction in August that was flagged as possible fraud now has another explanation – the customer is buying back-to-school clothes for his family and new work clothes for himself.
With this information, the bank doesn’t have to take action to protect the customer and itself, the shopping spree can continue as planned and the customer won’t be inconvenienced in any way.
[Register for Interop here and check out the “Navigating the Big Spectrum of Big Data’s Solutions” session on October 4 in NYC.]
Use, don’t just collect, data
While that appears to be a simple scenario and one that many banks could achieve, the reality is that very few banks have mastered the tools to be fully customer-centric. They may have a lot of data about customers but very few have become proficient at using it. Many also lack the necessary technology.
To be more customer-centric and fully exploit data, banks must have a comprehensive customer database. Among other uses, the database will allow them to spot trends, identify cohorts, and micro-target discrete populations.
A customer-centric bank also needs advanced mobile, NFC (near-field communications) and real-time capabilities; these are areas where today’s banks are behind the curve. Customer targeting capabilities are key. A truly customer-centric bank would know which customers would be likely to be interested in certain products, the best time of day to approach them and the best channel to use. They would also be able to monitor customers’ behavior through geo-location. A customer using an ATM at a mall, for example, might receive immediate percentage-off offers from stores or restaurants there.
A customer-centric bank might also find ways to use its data and other capabilities to benefit its individual and commercial customers at the same time. In one possible scenario, a bank might offer individual customers discounted movie tickets from a theater chain that is also a customer. In addition to the credit card fees, the bank could receive a referral fee (regulations permitting, of course).
A bank might also create referral relationships among professional services customers, such as attorneys, and prospective homebuyers. The bank’s representative could ask the customer if he or she has an attorney to assist with the upcoming real estate transaction. If the customer says no, the bank could recommend one from among its attorney customers. The bank would vet the attorneys and also explore in advance any liability issues. Bringing together customers in this way could be beneficial to all parties and help position the bank as a proactive partner to multiple customer segments.
Part 2 of this article will address how banks can understand the value of customer networks, and the technology required to achieve a truly customer-centric model.
Eric Stine is SVP and general manager of financial services for SAP