July 12, 2013

The balance between technology and humanity is finally reaching equilibrium, thanks to data analysis. For decades, bankers have persuaded customers to use self-service channels. Now that people are banking online and through mobile channels, and accessing their cash from convenient stores and ATMs, there is a personal information gap that needs to be filled. The lack of personal interaction that gives e-banking its cost advantage and saves customers time can also be a detriment to cross-sale and marketing opportunities.

As an industry we have successfully minimized the situations that return sales and marketing insights, such as teller-customer conversations during deposits. Instead, we offer fast, efficient means of banking that have been widely adopted, now budgeting a couple minutes for tasks that once took five times that. While the benefits of self-service advancements are necessary to be competitive, and are for the greater good of the industry, we must not forget the need for those intersections of opportunity to derive a wealth of knowledge from the most fleeting amount of time. Data analysis can meet this need.

The pairing of big data and small data can detect when and how consumer behavior changes, alerting banks for both everyday opportunities and the major moments that only come a few times in a customer’s lifetime. There is more information available from online and mobile banking customers than one might think. We are habitual by nature, like it or not. So when normal banking behaviors change in the slightest, then it will typically serve the bank well to look into why there has been that change. Tapping into this data is not hard, but does require a complete shift for bank personnel and the management of e-banking channels. The two entities must work closely together.

Today most banks have informative sites and a “contact us” form. Until they can get a sense of what customers are really doing online, banks’ Web presence amounts to little more than an advertising pamphlet. Even for banks that may review their analytics – at month’s end – to see that 14 people clicked through to their home equity loan page, what does that really amount to by then? Probably not new loans.

We have educated consumers to seek self-service tools, and they are inclined to check rates and research before making any big life decisions. The first place they will likely look is their primary financial institution, and banks have a chance to gain more market share at that very moment. After that moment passes, it is off to Google to search for additional offers. Most consumers are not confident in the best rate, for example, until they talk to someone.

Since we’ve dwindled physical service channels, the current customer does not want to call his or her bank to request information. That would risk 15 minutes on hold, or a plethora of tedious automated responses. Instead banks should have the data that their customer has looked at mortgage rates, stopped logging into bill pay or clicked on an ad. From there it is up to the bank to respond to that change and provide assistance. Even educated consumers can benefit from some personal financial guidance. Maybe paying off a credit card bill can help lower their APR, or perhaps waiting three more months to accrue additional savings is all they need to forego an additional PMI fee.

Banks are still service organizations; it takes human intervention to get results. Big data promises to connect these self-service inquiries to a service environment that closes deals. With it we can recognize these changes in a virtual environment and react accordingly. It is no different than traditional bank personnel’s training to react on their in-branch observations.

Big data identifies the insights that were previously only available in branches. It’s a sales funnel that picks up on trend lines to replace the personal interaction we’ve lost. The next step is to make sure branch personnel know how to -- and are willing -- to leverage the information.

Human interaction must be ported over to the digital channel, and the use of big data is the essence of our transition to true omnichannel banking. If you could have a conversation with anyone that showed interest with any of your products, what would you do with that? The successful banks will have managed leads as leads, regardless from where they originate. Consumers need to trust their bank as a single, unified brand rather than as having different channels as part of a brand. At the same time, the institution needs to leverage a single view of the customer by eliminating the siloed functions of those channels.

There is a natural demographic maturation of consumers’ needs for different banking services, and big data provides accurate self-segmentation due to their behavioral changes. You can better identify the individuals who are actually in the market to buy, and know when to follow up with them. Collecting data over and over, time after time, to detect patterns and find anomalies creates unrealized gains for the bank; however, to capitalize on it, you must know where to look for it and what to do with it. We do have the power to end the interaction v. self-service contradiction, and move between those cross-sections of opportunity freely and without hesitation. Just step on the gas and go.

Wade Arnold is the CEO of Banno, which provides a data-enrichment and interpretation platform for financial services providers.