Data, Data Everywhere…Where Do Banks Start?

The late CBS News correspondent, Charles Kuralt, was famous for his “On the Road” segments as he crossed the country to report “America’s people and their doings.” In the process, he wore out six motor homes in search of stories.

In my role as a product innovator, I focus on the cash management needs of companies and in particular the receivables products offered by banks. Although not as tireless as Kuralt, my recent assignment allowed me to interact with almost all of the top 40 banks and more than a hundred companies to better understand their current data challenges. While not all of my findings are surprising, they pinpoint what is impacting the financial services industry.

“We Need Help”

In a recent focus group with a dozen accounts receivables managers, the lament was made clear. They described the daily pain of finding and applying invoice details for payments, and the struggles they’re experiencing as B2B payments shift from paper to electronics, especially ACH. In another conversation, one executive from a top five bank said, “The ability to put data to productive use is worth $.03 to $.04 in earnings per share (i.e.: $50-60M) if only applied against tying together customer behaviors across major bank verticals to identify fraud.”

This captures the challenges that span the complete spectrum of data handled by banks: Completely unstructured and random transaction data, to the highly normalized data from analytic engines. The volume and types of data that banks must deal with are quite diverse.

The net-net: There are serious data challenges and opportunities for banks.

“Collecting Data Isn’t New. Applying It Is.”

It may take the sting of losing a major client to an aggressive competitor for a bank to realize it needs to make a change in how they approach data. As one bank product manager related, “We lost a major house account that was with the bank for decades because we could not meet their data needs to better manage their receivables.”

Deloitte Consulting, in an article by Omer Sohail, pointed out, "Banks always have had a lot of data and they collect a lot of data. The issue has been not leveraging all this data. More than 70 percent feel they're not leveraging the data to the best of their ability."

Surveyed bankers are less than thrilled with the state of analytics technology in their companies.

“About 16 percent said their analytics tools were "rudimentary" (meaning, spreadsheets and basic reporting tools); the majority (50 percent) said they had basic reporting tools with limited predictive analytics. Only 6 percent said they have the highest level of technology, including reporting and predictive tools, plus tools for analyzing unstructured data, with prescriptive triggers and alerts. A third (30 percent) of the bankers said their organization doesn't even use analytics in its strategy because it lacks proper technology and infrastructure.”

It would appear from the study results the journey to harness Big Data has a long road in front of it for most banks.

The Vexing Conundrum

Herein lies the fundamental challenge of big data for banks: Customer versus internal focus.

Is the challenge tilted in favor of one versus the other? How do you fund both the transaction needs of customers and the analytic needs of the bank? Banks are strapped for discretionary R&D funding for new customer-facing products as they address imposed regulatory compliance issues. In the process, little is left for the customer in the way of new products that address their fundamental needs.

The conundrum is addressable if an overarching framework is applied. The two end needs must be complimentary and not compete in order to succeed. As banks begin to develop a strategy to make sense of their vast amounts of data through analytics and new products, the starting point needs to be holistic. By incorporating the customer’s fundamental need for transaction services, which feed both the bank’s and customer’s needs for improved analytic insights – including fraud protection, payment trends or improved cash management tools – banks can begin to bring order to data. These guiding principles for success should be considered as banks construct their data strategies without spending a fortune. Any new data strategy must include both needs in order to secure funding.

Over the course of 24 months, and having accumulated hundreds of thousands of air miles, I’ve learned new cash management information products present a significant challenge to banks. They are awash in data, yet have not been able to aggregate, normalize and synthesize it for new product development.

In the next article, “Big Banks and Receivables Mass Data,” I’ll address the necessary steps to harness big data. And guess what? I won’t tell you to invest in a pricey big data solution.

Lawrence F. Buettner is a senior vice president at Wausau Financial Systems, which provides receivables technology for financial institutions. He has 30 year of experience in financial treasury management, and was an SVP at First Chicago.