Banks and other financiers could benefit from the use of big data in equipment leasing and financing, a new report claims, but is it worth it for community banks to invest in a big data program? And what is big data anyway?

Put simply, big data is basically data in the raw. “Big data” would be data sets so large they cannot really be processed using traditional software. Big data can come from websites, blogs, PDFs, videos or social media, and David O’Connell, a senior analyst at Aite Group, defines big data by three v’s: volume, velocity and variety.

“The reason it’s called big data is because there’s so much of it,” said Scott Thacker, CEO of Ivory Consulting Corp., a director of the Equipment Leasing and Finance Association.

The Equipment Leasing and Finance Foundation, the association’s nonprofit research arm, produced the study titled Big Data: A Study for the Equipment Finance Industry, which Thacker, as co-chair of the research committee, helped head up. The foundation specifically wanted to introduce the concept of “big data” to its membership, Thacker said.

“If you were a bank, you might want to know what people are saying about you on Facebook and Twitter and LinkedIn… You might be able to learn what your customers and potential customers are saying about their financing needs. They may have put that out on social media,” Thacker said. “One application would be to ask: ‘Who of my customer base is putting posts out onto social media sites and what are they saying about their financing needs?’”

More Loans

It’s not hard to understand why equipment financing is attractive to community banks these days. Commercial and industrial lending has been on the mend in recent years, as companies make up for equipment purchases they may have put off during the recession, and C&I loans offer a little more diversity in your loan portfolio.

Community banks made $171 billion worth of commercial and industrial loans during 2012, a 4.6 percent increase over the previous year, the FDIC reported. Further, C&I loans tend to have a lower charge-off rate, compared with total loans and leases – 0.32 percent versus 0.72 percent for all loans and leases.

But where, exactly, does big data fit into this?

“A big data program could give the community bank manager insights into the financing needs of their customer and potential customer base, where competitors are going and could help understand how a given community bank could potentially fit into the larger financing environment in terms of participating with other banks and different types of financing deals,” Thacker said.

According to the report, a big data program could also help a bank analyze consumer behavior and create new after-sales service offerings, among other suggestions.

Big Data, Big Commitment

 But for all its potential, big data is still a big commitment – particularly for community banks with limited resources and razor-thin margins.

“It’s definitely an expensive undertaking,” Thacker concedes. To do it well, smaller institutions typically partner with an outside third party, he said. And adopting a big data regime also means investing in new programs and skill sets, though Thacker believes that support from senior leadership is the most essential component.

O’Connell thinks that banks might be better served by focusing on more basic data analytics than by worrying about big data.

Community banks in particular could automate reporting, to free up human energy for actual banking, they could create better outbound marketing programs, and they could make use of predictive analytics.

“What ought to be on the roadmap is customer next best actions,” he added.

Customer next best actions is an analytics driven capability that can suggest a letter of credit or a wealth management service, or even a simple “Thank You,” for a given customer, based on a 360-degree view of that customer provided by the data already available to the bank, O’Connell explained. A similar principle could be applied to borrowers, too.

“I don’t think that community banks possess or interact with data at that scale. Even if they did, at this moment somehow, I would say that banks, in general, have far more small data headaches than they have big data opportunities,” he said. “If they can find a big data opportunity that has a higher ROI than combining and aggregating their existing data sets, then by all means do it. I don’t think it’s there.

Email: lalix@thewarrengroup.com