Data is the new currency, at least according to industry experts like Ankit Maharaj Singh.

“Driving growth and profitability for any organization purely relies on how successfully you can strategize your product placement, and all of that is based on how much scrubbing and analysis and deep thought is placed on data,” says Singh, vice president at Quinte Financial Technologies, a New York City-based data analytics and process automation firm focused on converting data into useful intelligence for community banks.

In reality, banks have a lot of data on which to act, and if leveraged properly, that data can boost profits. According to a November 2020 report from Capgemini, a Paris-based tech firm, organizations that use data masterfully will see up to 22% higher profitability and 70% higher revenue per employee. In addition, 54% of banking business leaders agree that by activating data in their processes, they are able to create a sustained competitive advantage.

Data alone does not a strategy make. In fact, experts agree that data should be leveraged to support a strategy—whether it’s identifying and targeting a new market, seeking cross-selling opportunities or supporting another business objective—not define it.

“A lot of people skip to the end and expect the data to give the strategic answer,” says Greg Johnson, chief operating officer at Cortera, a Moody’s Analytics company in Boca Raton, Fla. “It’s not going to give you the strategic answer, you still have to have a strategy to lead you, but then you can use data to inform or predict the opportunity there.”

While strategically leveraged data does drive revenue—60% of bankers report monetizing data assets and insights through products and services, according to Capgemini—evaluating that data can be daunting. From multiple systems and data sets to the sheer wealth of information available, community banks may experience their own data freeze, or an inability to act on insights.

Here are three steps to harnessing the power of data to support customer experience and increase revenue at the same time.

1. Leverage internal assets in support of strategy. As a starting point, community banks can begin exploring specific components of their existing data to identify behaviors. For example, if the bank wants to grow its younger customer base, it can start by segmenting current customers who fall into a certain age range and then explore which products and services this group uses the most. That information can provide insights into potential cross-selling opportunities, as well as the products and services to lead with when marketing to new customers.

“Look inside and see what you have,” Johnson says. “A lot of the gold is sitting right there under your fingers. Don’t ever underestimate what can be found with some of the simplest of approaches.”

2. Complement internal data with external sources. Once a community bank becomes accustomed to using its own data, additional sources can be layered on. By augmenting internal data with outside behavioral or geographic information, community banks can get a better picture of their customers’ needs, deepen their banking relationships and offer personalized solutions. Kim Snyder, CEO and founder of KlariVis, a Roanoke, Va.-based data analytics software platform, says by doing this, community banks can take a page out of the playbook of large retailers.

“External data sources allow you to create that contextual intelligence,” Snyder says. “So, understanding where a user is when they are logging into mobile banking, and tying that in with the weather, and tying that in with their location; are they exercising or sitting on their couch?”

3. Explore enterprise-wide analysis. Community banks are often strapped with trying to cull data sources from disparate systems. If that data could be integrated and then evaluated as a whole, it would produce a deeper picture of clients and their activities. In short, this cross-functional data dive can help banks amplify the power of relationship banking.

“If I’m a lender and I have a commercial real estate customer, wouldn’t it be great to know by looking at [data] that they’ve also done a secondary market mortgage with us? Just to have a conversation with them so they know you know who they are,” Snyder says. “All of that goes toward developing your product strategy around the data that you have and around the customer segmentation that you’re trying to attract.”

As digital transformation continues, a customer’s data footprint will become increasingly important for community banks if they are to continue to deliver the personal service for which they are known. Much of the needed information exists within the banking environment today. The trick to expanding your profitability is to know how to tap into it.

“It’s very important for community banks to be more competitive from a data perspective,” Singh says. “How well we utilize data will define our future. Strategically, I think community banks can be way ahead of the competition.”

Source: This article was originally published in “Independent Banker” on August 01, 2021