Banks Set Stage For Customer Acquisition With Data Analytics
As the banking industry and wider economy emerge from the financial crisis, banks have been able to start shifting their focus from controlling the damage to actually growing their business. With customers starting to spend more, look for loans and weigh their financial options, banks are accelerating their moves to a customer-centric (rather than the traditional product- or channel-centric) model to both attract and retain new customers. But customer-centricity requires banks to truly understand their customers, and despite years of investment and effort most banks still can’t analyze data at the scale and speed to do that, says Rani Goel, senior director of analytics product marketing for SAP.
“There’s a lot more focus on data now. There’s more sophisticated analytics tools, and there’s so much more unstructured data than ever before. The problem is that banks’ legacy systems can’t handle all that unstructured data,” Goel explains.
Fewer than half (46%) of banks can analyze external data about customers, according to a survey of 100 banking executives SAP conducted last year in partnership with Bloomberg. Even fewer of those surveyed could analyze social media activity (32%) or their share of a customer’s wallet (29%), according to the study.
[For More on Data and Analytics: Big Data:Where to Begin?]
The most common challenges cited by the respondents to achieving customer-centricity were data and analytics capabilities: 40% said that volume of data was a key obstacle, and 37% said the same about the complexity of analytics tools.
The respondents were confident in the value of emerging technologies to help them understand their data and achieve their organizations’ goals, Goel notes. More than half of the respondents said that technologies such as cloud (62%), predictive analytics (59%) and real-time data processing (55%) will be extremely valuable to their strategic objectives in the next two years.
But before banks can start leveraging these emerging technologies and their value, they have to build a foundation for data management and improving data quality, says Seth Rosensweig, managing director in AlixPartners’ information management services.
“I spoke at a conference last year about the Volcker Rule and pulling in data to the enterprise level for compliance. A lot of the questions from the audience were around technology, and what they could implement. I told everyone it’s not about technology yet. It’s about understanding your framework for data management,” he shares.
Banks need to be thinking about the hierarchies and taxonomies that they will use to identify and manage their data sets before they start to build the architecture for data and analytics to drive marketing and customer acquisition. Those that don’t track these issues and work through them before starting to layer new technologies on top of their existing infrastructure and will be at a disadvantage down the road, Rosensweig warns.
“Until banks can extract data from different systems and relate it to data throughout their organization, the true benefits of big data will remain elusive for them,” Teresa Epperson, a managing director at AlixPartners, agrees.
Mastering Data Management
Certain banks are farther along than others in being able to drive customer acquisition through data and analytics, and those institutions have started to master their own data management, says Chandan Sharma, global managing director of financial services marketing for Verizon Enterprise Solutions.
“They’ve elevated data management to a high-level… they also recognize the importance of creating these functions around data management in the right place within their organization,” he observes. “It’s then easy to have a cross-enterprise view of the customer.”
Sioux Falls, N.D.-based Great Western Bank ($9 billion in assets) is one example of an institution that has done extensive work around data management, and is now using that work as a stage to launch new customer acquisition and marketing initiatives.
“Our biggest challenge in using data and analytics for marketing and customer acquisition has been data quality, making sure that the codes are there for different documents and records,” says Ron Van Zanten, the bank’s vice president of data quality.
To address this issue the bank created a data committee with members from different teams across the organization, Van Zanten shares. The committee, which reports up into Great Western’s business intelligence operations council, created standard definitions that teams across the organization now use for different tiers, pricing and terms on accounts. Those definitions are now standardized across Great Western’s various systems, Van Zanten reports.
That data quality work has served to gain buy-in from employees across the organization by building trust in the bank’s data, Van Zanten adds. “If you have people in your organization who look at a report, and they say, ‘My loan numbers don’t match up,’ and that’s true, then it brings about doubt across the organization in what you’re doing,” he explains. “We can now validate our data, and the work that we’re doing with it.”
Gaining that buy-in across the organization isn’t always easy. Van Zanten’s team has been working to centralize Great Western’s data in its data warehouse. Sometimes parts of an organization can be reluctant to give up their data, he notes.
“We’ve taken the ‘source of truth’ from different silos and put it in our warehouse… some people have to give up the keys to their kingdoms. But this is now freeing up our staff to do new things, instead of producing the same old reports,” he remarks.
With this clean, well-defined data in hand, Great Western has started to cast a net for more profitable customers to help grow the bank. Great Western used to give away free checking to new customers in its branches, but now with the knowledge gained through its data management, the bank is working to entice customers who will have a more sticky relationship with the bank and buy value-add services, Van Zanten says.
About two months ago Great Western started purchasing demographic data from Experian to add to its own data and start to build profiles of what profitable customers look like and how to market to them, Van Zanten reports.
“We’ve built a new system so when a new customer opens an account we can see what similar customers like. If they open a debit card, we can offer things like direct deposit and push e-statements… and entice them to a more sticky relationship,” he adds.
The bank has also worked to better price its products for profitability by factoring in the cost of expenses on products into their price. “We can bake in the cost of funds transfers and operational costs, and take direct income and expenses on accounts, and then post those against savings and loans,” Van Zanten explains.
Great Western can now assign a numeric digit for onboarding a particular account, such as a consumer checking or a small business account, and fully understand the cost of servicing that account.
Predicting Customer Behavior
Another bank that has worked hard to organize and improve the management of its data is Fifth Third Bank ), based in Cincinnati ($125 billion in assets) In the summer of 2012 the bank began reorganizing and simplifying its consumer checking product suite.
“We had a large number of grandfathered [checking] products that we no longer offered, some as a result of acquisitions we had done. From June 2012 to the first quarter of 2013 we simplified the product suite down to five products,” recalls Mark Erhardt, the senior vice president of retail product management at Fifth Third Bank.
The bank also built relationship-based pricing into some of those new products, allowing customers to forgo fees for certain account activities or purchasing other Fifth Third products. During this process the bank quickly understood that it needed to get better at analytics to be more effective at product pricing, Erhardt says.
Fifth Third partnered with Nomis Solutions which provides an analytics-based product pricing engine, to help attract new customers. While in the process of simplifying its product suite, Fifth Third built a new customer records infrastructure and cleaned up customer data throughout the organization. That work, along with Fifth Third’s ability to easily extract data from its proprietary core system, helped the bank deliver better data for analysis when it started its partnership with Nomis.
“They had really good clean data, and that isn’t always the case with everyone,” Frank Rohde, Nomis’ CEO, remarks. “A lot of other banks really struggle to get that data out of their core.”
Fifth Third is now working on a new pricing initiative with Nomis across its auto finance, consumer deposit and home equity product lines. Using Nomis’ pricing engine the bank can run scenarios on how different price points will impact its customer acquisition and deposit levels, Erhardt says.
“If we want to get to a specific deposit level, Nomis can help us run a scenario to find the right price points for that growth. We can run an optimization for interest costs, and look for opportunities to reduce expenses in certain products, or in certain tiers or geographies,” Erhardt explains.
Fifth Third is running scenarios with Nomis’ technology to help it prepare for the rise in interest rates that everyone expects the Federal Reserve will enact at some point in the next few years. The bank can do assumptions based on where rates are headed and run a scenario in terms of where it wants to be with rates in the market to be aggressive in attracting customers, Erhardt shares.
“Deposit pricing has been a back-burner issue… but with changes in rates, plus new liquidity regulations, and also consumers’ ability to shop for products online, it’s going to be a front-burner issue again,” Erhardt predicts.
As rates rise and customers start to move their money for a better rate, banks will struggle to predict how their portfolios will be affected. Banks simply don’t have relevant data to analyze and understand how money will move, says Nomis’ Rohde. Data from the past few years doesn’t show any rise in interest rates. And data from 2004-2007, the last time interest rose, isn’t usable because customers didn’t have modern digital tools back then such as mobile banking, Rohde explains.
Nomis Solutions has developed a way to circumvent this lack of data for those institutions looking to take advantage of interest rate increases to improve acquisition. “We got a patent on a recalibrating methodology that can change based on how consumers are behaving right now. It allows us to quickly recalibrate models to take into account what’s happening in the market. When the data starts to indicate a trend, the institution can then forecast and react quickly,” Rohde explains.
With this capability to quickly react to the market, Fifth Third will be able to leverage interest rate changes to both drive growth and deepen customer relationships through better and more targeted pricing, Erhardt comments.
While Fifth Third and Great Western are using their improved data management and quality to target new customers, the framework they’ve built through centralizing and organizing their data will be applicable in other areas throughout their organization. “I think this ability to manage data effectively will be one of the most important differentiators in the industry,” Verizon’s Sharma says. The same principles around data management and infrastructure that apply in customer acquisition also apply in other areas like retention, risk management and compliance, he explains.
Jonathan Camhi has been an associate editor with Bank Systems & Technology since 2012. He previously worked as a freelance journalist in New York City covering politics, health and immigration, and has a master's degree from the City University of New York's Graduate School ... View Full Bio