Business Intelligence Making Headway in Banks’ Profitability Efforts

Imagine being able to look at all the data on your customers across your organization to determine the best ways to increase the profitability and loyalty of those clients. Nothing new there -- banks have been doing this in some form for years. It's called CRM, right?

Not quite. Although customer relationship management and the technologies that have grown around it provide banks with some value around data interpretation, the future of analytics lies in business intelligence (BI).

Though the two may be linked, experts say, it is important to understand the distinctions between the two concepts. "CRM is the process of managing information and contact with clients," explains Raymond Dury, CIO with Cincinnati-based Fifth Third Bank ($104.6 billion in assets). "It gives you continuity and history of the contact. That's not BI."

"CRM was about getting information to enhance your customer relationships," adds Jeanne Edwards, a partner with KPMG in Charlotte, N.C. "BI brings in the operational and performance information -- it synthesizes the two to allow for dynamic reporting. It's the move from reactive information to more proactive, predictive data to make more insightful, dynamic decisions. BI is not static data."

Tim Ramsey, an Atlanta-based director in the financial services advisory practice with KPMG agrees, adding, "CRM was originally engineered to do this but ended up being an automation of processes. BI is really around how clean your data is and how well you can extract value from it."

Therefore, when thinking of BI, it is important to look at it in a broader sense than simply the analysis of data. "CRM is one aspect of business intelligence," says Thomas Sanzone, CIO of Credit Suisse (Zurich/New York; US$1.17 trillion in total assets). "BI is looking at a broad spectrum of data around our business -- clients being one dimension, markets being another, transactions another -- to make better decisions going forward."

Action Figures

Part of the problem with CRM on its own is that it produces data but often leaves people wondering what to do with it. The idea behind BI is to change data into something people can use, according to Gary Greenwald, head of global capabilities and information products with New York-based Citigroup Corporate and Investment Banking. "The challenge is turning the data into actionable information," he says.

And by making this actionable information meaningful through BI initiatives, banks can improve their performance, say the experts. According to Ellen Joyner, global financial services marketing manager with SAS (Cary, N.C.), banks increasingly wish to broaden their BI capabilities so that information can be accessed by almost anyone in the organization, beyond the "power users."

Financial institutions should embed this actionable data into the day-to-day work processes of banks' end users, asserts Cindy von Hollen, banking industry principal with SAP (Walldorf, Germany). "What BI boils down to is inline analytics -- incorporating analytics and BI into the natural workflow of the bank," she comments.

Data Scrubbing

Of course, before they can do anything with it, banks need to find, aggregate and cleanse the data. This is no easy feat given the vast amounts of information financial institutions gather enterprisewide.

"Many banks still haven't gotten together consolidated data even at the household level," says SAS' Joyner. "You have to gather the data and clean it up first. Most of the time in getting a BI initiative under way is spent in the data management area."

According to Citigroup's ($1.88 trillion in total assets) Greenwald, his global treasury services group got that message. "The concordance issue -- bringing together all the disparate data streams about our clients -- was important," he explains. This was a complicated challenge, Greenwald says, considering that much of Citigroup's clientele on the treasury management side tends to be large, multinational firms. Since they have operations in many countries, Citigroup debates whether to look at them as one client or as several.

"We're trying to make sense of the structure of our corporate relationships," Greenwald relates. "We wanted a single identity number for a corporate that was universal throughout the bank."

To do this, Greenwald continues, particular attention needs to be given to the quality of existing data. "We have lots of tools that produce data. But whether that turns into actionable data remains to be seen," he says, noting that data flows through an Oracle (Redwood Shores, Calif.) data warehouse. "We are becoming more nuanced in terms of which data is valuable and usable. It's getting it to the point where if we give the data to someone, it's information that's meaningful to the end user's goals." Greenwald adds that Citigroup partners with SAS for some projects while developing others in-house.

One way of making information meaningful is by employing BI tools to drill down into the data. According to Credit Suisse's Sanzone, the bank is moving toward a more client-centric model. Using mostly in-house know-how, he says, Credit Suisse is employing BI like a fine-tooth comb in its customer segmentation efforts.

"For example, in our private bank clients are segmented by their net assets," he explains. "Today we're making much finer segmentations of these clients in our business. So if you have clients that are both worth $3 million, you need to realize there's a distinction between someone worth that much who's 30 versus 60 years old. Their investment profile is very different; the way you sell to them and address their needs is very different. Being able to look at clients and data at a finer level really provides opportunities to drive the business."

Sanzone stresses, however, that successful use of BI may require data that a bank might not necessarily have. "You have to know what data you're missing so you can capture it, analyze it and deliver results," he says. "Some of it might be somewhere in the organization or you have to purchase it or just derive the missing data yourself. That's the difference between success and failure."

Fifth Third's Dury agrees, saying that much of BI is simply about gathering the appropriate raw data in the first place. "We do have a data warehouse," he says. "But for specific things where we don't have the data, we will pull it from data suppliers or create a data history based on what we do have.

The bank's methods typically are homegrown, Dury notes. However, it does employ tools from Business Objects (San Jose, Calif.) "to show striations in the data -- how old is the client relationship, what is their profitability, where is our break-even," he adds. "This is the normal, repeatable analysis that we need on a regular basis."

In Good Hands

Of course, actionable data is only valuable when it is put in the hands of the right people. Dashboards, applications that show data about the business in real time or near real time, are increasing in popularity as a means to push information to managers and staff. "The dashboard-cockpit metaphor works well," Credit Suisse's Sanzone says, adding that there is real value in dashboards, especially as global banks expand their reach and product complexity.

"It's important as we run a complex global business that we build these dashboards and efficiently manage the business. It's knowing out of all the thousands of things going on at any one time where we need to focus our attention," Sanzone explains. "You've got to deliver the information, particularly the exception information, that really warrants the attention of the necessary people."

But sometimes getting information into the hands of the necessary people can be a challenge, notes KPMG's Ramsey. "You can't really push BI tools on a teller platform because they aren't designed for that," he explains. "You have to create a new layer to get this real-time, actionable data delivered to the front lines. That will be the next step in BI."

After all, the end goal of BI is to improve the ability of bank employees to make better decisions that ultimately will lead to better performance, profitability and customer loyalty. And much of the information BI delivers is designed to create customer stickiness, observes David O'Connell, a senior analyst with Wellesley, Mass.-based Nucleus Research. "BI should be geared a little more toward the customer service rep who faces the customers so that they'll know everything about that customer and what they might be most likely to buy next," he says.

Moultrie, Ga.-based Ameris Bank ($2.1 billion in assets) employs technology from Banker's Dashboard (Stockbridge, Ga.) to disseminate information to front lines. "This is the tool we use to push results down to each branch -- the branch officers and staff members," explains Dennis Zember, the bank's executive vice president and CFO. "It helps us compare how our salespeople are doing at each branch. Before [implementing the tool], it was hard to provide meaningful information."

One area in which Ameris has leveraged Banker's Dashboard is the collection of loan fees, which account for a large portion of the bank's monthly income, according to Zember. "About a year and a half ago, we collected about $300,000 a month in loan fees," he relates. "Then we started holding people accountable to the information that was on Banker's Dashboard as to who was more productive. These loan fees have doubled to about $600,000."

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