By Evan Sparks
While the banking industry as a whole has been reporting record profits for several quarters–at least in terms of dollar figures–since the financial crisis, more meaningful measures of bank profitability have remained depressed. Average return on equity has been hovering around only two-thirds of its pre-crisis level, and return on assets has been stagnant at around 1 percent. Net interest margin remains persistently depressed and net income is stagnant as well.“This is not the growth that I think many people were hoping for,” says Bryan Ridgway, a senior solutions engineer with software and consulting firm Kaufman Hall.
In light of these relatively low industry-wide performance numbers, it’s not surprising that survey research shows that nearly three-quarters of bankers say “profitability measurement is the number-one initiative within organizations,” explains Kaufman Hall VP Ken Levey. Meanwhile, as profitability becomes job number one for bank leaders, there are new tools and better data that allow bankers to do more to achieve it. “Institutions do see the importance of profitability analysis, but there’s a lot they can do to improve it,” says Levey.
The difference today, adds Ridgway? “Access to more data today than you ever had before.” The data are more granular, more relevant and of better quality. Sophisticated software allows managers to analyze results and look at multiple segments, regardless of what factors are going into the profitability analysis. Today, Ridgway says, profitability analysis helps drive decisions about product launches and features, branch openings and closings, cross-selling strategies and more.
For example, there’s “very limited value in a standard P&L statement,” Ridgway notes. What if there’s one account of one large profitable customer that’s driving profits and that account matures in three months? More sophisticated analysis that encompasses a greater range of data helps bankers make strategic choices about how to “get more of my customers down on this end to behave more like customers at that end,” he adds.
Levey offers five key practices for bankers to consider when implementing a profitability analysis program:
- Make profitability matter. “Let’s start with making the metrics easy to understand and reconcile,” Levey says, noting that they’re useless if people can’t understand them. “Change the culture of the organization: the profitability metrics you’re using for the organization should be the same you’re using to [pay]loan officers. . . . As we incent people, make sure their goals meet the goals of the organization.”
- Create a profitability steering committee within the organization. It starts with upper management making a cultural change. “Decide on the metrics you want to use to measure your organization,” he explains — then communicate and roll them out. “These are going to be very difficult meetings. You’re playing with people’s compensation.” Just a little over a quarter of bankers have a profitability steering committee, he added.
- Consider all elements of profitability. Net interest margin, net interest income/expense attribution, loan loss provisions, capital allocation, multi-dimensional reporting and analysis — everything relevant needs to be factored in.
- Establish a profitability roadmap. Banks doing this must define their end visions, Levey says — but be realistic about how far you can get along the path. “I think it’s important to start with a quick win,” he says. “Don’t get overwhelmed by trying to do too much.” He notes that using these tools is not a three-month process — but it could be a two to three-year process.
- The goal should not be perfection. Compare progress against a baseline, Levey says; ensure that metrics are consistent and defendable, and make sure everyone in the bank understands them.
Key Questions for Banks Developing a Profitability Analysis Strategy
What types of decisions will be made based on the analysis?
Who’s going to make those decisions and how will they be held accountable?
What information or metrics are needed? NIM, total profitability, ROE, RAROC, profitability grade, rankings, percentile groupings?
What calculations and methodologies are needed? Matched-term FTP, overhead cost allocation, product/unit costs, activity based costing, capital allocations, provision allocations?
What tools are needed? Excel, an already-owned tool, a new tool, a single platform versus separate tools, an owned versus an outsourced solution?
What data are needed? General ledger data, instrument level data, customer information files, statistical data, transaction data, channel data, demographic data, credit data?
