If the Yanny vs. Laurel controversy reinforces anything, it is we all have our perception of reality and trying to explain that reality takes some effort. Those lessons are the same ones we are learning about the role that clear metrics play in bank performance. State several performance metrics and everyone will not only have a different reality of what success means but will have difficulty explaining their differences. In this article, we highlight some important bank metrics and discuss the construction of what a powerful set of bank benchmarks could look like.
Perception and Clarity
If you are looking to improve performance, one idea that we have found helps is to improve the benchmark metrics and your use of those metrics to achieve superior bank performance. Vague metrics result in vague results and metrics that don’t correlate to success likely result in your bank not achieving success.
We bring this up as we participated in an industry association bank roundtable last year when senior managers presented their metrics for 2017 that included items like:
Bank A: “Be in the top 25% of peer group performance.”
Bank B: “Grow loans by 11%.”
Bank C: “Maintain a 3% net interest margin.”
Bank D: “Keep the cost of funds below 1%.”
Bank E: “Achieve a 15% ROE.”
Last week we checked with each of these banks, and we found two things interesting and scary – all were underperformers for 2017 and worse, all rationalized their performance away with many considering themselves a success.
Nothing could be worse for our industry – a bad process paired with bad perception and no accountability.
Writing Clear and Concise Benchmarks
For starters, good benchmarks start with a clear idea of what you are trying to achieve. If your bank has a benchmark to “improve customer service,” you will likely fail. To effectively manage to a benchmark, you need a starting point, a goal and a time period. In this manner, all can be clear on what needs to be achieved. Below is the formula that has proven effective for us:
While financial metrics such as efficiency and return on equity are easy, bankers need to get creative on things like customer satisfaction, community involvement and similar. Customer satisfaction, for instance, can be benchmarked and tracked with an annual survey, with a sampling done by a third-party or by referrals. Whatever the case, bankers need to come up with a suitable proxy metric for their goal and then figure out a clear starting and endpoint.
Have The Right Goals
Bank A did achieve their goal of being in the top 25% of peers, but it should be noted that only the top 10% of peers performed above the industry average. Bank A, unfortunately, despite making their goal, still achieved a below average return when compared to the industry.
Bank B also achieved their goal of growing loans by 13%. Unfortunately, as we have written about before (HERE), loan growth is tricky to drive performance as this bank proved. To produce current year profit in loan growth, you have to have your timing, risk, origination costs and structure right. Like in Bank B’s case, loan growth sometimes results in lower, not higher current year income.
Bank C was proud of the fact that they achieved their net interest margin goal of maintaining 3%. Unfortunately, this bank failed to read our article on how net interest margin is often statistically correlated to underperformance (HERE). True to form, credit risk improved across the industry through 2017, but this bank would not adjust their pricing. As a result, they gave up many loans that had 18% risk-adjusted return on equity so they could book more loans that had a sub 9% risk-adjusted return. Sure they got their net interest margin, but they also booked mostly small loans below $200,000, lines of credit and construction loans. Risk and cost are often your two largest components to loan profitability. How can you ignore these factors when it comes to loan pricing and setting your goals?
Dependent and Key Indicators
It also helps to be clear on the difference between an “independent metric,” a “dependent metric,” “a performance indicator” and a “key performance indicator.”
An independent metric is a metric that doesn’t have any influence on a performance indicator. For example, if you are trying to improve your return on assets, metrics like Bank D’s “cost of funds” have very little, and often negative impact on return. Statistically, there are banks out there with high cost of funds that have superior returns and low cost of funds with below average returns. Cost of funds doesn’t take into account duration, convexity, maintenance cost and other performance metrics that influence return.
What is the fastest way to lower your cost of funds – run off your higher cost of funds accounts. While you are at it, attract a bunch of short-term money, waive fees and go heavy on your free checking attributes. You might get a fantastically low cost of funds, but it will turn out to be expensive short-term money and an indicator of negative return.
There is nothing wrong with lowering your cost of funds as long as you control for other performance metrics or your goal is dependent on that variable. For example, if the bank wanted to improve the value of its deposit base, then the cost of funds is a dependent variable. However, for a return goal, a bank’s cost of funds is often an independent variable.
The illustration below highlights some definitions that banks might want to use to discuss various metrics. In this example, if your goal is to improve efficiency, then that would be a “key performance indicator,” or KPI. A related performance indicator that you might want to control that KPI with would be a metric around “asset per employee.” You would then want to take the dependent variable from that and focus on things like branch costs and loan origination costs to best affect your performance indicator and your KPI.
Metric Alignment and Horizon
Banks also want to think through their goals and the metrics they choose to make sure they are not working at cross-purposes. Banks that want to grow loans in double digits AND maintain their deposit costs, particularly in a rising rate environment are asking for trouble. As we have written about HERE, there is a strong correlation between loan growth and deposit beta.
Similarly, improving the customer experience and reducing costs is also difficult to pull off. Banks need to size their time horizon in accordance with the strategic initiative timeline. If a goal is to improve efficiency, and that new digital loan origination platform takes two years to bring online, then that efficiency improvement goal might want to be over three years.
Bank E had a perfectly workable goal, but just not the right process. Bank E failed to align their other goals, identify the performance indicators and the dependent benchmarks and failed to choose the proper time horizon for their goals. As a result, they were substantially under their 15% return on equity target.
Many metrics may offset each other in the short-run but be in alignment in the long-run. It is important for bank management to understand the timing and time lag of when each strategic and tactical effort will breakeven.
Some Common Metrics with Efficacy
Finally, not all goals are financial, and so it is important to pick the right metrics for the right goal and make sure they are in alignment.
We have highlighted the top five goals in each of the popular goal categories in banking all of which have a high level of efficacy. While not all of these goals may apply to your bank, this might give you an idea of how you can put a set of goals together that will result in performance that is superior by anyone’s perception.
Submitted by Chris Nichols on May 21, 2018