While bankers historically have been focused on driving growth, the reality is that not all growth creates sustainable value or profits for banks. In fact, some industry estimates suggest that up to 40% of a bank’s customers may be unprofitable to their institutions. This underscores the level of complexity involved in effectively evaluating and managing profitability as bankers must have a clear view of which customers, channels, branches and products actually drive the greatest value.
A comprehensive profitability framework must start with a funds transfer pricing (FTP) system. An FTP system allocates the bank’s net interest margin to individual instruments and is the key driver in determining profitability. The allocation of margin is critical in financial institutions as it typically comprises up to 80% of net income.
To properly evaluate the institution’s performance while addressing regulatory requirements and evolving market conditions, banks must create an actionable framework upon which to measure profitability along several critical dimensions – a simple strategy that can present some noteworthy challenges, namely around data and methodology.
Good data is the foundation of any actionable profitability framework, so incongruous or unavailable data can jeopardize the ability to determine profitability across the organization. The data must be accurate, consistent and available at the correct level. If the bank’s goal is to determine activity unit costs for organizational, product and customer profitability, the data must be attributed and segmented across all of those dimensions.
In addition, methodology issues often arise – where there are several methodologies that can be applied, a bank must choose the most appropriate methods for the institution. For example, the application of FTP methods can be a simple pool approach (not recommended), or a robust matched maturity term funding approach. A matched term funding approach allows for the accurate calculation of three distinct spreads: the spread for assets, liabilities and the funding center. In this approach, each FTP rate is based on the cash flows of the underlying instrument, and then applied based on those cash flows at its origination date (or last repricing date for an adjustable rate account). This ensures that the charge/credit calculated (asset and liability FTP rates) matches the term of the instrument, taking out all interest rate risk to the originating department and “giving” that spread to the funding center to manage so that they may manage the interest rate risk of the organization.
There are also multiple approaches to calculating capital assignments, ranging from a regulatory risk-based assets method to a more complex, systemic model-driven method that incorporates various risk factors at the product or even the account level. These methodologies need to be evaluated and agreed upon by the institution’s key stakeholders. This step is critical to the acceptance of the results and their use throughout the organization. At the end of the process, the bank’s methodologies should not just produce numbers, but insightful, actionable information that is easily understood by those making decisions.
Staffing represents another common challenge. There are few banks today that have the luxury of maintaining a large staff with the bandwidth to support and update a complex profitability measurement system. As a result, financial institutions need a system that requires minimal maintenance and can quickly model and analyze results on the fly. Other key components required include:
Single data repository. Since there is a considerable amount of data involved in any profitability framework, the source data, assumptions, and the derived results must be available for past, current and future periods. Keeping historical data allows the bank to analyze trends and look for outliers that may uncover a need to adjust methodologies. Additionally, this data should be stored within a secure, scalable, auditable and manageable database and enable users to drill down into the drivers of calculated information to foster the acceptance of the results.
Robust calculation and modeling engine. To fully understand how decisions impact the bank’s profitability, end users must accept and comprehend the system’s calculations. To achieve this, profitability calculations must be transparent, auditable and easily understood throughout the institution. The application should allow the trace-back of results to their original source data and drivers. In addition, profitability results must be presented in a clear way that can be easily interpreted and used by any user to make decisions.
Insightful analytical capabilities. The most critical component of profitability measurement is a strong analytical capability. The application must be able to satisfy each user’s analysis needs while allowing them to easily perform ad hoc queries. The system should also enable alerts highlighting potential issues, allowing users to focus on areas that need improvement and revealing what elements drive the greatest value to the institution. The application should also provide user-friendly pricing models, available to the front-line staff. Using the information derived from the profitability measurement process at the time of decision is critical to positively impact the bank’s performance.
As today’s banks seek to better understand how its customers, channels, branches and products affect the bottom line, it is essential that they leverage a profitability measurement framework and utilize technology that properly supports the requirements of the institution – one that empowers banks to disseminate information to all areas of the institution to drive better decision making and, most importantly, gain a competitive advantage within the marketplace.
Mr. Levey is the vice president of financial institutions for Portland, Ore.-based Axiom EPM, which delivers performance management solutions for mid-sized and large banks and credit unions around the world. He can be reached at [email protected].
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