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Anticipating Uncertainty with Scenario Planning


Effective scenario modeling is vitally important in today’s tentative economic recovery, as the level of uncertainty surrounding key business drivers is higher than ever before. Scenario planning is not a new concept, yet very few financial institutions have taken the strategic step of implementing sophisticated scenario planning into their strategic planning initiatives, preferring instead to simply budget or forecast with only one economic scenario in mind.

The reality is that while having a strong general understanding of the institution’s anticipated revenue or earnings per-share is important, deeper insight into what factors actually drive the business – and then modeling the cause and effect of certain situations on the institution’s financial drivers – will provide more meaningful insight into the institution’s expected performance. While many financial institutions understand the importance of modeling multiple scenarios, they lack the technology needed to do so, citing bandwidth constraints and lack of institutional knowledge as additional barriers to implementing a more insightful, sophisticated scenario-modeling process.

The ability to accurately analyze the impact of economic fluctuations on the institution’s performance and its bottom line can be difficult, but not impossible, to achieve. First, institutions must have an understanding of the four common types of scenario models to determine what approach is most appropriate for their institution:

Single variable sensitivity analysis. To quantify the impact of a particular change, this type of scenario modeling changes one variable at a time while holding others constant. While fairly simple, it helps identify the drivers or model inputs that have the most impact on the institution and therefore deserve the most attention. This analysis is a great educational tool for the institution’s management team and is a good starting point for the analysis.

Multi-variable narrative-based. This type of modeling is appropriate for scenarios that require a more formal approach following a particular story line or narrative, as it measures the impacts of various uncertainties occurring jointly. For instance, a scenario might take the form of a certain theme, piecing together the plausible relationships of market forces, including factors that the institution is quite certain of, as well as factors that are more difficult to predict. The challenging part of a multi-variable narrative-based approach is the time-consuming process of agreeing on themes and constructing the models.

Initiative-based scenario modeling packages different sets of initiatives into one composite plan or strategy. The institution’s stakeholders can then develop various self-contained initiatives, inclusive of a full set of financials, such as adding a new branch or product. This insight enables management to layer various initiative combinations on top of a baseline to manage overall operations of the organization.

Stochastic is a computer-simulated scenario planning model that applies random number generation processes (i.e. interest rates, commodity prices, exchange rates, etc.) against a key variable(s) to determine probability distribution and the potential impact on the institution’s financial plans. This type of planning can generate up to thousands of scenarios, allowing the institution to evaluate a distribution of several outcomes. A stochastic model is commonly used to manage risk.

From a business standpoint, scenario planning is a powerful learning tool, revealing assumptions and biases that are otherwise hidden. It also expands the range of what is possible with regard to the institution’s strategy. Failure to model plans based on multiple scenarios could lead to, among other things: costly surprises down the road; an inability to generate new opportunities; poor quality of strategic thinking; and lack of competitive advantage.

Many institutions have the perception that this type of scenario planning is beyond their capabilities. However, if they implement technology and processes that thoughtfully reveal areas of exposure and opportunity, they can achieve better decision-making and have the ability to guide the performance of the institution, even in the most unpredictable market conditions.

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].