Migration Steps to Cash Flow Margin Planning and Forecasting: A Case Study

Journal of Performance Management, 2005 by Garza, Jaime, Schabes, Adam

As financial institutions are enhancing or replacing their performance measurement systems, much attention is also being given to enhancing their planning and forecasting processes. A key area of focus is the planning and forecasting of net interest margin as the interest rate environment illustrated in Chart 1 has been less than stable over the past several years. The interest rate environment combined with changes in customer behavior and complex funds transfer pricing methodologies is requiring institutions to understand the dynamics of both the customer and FTP rates collectively. Even more challenging is the fact that you are dealing with many moving parts that are often on a non-linear basis. With a large percentage of an institution's income directly resulting from margin the question begs, "why shouldn't margin planning receive more attention?" Chart 2 illustrates the major components of income and expense on a national average for financial institutions reporting to the FDIC.

As illustrated in Chart 2, combining interest income and interest expense (margin) makes up a very large portion of the return on asset component, yet many institutions concentrate resources on planning and forecasting the non-interest component of the income statement. Many institutions cite that changing to a cash flow basis for planning and forecasting margin would require too much bottoms-up input, thus equating to more time consumption. The fact is, that if done correctly much of the assumptions and calculations would be centralized and automated reducing time and effort.

In many institutions the culture also presents unequal levels of education, information and technology. This current state represents the need for a parallel effort of process improvement and change management strategies. Some view change management as cumbersome and time consuming but the goal is to manage the change relative to the objective. The simple methodologies of the past are also not conducive to the practice of integrating methodologies for actual results into the plan or forecast. In some cases institutions have gotten lucky with respect to variances but for many others, not having the tools to explain variances or shifts from plan represents the business case for changing the margin planning and forecasting methodologies.

THE PROBLEM AND A STARTING POINT

As performance measurement systems are providing better information and insights into actual results, executives and managers from middle and front offices are inquiring about the future. Identifying if potential hurdles exist requires the ability to drill-down into planning accounts analyzing both the existing book and projected volumes. However, many institutions do not have the data and structure to do this. The degree of difficulty seems to increase with the repricing, variability and optionality of products. For example, variable rate products that reprice within one month do not require as much consideration as adjustable rate, hybrid or fixed rate products. Additionally, products that contain customer optionality such as mortgages and non-maturing deposits require particular attention. Often planning chart of accounts are based on general ledger and not product attributes that may lack enough visibility into cash flow characteristics. We recommend that a chart of accounts be developed bearing in mind:

* A roll-up and product variability structure that can be used across the organization

* Correlation to performance measurement and asset/liability management (ALM) reporting charts

* Integration of top-down and bottoms-ups methodologies

* Incorporation of pipeline

* Product management views

Once an agreed upon chart is developed then "quick-hit" areas of focus should be identified. We found two pressing areas. The first was to provide the ability to gain insights about mismatch unit volatility then be able to forecast it under shifting economic rate and balance sheet scenarios. The second was to forecast break funding charges to assist the lines of businesses with the development of a plan and strategy for assessing how to recover the costs from the customer.

DATA AVAILABILITY AND HAVING THE PROPER ARCHITECTURE

The ability to produce and calculate cash flows is not possible without the appropriate data. One of the most underrated tasks in performance measurement is the ability to acquire quality data. You need to team up with operations and application support areas to determine if the right level of data is available. Most organizations lack the documentation of the links and interdependencies from one source system to another. In addition, the application software is rarely installed without customizations. It can require a large effort to scrub your data so that it is reliable for detailed analysis. There are several ETL (Extract, Transform & Load) software tools on the market that allow you to bring data into one common format for analysis. The software allows you to establish rules for translating a set of common attribute definitions accounting for things such as mergers or acquisitions. For example, during a conversion of a loan portfolio from an acquisition, the source system may use the acquisition date as the loan origination date. This may cause a problem in the funds transfer pricing calculations of the portfolio causing incorrect margin forecasts. For this reason you may need to back into the origination date based on attributes such as the maturity date and term of the loan.