Updating Analytical Procedures

By Blocher, Edward; Krull, George W., Jr. et al. | The CPA Journal, November 2002 | Go to article overview

Updating Analytical Procedures


Blocher, Edward, Krull, George W., Jr., Tashman, Leonard J., Yates, Stephen V. N., The CPA Journal


NEW SPIN ON OLD PROCESSES

In Brief

Tools for Greater Audit Effectiveness

New tools for analytical procedures promise even greater audit effectiveness and more efficient analytical procedures. Tools such as Microsoft Excel are already on most auditors' desktops. Business forecasting tools (BFT) are also readily available and promise both case of use and greater precision for the expectations that auditors must develop when using analytical procedures. These tools can allow the auditor to turn more attention to gathering reliable data for analytical procedures, and reward the effort of doing so. Perhaps most important, the new tools facilitate the development of explicit types of expectations, such as regression and time-series analysis, which, because they are more informed than implicit expectations, are more precise and more reliable for both the planning and substantive test objectives of analytical procedures. Moreover, BFT systems, unlike Excel, have built-in statistical checks to guide the auditor to more effective use of the tool.

The most effective analytical procedures provide the most reliable and accurate expectations for the account balance or item being examined. The most precise procedures involve making an "explicit expectation" of the account balance or item. With an explicit expectation, the auditor identifies the financial and operating relationships affecting the account, then uses those relationships to develop the expectation.

A simple comparison of current to prior year balances or ratios is not an explicit expectation. The implicit expectation is that the balance or ratio will be the same as the prior year's. In contrast, an explicit expectation asks "What should that balance or ratio have been at the end of the year?" For example, an explicit expectation for the sales account for a retail firm would use local business trends as well as information about the firm's operations (e.g., advertising expense) for the year. Because explicit procedures are more precise, they are the strongest analytical procedures for audit planning and testing. The most commonly used explicit procedures are regression analysis and time-series analysis. Spreadsheets and forecasting tools are readily available to perform these analyses.

Case Study on Developing Expectations for Balances

Consider an auditor performing an analytical procedure for the purpose of assessing the reasonableness of reported sales of a retailer. The monthly sales balances for the current year (2001) and the two prior years are known, and the sales are likely to be affected by three variables:

* Local business activity

* Monthly operating expense

* Monthly sales expense.

The auditor expects sales to increase in proportion to an increase in each of the three variables.

Regression and time-series analysis are predictive methods that systematically and mathematically provide the best-fitting expectation for the available data. Both the regression and time-series methods use prior periods' account balances to predict future balances. In the audit context, the "future balances" are the unaudited monthly figures for the current year.

Time-series analysis takes into account only information for the particular account balance: that is, its seasonality, trend, and any specific events that affected the sales balance for the current and prior years. These balance-specific factors are often called the time-series properties of the balance. Seasonality, special promotions, and other time-series properties are likely to be useful predictors of sales.

In contrast, regression analysis can include time-series properties as well as information about the relationship of sales to an index of local business activity, operating expenses, and selling expenses variables.

The Sidebar illustrates both regression and time-series analysis using Microsoft Excel and another widely available business forecasting tool that uses spreadsheet data input. …

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