Many CPAs use computers to improve the speed of their tasks. However, using computers to change approaches or methods of performing audits is less widespread. The analytical approach presented here is a unique use of computer power that goes beyond just doing things faster. It presents a better way to look at relationships within account balances and identify account balances with a greater risk of material misstatement. The ability to determine and interpret patterns in financial information is an essential key to effective analytical procedures. Auditors are accustomed to looking for relationships and patterns in account balances or other information expected to exhibit a relationship, such as a change in vehicle expenses compared to the change in the number of vehicles owned. In "A Test Of Analytical Procedure Effectiveness" (CPA Journal, June 1992), Pany and Wheeler warn that analytical procedures are at times limited in their ability to detect errors and suggest that more sophisticated techniques may enhance effectiveness.
An approach that has proven effective in other disciplines in analyzing disparate data is known as exploratory data analysis (EDA). Under this approach, like data from multiple sources are subjected to statistical analysis without any preconceptions of what would be considered unusual or questionable. Based on the relationships of all the data from the various sources, patterns that seem unusual or don't make sense are highlighted or flagged for investigation. The data is explored and displayed on a computer screen using graphs, diagrams, or straight numerical data based on statistical models. An important element is the visual and graphical display of the data. With today's high quality monitors, the use of color to identify data and relationships becomes an added tool. EDA's objective is to allow users who have knowledge of data to explore patterns within the data. It is based on the premise that data from multiple sources can be explored and examined with the expectation of learning hidden truths. EDA's objective is compatible with the goal of analytical procedure--to identify potential misstatements, but in a way that the auditor finds easy and not intimidating to use. The approach allows the auditor to see things that stand out graphically that might otherwise be missed in a simple numerical review of the data.
This type of graphical analysis is not a replacement for the traditional use of statistics in areas such as sampling but is intended to improve the persuasiveness of the information gained in performing analytical procedures. SAS 56, Analytical Procedures, states that the focus of analytical procedures should be on enhancing the auditor's understanding of the business and identifying areas of risk. EDA is able to accomplish this.
THE TOOLS OF DATA ANALYSIS
Statistical packages have changed considerably over the last few years, and have become more user friendly. Newer packages constructed around the concept of EDA lend themselves to innovative graphical approaches. Rather than performing a series of statistical tests, these programs provide a graphical analysis of data including the comparison of several aspects of the data simultaneously, which John Tukey, the originator of EDA describes as detective work.
Several acceptable application software programs perform EDA, including one designed for Macintosh computers, Data Desk, developed by Paul Velleman, relying on the work of Tukey. A highly recommended program for the PC environment is Systat. The software furnishes standard statistics but also incorporates extensive color graphics and provides for a great deal of flexibility in exploring data. Systat with Sygraph requires an IBM PC, XT, or compatible; PC-/MS-DOS 2.0 or later; 640K of RAM; two floppy drives and a graphics adapter. The list price for Systat with Sysgraph at the time of our study was $795. Data Desk requires a minimum of a MAC Plus with 1 megabyte of RAM, an 800K disk drive, and either a second floppy disk drive or a hard drive. …