Log in / Register
Home arrow Business & Finance arrow Fraud and fraud detection
< Prev   CONTENTS   Next >

Determine Whether IDEA Is Appropriate

IDEA is most useful when there is a problem to solve on an audit or used for substantive testing. IDEA should always be used subject to consideration of data volume and the cost of obtaining the required electronic data.

Data analysis techniques are necessary where there is a large volume of transactions. The greater the number of records, the more valuable IDEA is. When the number of records is low, using IDEA may not provide much benefit over a manual audit.

Consideration must also be given to the costs incurred in obtaining the data. Costs may be direct monetary cost in using outside services or cost in time for both the auditors and IT specialists. There may be major costs involved in determining the files and fields needed, writing queries, processing, and transferring the resulting data from the host computer to the auditor's computer or IDEA server. Time needs to be budgeted to examine the resulting files to ensure completeness and accuracy. Additional time may be required to investigate and correct data issues.

Data Requirements

Once the audit objectives have been well defined and it is determined that IDEA is the appropriate tool, the next step is to determine the data requirements. In order to do so, you must first identify the business or computer system, the business software used, and the files and fields needed to meet the audit objectives.

Hardware and Operating System

Identifying the computer system hardware and operating system will allow the auditor to determine whether IT support is needed. Computer hardware may be of entry level, business class, workstations and servers, mainframe, or supercomputers.

Operating systems include Windows, Mac OS, iOS, UNIX, Linux, and IBM OS.


Software can include off-the-shelf, add-ons, ERP, and custom-designed packages. Files

Though it may be simpler with off-the-shelf packages, you must still decide whether to obtain the raw data files and use your own copy of the package to convert the data to be readable by IDEA or to accept an export. The simplest types of export that most packages can handle are Microsoft Excel and print/pdf reports. Though there are disadvantages to both, no specialized skills are required.

For ERP and customized packages from large systems, IT support is required. At times, the expertise lies outside of the organization and third parties or consultants may be required.

Data Dictionary

For small packages, getting everything is simpler.

For large data packages, you need to determine which fields are relevant to the audit objectives. Files may be too large if everything is obtained. Also, many fields may not be relevant to the audit, such as budget, statistical, and nonfinancial fields. Consideration should also be given to the time and cost related to queries and processing.

Data Requirements

- Volume: While it is easier to ask an IT specialist for the entire file, as they would not need to create a query or do processing, it may not be practical due to the volume of data and additional work by the auditor to define every field in the record layout for IDEA.

- Ease of download: IT specialists are generally unconcerned with performing processing on their server because server memory is usually plentiful. However, the network is the bottleneck in the download process. Transferring data over the network may tie up resources. Transferring large amounts of data over a network may prevent or slow work for other users in the company. There may also be some security concerns.

- Master files: When obtaining any detailed files, you should also obtain the related master files. For example, vendor files may only contain vendor numbers, and you will need to obtain the vendor master file to join other relevant information, such as vendor name and address, to the detailed file.

- Flags, codes, and references: All fields containing flags, codes, and references should be reviewed and the translation chart obtained either in hardcopy or as a file. These flags and codes are usually meaningful and it is important that you understand their meaning.

Required Files and Fields Special attention should be given to date fields. For example, the posting date may be just as relevant as the transaction date for your audit objectives. When in doubt, include the field and then document its usefulness for the next time. Ensure fields with references can be traced to the source documents.

File Formats

Determine the most suitable file-output format under the circumstances.

Transfer Method

Determine what the most appropriate data transfer method is for the circumstances. Data transfer methods, include:

- Direct connect to the network server

- Internet

- FTP server: Care should be taken when transferring EBCDIC data as it converts to ASCII unless transfer options are set as binary. You may lose valuable data in the conversion process.

- Removable media (DVD, external USB drives, flash drives)

Other Questions to Consider

- Where is the data located.? - Is it live or archived?

- Is the requested data period available.?

- Can it be accessed?

- Is it readable?

- How long are data being retained?

- How large are the estimated file sizes.?

Once the data requirements have been established, a data request should be made in writing and include:

- Data parameters including files, fields, and the review period. - File format.

- Transfer method.

- Date when the data should be available.

- Contact information for the auditor.

- For reconciliation purposes, you may also want to request the number of records and totals for each file, as well as printouts of the first 50 records for each file. Verification items can also be requested from other sources. For example, you could request the trial balance files in order to verify sales or accounts receivable files.

Found a mistake? Please highlight the word and press Shift + Enter  
< Prev   CONTENTS   Next >
Business & Finance
Computer Science
Language & Literature
Political science