IDEA (software)

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IDEA
Basic data

developer CaseWare IDEA Inc.
Current  version Version 10
operating system Windows
category Mass data analysis
License Proprietary
German speaking Yes
[1]

IDEA (Interactive Data Extraction and Analysis) is software originally developed for the Canadian Court of Auditors and has been on the market since the 1990s for analyzing large amounts of data.

meaning

IDEA has its origins in internal auditing and controlling and is now also used in auditing in 90 countries in various areas of data analysis. The software has been used by the German tax authorities since January 1st, 2002 . The customs administration has also been using IDEA since 2005 for customs audits.

IDEA is mainly used in the context of external audits to analyze data that the tax authorities are allowed to access in accordance with the "principles for the proper management and storage of books, records and documents in electronic form and for data access" ( GoBD ). The currently most common type of access is data carrier transfer (so-called Z3 access), in which the audit-relevant data are to be transferred to the auditor on a data carrier. The data contained can then be subjected to significantly more function evaluations with IDEA than would be possible with the system-immanent evaluation options of the programs installed at the taxpayer.

The special importance of IDEA is that with the use of this program complete exams are possible in the shortest possible time. In addition, the tax authorities are constantly developing new audit macros with which audit steps can be carried out automatically. The knowledge and experience of individual auditors are thus externalized and thus generally made available to all tax auditors.

positioning

Conceptually, IDEA is comparable to both spreadsheet software such as Microsoft Excel and a database system. IDEA also manages data in tables. In contrast to Excel or a database system, the functions of IDEA are somewhat more restricted and designed more for the specific purpose. IDEA, on the other hand, is optimized for the rapid processing of very large amounts of data. In addition, the import and analysis steps carried out are logged. Accordingly, the creation of an evaluation file remains traceable. The work steps carried out can be exported to text documents in order to document the analysis procedure.

In addition to the IDEA software, additional modules such as "AIS TaxAudit" can be used. These modules, for example, import the data exported from common financial accounting programs via a manufacturer-specific interface (HSS) and use them to create standardized output and test tables. With annually updated test macros (e.g. to take legal changes into account) standardized evaluations can be carried out. Further detailed checks can be carried out on the basis of these evaluations. An extension with your own test routines is possible. The aim is that the user of the test macros needs less technical and programming knowledge, but only specialist knowledge of the matter. The tax authorities also use TaxAudit across the board. In addition to IDEA, the financial administration also uses Excel-based tools, e.g. B. for the summary risk assessment ( SRP ). A software comparable to IDEA is ACL (Audit Command Language). It also comes from a Canadian manufacturer.

Range of functions

The functionality of IDEA is aimed at mass data analysis. The following essential functionalities are available:

  • Age structure analysis: is used to group a file from a certain date (due date) in up to 6 predefined intervals. These intervals can be days, months, or years. For example, it can be used for the due date analysis to determine open items that are older than 2, 4, 8, 10, 12 or 14 months with regard to a selected key date.
  • Benford's Law : describes that digits and sequences of digits in a set of data correspond to a certain pattern (probability distribution). For this purpose, the data are compared with the data pattern expected according to Benford's Law.
  • Data import: it is possible to import different data formats ( Microsoft Access , Microsoft Excel, dBase , print lists, ASCII , EBCDIC , ODBC etc.).
  • Complementary statistical methods: include correlation , trend and time series analyzes .
  • Extract and filter: are used to identify records that meet a specific condition.
  • Field statistics: for all numeric fields, date and time fields within a file.
  • History: includes an audit trail with entries on all operations. IDEA creates an entry in the history for all operations carried out on the file, including the import and the checking functions. It enables complete documentation of all steps that are carried out in IDEA in order to be able to reconstruct them afterwards.
  • IDEASkript: is a development tool to expand the possibilities and functionality of IDEA by automating repetitive tasks or processes with IDEASkript in a macro.
  • Gap analysis: With the help of the gap analysis, missing data records can be determined in a numerical order or in a certain range of values ​​in numerical fields, character fields or date fields of a file. A gap indicates that one or more records are missing from the sequence. Gap analysis is commonly used to check the completeness of data, e.g. B. to analyze missing document numbers.
  • Multiple occupancy analysis: is used to identify records with or without duplicates within a field or a combination of up to 8 fields. For example, multiple invoice numbers can be identified.
  • Fuzzy multiple occupancy analysis : This allows similar elements to be identified using a fuzzy search . For example, typing errors can be determined using this analysis. Individual words up to short sentences can be analyzed.
  • Pivot table : is a surface (cross table) to display and organize data in a desired order. It can be used to clearly display combinations and structures of a complex database.
  • Report Reader: is used to prepare data and import print lists and PDF files.
  • Layering : is used to group data in numeric or date fields. With this function, the data of a file can be divided into value layers (usually from the minimum to the maximum values ​​of one or more fields) and the data records of the file can be accumulated in the relevant layers. By summing the data records and the values ​​in a layer, the user can obtain a profile of the data within the file.
  • Samples : IDEA offers various sampling methods in combination with the possibility of calculating the sample sizes based on the parameters you have defined and of assessing the results of the sample tests.
  • Totalization: This function adds up the data in a numeric field (total field) with regard to one or more key fields. For example, this function can be used to add up the outstanding payment amounts for a " open items " file for the "customer number" key.

application

Application examples are checks to determine whether employees and suppliers have identical account details, or whether supplier account details have been changed for individual transfer transactions and reset to their original status after the transactions have been completed. Checking the completeness of documents based on their numbering or recognizing periods in which no documents exist are typical tasks. The specific test steps that can be carried out with IDEA mainly depend on the type and quality of the available data and the qualification of the user.

Web links

Individual evidence

  1. ↑ Kruger, Ralph; Schult, Bernd; Vedder, Rainer: Digital company audit: GDPdU in practice - principles for data access and the verifiability of digital documents, Gabler Verlag, Wiesbaden, 2010, ISBN 978-3-8349-0676-2 , p. 52
  2. ↑ Goldshteyn, Michael; Gabriel, Alexandra; Thelen, Stefan: Mass data analysis in the annual audit - basics and practical applications with the help of IDEA, IDW Verlag, Düsseldorf, 2013, ISBN 978-3-8021-1883-8 , p. 43
  3. ↑ Becker, Axel; Beckmann, Andreas: Digital customs inspection: more data, less opinion, Außenwirtschaftliche Praxis, special edition 2015, pp. 45–46
  4. ↑ PricewaterhouseCoopers AG Wirtschaftsprüfungsgesellschaft (ed.): Digital tax auditing: Challenge or relief ?, PwC, 2012, p. 21
  5. ^ Eller, Eller, Peter: Electronic invoicing and digital tax auditing, Erich Schmidt Verlag, Berlin 2003, ISBN 3-503-07408-2 , p. 94
  6. ↑ Kruger, Ralph; Schult, Bernd; Vedder, Rainer: Digital auditing: GDPdU in practice - principles for data access and the verifiability of digital documents, Gabler Verlag, Wiesbaden, 2010, ISBN 978-3-8349-0676-2 , p. 53
  7. ↑ for a detailed description see Goldshteyn, Michael; Gabriel, Alexandra; Thelen, Stefan: Mass data analysis in the annual audit - basics and practical applications with the help of IDEA, IDW Verlag, Düsseldorf, 2013, ISBN 978-3-8021-1883-8 , pp. 44–61