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The Reduced Rules Rule Based Forecasting Decision Support System: Details and Functionalities: An Audit Context

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  • Manuel Bern
  • Edward Lusk

Abstract

In execution of PCAOB audits at the Planning and Substantive Phases, forecasts of various financial account balances are often used to collect information on the veracity of the client’s final reported balances. One of the forecast methods widely acclaimed in the academic context is the Rule Based Forecasting [RBF] model of Collopy and Armstrong [C&A]. However, for the most part, the RBF has not found its way into the panoply of the auditor. In our practice-oriented experiential context, the reason for this seems to be the lack of an enabling Decision Support System[DSS] usually needed to create reliable RBF-forecasts in a timely manner needed at the Substantive Phase of the audit. Focus In this report, we detail a GUI-friendly DSS, the VBA-programming of which is based upon a 2013 revision of an updated C&A model offered by Adya and Lusk. The DSS is called- The Reduced Rules- Rule Based Forecasting- Decision Support System [RR-RBF-DSS]. We provide a comprehensive example of the RR-RBF-DSS in a PCAOB-audit context for a Caterpillar™, Inc.Ò account Panel downloaded from Bloomberg™. This example, carefully details all of the numerous User Form-Launch platforms as well as discusses the statistical and operational Rule-scoring functionalities of the RR-RBF-DSS. The RR-RBF-DSS is available as a download without cost or restrictions on its use.

Suggested Citation

  • Manuel Bern & Edward Lusk, 2020. "The Reduced Rules Rule Based Forecasting Decision Support System: Details and Functionalities: An Audit Context," Accounting and Finance Research, Sciedu Press, vol. 9(3), pages 1-13, August.
    • Handle: RePEc:jfr:afr111:v:9:y:2020:i:3:p:13
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    References listed on IDEAS

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    1. Makridakis, Spyros & Hibon, Michele & Lusk, Ed & Belhadjali, Moncef, 1987. "Confidence intervals: An empirical investigation of the series in the M-competition," International Journal of Forecasting, Elsevier, vol. 3(3-4), pages 489-508.
    2. Adya, Monica, 2000. "Corrections to rule-based forecasting: findings from a replication," International Journal of Forecasting, Elsevier, vol. 16(1), pages 125-127.
    3. Adya, Monica & Collopy, Fred & Armstrong, J. Scott & Kennedy, Miles, 2001. "Automatic identification of time series features for rule-based forecasting," International Journal of Forecasting, Elsevier, vol. 17(2), pages 143-157.
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    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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