Return to search

BINARY BRIGHT-LINE DECISION MODELS FOR GOING CONCERN ASSESSMENT: ANALYSIS OF ANALYTICAL TOOLS FOR BANKRUPTCY PREDICTION CONSIDERING SENSITIVITY TO MATERIALITY THRESHOLDS

In August, 2014, the Financial Accounting Standards Board issued an update concerning the disclosure of uncertainties about an entity’s ability to continue as a going concern. The standard requires an entities management to evaluate whether there is substantial doubt about the entity’s ability to continue as a going concern and to provide related footnote disclosures in certain circumstances. One consequence of this regulation is the need for guidance for audit testing of management’s assessments in each phase of the audit.
This research evaluates the usefulness of bankruptcy prediction models as analytical tools in the planning stage of an audit for going concern assertions and questions the use of precision as the only measure of a model’s effectiveness. I use simulation to manipulate the fundamental accounting data within five bankruptcy prediction models, explore failure rates in an environment with materiality concerns, and consider the total change in market value due to simulated errors. Given the inherent limitations of the information environment and/or current prediction models, my results indicate auditors’ current failure rates are not an indication of audit failure. The results suggest that bright-line testing using bankruptcy prediction models are sensitive to materiality and that the cost trade-off between Type I and Type II errors is an important indicator of model choice.

Identiferoai:union.ndltd.org:uky.edu/oai:uknowledge.uky.edu:accountancy_etds-1011
Date01 January 2019
CreatorsBundy, Sid
PublisherUKnowledge
Source SetsUniversity of Kentucky
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceTheses and Dissertations--Accountancy

Page generated in 0.0019 seconds