Decision Tree Tool for Auditors’ Going Concern Assessment in Spain

The COVID-19 pandemic increased uncertainty about the financial future of many organizations, and regulators alerted auditors to be increasingly skeptical in assessing an entity’s ability continue as a going concern. An auditor’s assessment concern is matter significant judgment. This paper proposes use machine learning construct Decision Tree Automated Tool, based on both quantitative indicators (e.g., Z-scores) qualitative factors partners’ judgment industry risk given pandemic). Considering results model that provides additional audit evidence for their going-concern assessment. auditing firm Spain used supplemental guide, model’s suggested were compared auditors’ reports evaluate its effectiveness accuracy. predictions significantly similar assessments, indicating high level accuracy, differences between proposed outcomes final conclusions investigated. also insights machine-learning predictive models considered research.