We analyze empirically the usefulness of combining accounting and auditing data in order to predict corporate financial distress. Concretely, we examine whether audit report information incrementally predicts distress over a traditional accounting model: the Altman's Z‐Score model. Although the audit report seems to play a critical part in financial distress prediction because auditors should warn investors about any default risks, this is the first study that uses audit report disclosures for predicting purposes. From a dataset of 1,821 Spanish distressed private firms, we analyze a sample of distressed and non‐distressed firms and develop logit prediction models. Our results show that while the only accounting model registers a classification accuracy of 77%, combined models of accounting and auditing data exhibit considerably higher accuracy (about 87%). Specifically, our findings indicate that the number of disclosures included in the audit report, as well as disclosures related to a firm's going concern status, firms’ assets, and firms’ recognition of revenues and expenses contribute the most to the prediction. Our empirical evidence has implications for financial distress practice. For managers, our study highlights the importance of audit report disclosures for anticipating a financial distress situation. For regulators and auditors, our study underscores the importance of recent changes in regulation worldwide intended to increase auditor's transparency through a more informative audit report.

中文翻译：

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审计报告信息是否比Altman的传统Z-Score模型改善了财务困境预测？

我们从经验上分析了合并会计和审计数据以预测公司财务困境的有用性。具体而言，我们检查审计报告信息是否能增量预测传统会计模型（Altman's Z）的困境评分模型。尽管由于审计师应警告投资者任何违约风险，审计报告似乎在财务困境预测中起着至关重要的作用，但这是第一项使用审计报告披露进行预测的研究。从1,821家西班牙不良私营企业的数据集中，我们分析了不良和非不良企业的样本，并开发了logit预测模型。我们的结果表明，尽管唯一的会计模型的分类准确度为77％，但是会计和审计数据的组合模型显示的准确度要高得多（约87％）。具体而言，我们的发现表明，审计报告中包含的披露数量以及与公司持续经营状况，公司资产，公司对收支的认可对预测的贡献最大。我们的经验证据对财务困境的实践有影响。对于管理人员，我们的研究强调了审计报告披露对于预测财务困境情况的重要性。对于监管机构和审计师，我们的研究强调了全球范围内最新法规变化的重要性，这些变化旨在通过提供更多信息的审计报告来提高审计师的透明度。