Identifying going concern issues in auditor opinions: link to bankruptcy events.

In this work, we examine the auditor opinions that are provided in financial reports of public companies, when they express issues related to going concerns. Auditor opinions provide explicit insights regarding potential threats to the financial status of companies. We, therefore, provide methods for the automated classification of the auditor narratives to going concern issues, and we investigate which of those issues are related to bankruptcy events. We focus on annual reports of public US companies and publicly available bankruptcy labels to learn models that label these reports with probable going concern issues in an automated way. Our experimental results validate our approach and provide evidence that the analysis of these narratives can lead to the identification of specific issues related to bankruptcy concerns and thus alarm the interested parties.