Modelling business bankruptcy for audit purposes

Abstract

To facilitate informed decision-making and foster transparency, stakeholders require access to reliable financial information. Financial audits serve the purpose of assisting companies in achieving success by assuring the accuracy and transparency of their financial statements. However, due to the evolving and increasingly competitive nature of markets, companies may exhibit indicators of financial vulnerability, commonly referred to as "red flags." These warning signs could potentially lead to business failure and bankruptcy. To mitigate such risks, predictive models for assessing the likelihood of business failure have been developed. Such models offer valuable decision-making support for auditors, enabling them to identify and mitigate risks associated with financial distress. The primary objective of this study is to develop a predictive model based on logistic regression and compare its effectiveness with traditional audit opinions. The sample comprises Portuguese small and medium-sized enterprises from the textile sector. Data were collected from the SABI database (Iberian Balance Analysis System). For the years 2017 and 2018, 371 insolvent SMEs and 2412 active SMEs were obtained. Through empirical analysis, it was found that regression models possess greater predictive capability compared to conventional audits. The application of these models significantly enhances the accuracy of assessing a company's financial status, thereby enabling professionals to provide more informed and appropriate opinions.