Open Access

Annika Wolf

• The EU Directive on Restructuring and Insolvency (EU 2019/1023)1 requires Member States to have an early warning system to allow companies in financial distress to detect distress early (enough) to engage in a restructuring, thereby avoiding insolvency. With the absence of a common model at Member State level, this paper analyses the opportunities for artificial intelligence / machine learning-based methods at a corporate level. It is in a company’s interest to implement a system that will alert the management to the need to take action and prevent a distress situation. The introduction sets the scene while part two discusses the theoretical framework of artificial intelligence / machine learning-based methods and distinguishes between artificial intelligence / machine learning and prediction models. Part three refers to the goal of the EU Directive on Restructuring and Insolvency for Member States to provide alert mechanisms for companies through financial distress prediction models. In Part four, the opportunities and obstacles are investigated through an empirical study with qualitative data, collected from German experts on the current status of (German) companies with respect to implementing artificial intelligence / machine learning as an early warning tool. The study finds that companies see opportunities for using artificial intelligence / machine learning-based methods as early warning tools. The conclusion summarises that there are obstacles to overcome in order to identify financial irregularities and to provide indications for future action to avoid or prevent financial distress.