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Firms are going bankrupt in Sweden at a rate without precedence in the 21st century. This development conicides with a financial and economic period of high uncertainty, where the Covid-19 outbreak caused lockdowns across the world. This was later followed up by wars, energy crisis, and a sharply increasing policy rate along with inflation. Small- and medium-sized enterprises (SMEs) in Sweden and elsewhere must manage this situation, and business executives, creditors, and other stakeholders are required to navigate through this challenging financial setting. A tool for doing so is to utilise bankruptcy prediction models to gain insights into various businesses’ health. Bankruptcy prediction models have been continously studied for decades, where no consensus regarding the methods for doing so nor variables to consider has been reached. Additionally, previous research has found that country-specific adoptions of bankruptcy prediction models improve out-of-sample performance, and that they should be adjusted in times of financial crisis.

The purpose of this study is to analyse the renowned Altman Z'' -score model in order to compare its performance between the pre- and post-Covid-19 period, as well as develop the field further by considering Swedish SMEs in times of virtually unparalleled financial circumstances. By comparing these time-periods, the aim is to determine whether the model’s accuracy remains robust in the post-pandemic financial environment. The model’s performance is evaluated using key financial ratios that has shown promise in previous research.

The empricial results indicate that the Altman Z''-score model’s overall accuracy has improved in the post-Covid-19 period but still displays moderate predictive power for identifying bankrupt companies. This highlights the need for adjustments. The results also show that the coefficients for Altman’s Z'' -score model are either obsolete or unfit for Swedish SMEs, as re-estimating them improves the predictive power in the post-Covid-19 period. Further, considering alternative financial ratios than the original model leads to a bankruptcy prediction model with six new financial ratios that outperforms Altman’s original Z''-score model. These results remain out-of-sample, indicating that the variables included in Altman’s Z''-score model are relatively obsolete for Swedish SMEs.

The thesis contributes to theory by expanding the knowledge on bankruptcy prediction in the context of unprecedented economic disruptions. Practically, it provides Swedish SMEs, creditors, and regulators with a refined bankruptcy prediction tool, offering more accurate insights for financial decision-making.