Predicting Corporate Bankruptcy in Sweden: A Machine Learning Approach Combining Financial and Nonfinancial Data
Company bankruptcy can have severe consequences for stakeholders and the broader economy, making early and accurate prediction essential. This thesis investigates the effectiveness of integrating financial and textual data for bankruptcy prediction among Swedish companies. Financial ratios are extracted from structured statements in the Retriever database, while unstructured textual data is retrie
