Disclosure of tax information -from tax reporting system to the financial statements, Case: Fortum Oyj

The main target of the study was to examine how Fortum’s tax reporting system could be developed in a way that it collects required information which is also easily transferable to the financial statements. This included examining disclosure requirements for income taxes under IFRS and US GAAP. By benchmarking some Finnish, European and US companies the purpose was to get perspective in what extend they present their tax information in their financial statements. Also material weakness, its existence, was under examination. The research method was qualitative, descriptive and normative. The research material included articles and literature of the tax reporting and standards relating to it. The interviews made had a notable significance. The study pointed out that Fortum’s tax reporting is in good shape and it does not require big changes. The biggest renewal of the tax reporting system is that there is only one model for all Fortum’s companies. It is also more automated, quicker, and more efficient and it reminds more the notes in its shape. In addition it has more internal controls to improve quality and efficiency of the reporting process.

Predicting bankruptcy of Finnish limited liability companies from historical financial statements

This master’s thesis studies the probability of bankruptcy of Finnish limited liability companies as a part of credit risk assessment. The main idea of this thesis is to build and test bankruptcy prediction models for Finnish limited liability companies that can be utilized in credit decision making. The data used in this thesis consists of historical financial statements from 2112 Finnish limited liability companies, half of which have filed for bankruptcy. A total of four models are developed, two with logistic regression and two with multivariate discriminant analysis (MDA). The time horizon of the models varies from 1 to 2 years prior to the bankruptcy, and 14 different financial variables are used in the model formation. The results show that the prediction accuracy of the models ranges between 81.7% and 88.9%, and the best prediction accuracy is achieved with the one year prior the bankruptcy logistic regression model. However the difference between the best logistic model and the best MDA model is minimal. Overall based on the results of this thesis it can be concluded that predicting bankruptcy is possible to some extent, but naturally the results are not perfect.