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The article describes the methods of financial and economic examinations to determine the insolvency of a company in the Baltic countries, Republic of Armenia, Ukraine, Republic of Belarus, the Russian Federation and Republic of Kazakhstan. The signs of insolvency regulated in legislation of the countries, and international requirements for the validation of expert methods are presented in the article. The authors present the results of a comparative analysis of the considered methods for assessing insolvency and results of testing methods based on data of annual reports of focus group of five Latvian bankrupt companies. The research has shown that the expert methods of all eight countries are based on a normative approach — comparing the calculated financial ratios with their normative value. In Ukraine, Republic of Belarus, the Russian Federation and Republic of Kazakhstan, the financial ratios and their normative values are approved in the legislation of the countries. In the Baltic countries and Republic of Armenia, these ratios and their values are developed in approved expert methodologies. The method of «net assets» is also used to assess the solvency of large companies. The test results showed that the methods of the countries reviewed are applicable in practice and give a similar assessment of the solvency of companies as a whole. More similar results present the methods of the Baltic countries, Ukraine and Republic of Belarus. The results of the methods of Republic of Armenia, Kazakhstan and the Russian Federation are more similar to each other, but slightly differ from the previously listed group of countries. The authors demonstrated the ability to validate the expert methods, which is necessary to use an expert conclusion on the assessment of insolvency as an evidence base in another country.

To protect investment and ensure repayment of payables, recent studies have focused on identifying the relationships between company bankruptcy and internal fraud. The P-score model that is based on the most popular Altman Z-score model has been developed to indicate the manipulation of financial statements. Purpose of the study is to determinate the accuracy and the feasibility of P-score and Z-score models to detect fraudulent bankruptcy in regional conditions, based on reports of the Latvian construction companies that failed due to fraud, and during the verification of other known data. Research methodology is based on the background studies of P-score testifying, applying this approach to the Latvian condition. The present study analyzes the behaviour of the two models in identifying distress and fraud. To testify the results of the study, the authors use the financial analysis methods, comparison, statistical and quantitative research methods. Findings have shown the possibility of using the P-score and Z-score technique for bankruptcy fraud detection at the Latvian companies, based on the construction sector samples. The accuracy of the method is above 80%. Research limitations – acquisition a large amount of data on companies that are in the process of analytical studies on the recognition of their insolvency and having signs of fraud is not possible due to the confidentiality of information. Practical implications – the results of the study may be applicable to the audit of the company, investment reliability assessment, partnership evaluation and economic examination to detect fraud. Originality/Value of the study is the first test of practical implication of P-score model in Latvia and the Baltic countries on the samples of small and medium-sized construction companies. The authors propose improving the coefficients of the P-score model taking into account the requirements for financial statements in Latvia

The aim of the article is to study forensic accounting methods to detect fraud in financial statements. A taxonomy of forensic analytics methods is proposed and a generalization of seven mathematical models for detecting fraud recommended by forensic accounting experts and practitioners is provided, allowing for the detection of fraudulent financial statements before it is too late. The authors’ qualitative analysis of evaluating fraud detection models is based on data from semi-structured interviews conducted in the focus group of forensic accountants, investigators, and prosecutors.

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