Financial fragmentation and SMEs’ access to finance

This paper focuses on the impact of financial fragmentation on small and medium enterprises (SMEs)’ access to finance. We combine country-level data on financial fragmentation and the ECB’s SAFE (Survey on the Access to Finance of Enterprises) data for 12 European Union (EU) countries over 2009-2016. Our findings indicate that an increase in financial fragmentation not only raises the probability of all firms to be rationed but also to be charged higher loan rates; in addition, it increases the likelihood of borrower discouragement and it impairs firms’ perceptions of the future availability of bank funds. Less creditworthy firms are even more likely to become credit rationed, suggesting a flight to quality effect in lending. However, our study also documents a potential adverse effect of increasing bank market power resulting from greater integration. This suggests that financial integration could impair firms’ financing, if not accompanied by policy initiatives aimed at maintaining an optimal level of competition in the banking sector

Medical Fuzzy-Expert System for Assessment of the Degree of Anatomical Lesion of Coronary Arteries

Background: Today, cardiovascular diseases cause 47% of all deaths among the European population, which is 4 million cases every year. In Ukraine, CAD accounts for 65% of the mortality rate from circulatory system diseases of the able-bodied population and is the main cause of disability. The aim of this study is to develop a medical expert system based on fuzzy sets for assessing the degree of coronary artery lesions in patients with coronary artery disease. Methods: The method of using fuzzy sets for the implementation of an information expert system for solving the problems of medical diagnostics, in particular, when assessing the degree of anatomical lesion of the coronary arteries in patients with various forms of coronary artery disease, has been developed. Results: The paper analyses the main areas of application of mathematical methods in medical diagnostics, and formulates the principles of diagnostics, based on fuzzy logic. The developed models and algorithms of medical diagnostics are based on the ideas and principles of artificial intelligence and knowledge engineering, the theory of experiment planning, the theory of fuzzy sets and linguistic variables. The expert system is tested on real data. Through research and comparison of the results of experts and the created medical expert system, the reliability of supporting the correct decision making of the medical expert system based on fuzzy sets for assessing the degree of anatomical lesion of the coronary arteries in patients with various forms of coronary artery disease with the assessment of experts was 95%, which shows the high efficiency of decision making. Conclusions: The practical value of the work lies in the possibility of using the automated expert system for the solution of the problems of medical diagnosis based on fuzzy logic for assessing the degree of anatomical lesion of the coronary arteries in patients with various forms of coronary artery disease. The proposed concept must be further validated for inter-rater consistency and reliability. Thus, it is promising to create expert medical systems based on fuzzy sets for assessing the degree of disease pathology