Совершенствование методов управления
Financial Decision Making Using Computational Intelligence covers all the recent developments in complex financial decision making through computational intelligence approaches. Computational intelligence has evolved rapidly in recent years and it is now one of the most active fields in operations research and computer science. The increasing complexity of financial problems and the enormous volume of financial data often make it difficult to apply traditional modeling and algorithmic procedures. In this context, the field of computational intelligence provides a wide range of useful techniques, including new modeling tools for decision making under risk and uncertainty, data mining techniques for analyzing complex data bases, and powerful algorithms for complex optimization problems.
Authorities of the state regulation, creditors and investors are interested in getting reliable information about the banking sector activities. The procedure of bank financial soundness and accountability evaluation is carried out by supervision authorities as well as by international and national rating agencies. The analysis of the methodologies of bank accountability evaluation and forecasting in Russia shows the following results. The Bank of Russia makes decisions on banks financial soundness based on financial coefficients of different groups; the calculations are grounded on the official bank statements. Apart from financial indicators, rating agencies evaluate qualitative parameters of the bank activities. The common problem of the bank financial accountability analysis in Russia is the lack of use of the forecasting methods predicting the financial statement of banks and the probability of default. As a result, the problem-free banks corresponding to the demands of the supervision authorities on standards were considered to be problematic during the crisis. The aim of this research is the dynamic analysis of the main indicators of the Russian banks activities at the different stages of the economic cycle in order to identify the indicators of the early bankruptcy prediction and the opportunity to forecast the changes in the bank financial statement.
The aim of the article is to model dynamics of risks and assess the cyclical effect of Basel II in the Russian banking system.