Analysis of banking and currency risks using IT

Abstract

The work includes a review and analysis of modern leading specialized software products that are used to identify, analyze and manage risks in various areas. As an alternative, the project of own information system for analysis, forecasting and effective management of banking risks is proposed. To receive input data, the system uses a simple and easy free service for current and historical currency exchange rates and cryptocurrency rates. Currency data comes from financial data providers and banks, including the European Central Bank. The main methods used in the analysis are visualization, calculation of statistics and forecasting. The use of visualization allows you to present information in an easy-to-understand form, summarize statistical and analytical data concisely and succinctly. To forecast the main movement trends, it is proposed to use market indicators RSI, Bollinger Bands and Japanese candles, as well as machine learning using the algorithm of singular spectral analysis. Using the created product, an analysis of the shares of well-known global banks with subsidiaries in Ukraine was carried out. Trends in the exchange rates of various currencies, such as the pound sterling, the Japanese yen, the Chinese yuan, the dollar, the euro, and the hryvnia, were also analyzed. The proposed information system is publicly available and easy to use. The described methods of analysis enable an unqualified user to draw conclusions on the basis of the obtained visualizations regarding the choice of the optimal reliable bank, management of the risk of devaluation of hryvnia savings, and minimization of losses from money conversion. The results show that in the case of a small set of assets and, accordingly, restrictions on the diversification of capital investments, the use of such information systems is effective and profitable. The presented methodology also demonstrates that an investor, having basic knowledge of information and communication technologies using modern Python, Java or C# programming languages, can effectively use them to create specialized systems for data analysis, visualization and forecasting.