Финансовая грамотность: материалы для родителей. Модуль "Банки". 10-11 классы, СПО
The methodology of econometric approach to off-site monitoring of the Russian banking system is suggested. It includes econometric models of the probability of bank default, based on historical data on Russian bank defaults; models of ratings assigned to banks by rating agencies or experts, models of banks’ interest rates, and models of banks’ cost efficiency. Models are tested on real data in order to estimate possibility their potential use as part of Early Warning System in banks supervision.
Bank stabilization measures adopted by the Russian authorities since 2008 have benefited core state-owned financial institutions to a greater extent than other market participants. Public sector keeps swelling at the expense of domestic private sector. According to the author’s methodology, by January 2010 state-controlled banks possessed over 50 percent of all bank assets, thus putting Russia in the same league with China and India. Development banking and policy lending expand. A feature distinguishing Russia is gradual substitution of direct state control by indirect state ownership in the shape of corporate pyramids headed by state-owned enterprises and state-owned banks. We construct a dataset of bank-level statistical data for the period between 2001 and 2010 and find that quasi-private banks (indirectly state-owned banks) were the fastest growing subgroup. Nationalization and rehabilitation of failed banks was carried out by state-controlled banks and entities rather than by federal executive authorities directly. We suggest that the response of the Russian authorities to bank instability was consistent with long-term trends in the banking system evolution. Anti-crisis measures of 2008-9 re-aligned the sector with the traditional model of banking that rests upon dominant state-owned banks, directed lending, protectionism, administrative interference and elements of price controls. Increased government ownership of banks and control over lending activity are unlikely to be fully dismantled after the crisis is over. This scenario can nevertheless accommodate a tactical retreat of the state from non-core assets in the financial sector, leaving control over 3 largest institutions intact.
This paper uses the banking industry case to show that the boundaries of public property in Russia are blurred. A messy state withdrawal in 1990s left publicly funded assets beyond direct reach of official state bodies. While we identify no less than 50 state-owned banks in a broad sense, the federal government and regional authorities directly control just 4 and 12 institutions, respectively. 31 banks are indirectly state-owned, and their combined share of state-owned banks’ total assets grew from 11% to over a quarter between 2001 and 2010. The state continues to bear financial responsibility for indirectly owned banks, while it does not benefit properly from their activity through dividends nor capitalization nor policy lending. Such banks tend to act as quasi private institutions with weak corporate governance. Influential insiders (top-managers, current and former civil servants) and cronies extract their rent from control over financial flows and occasional appropriation of parts of bank equity.
The Article is focused on a problem of forecasting demand for cash money in ATMs of a commercial Bank. The solution of the forecasting problem let us optimize the processes of liquidity management, cash management and ATM service by the collection service. The method of machine learning - neural network-is used to obtain the forecast of cash turnover. The authors made and trained a model of a multilayer perceptron with one hidden layer in the Python 3 programming language using the Keras library, as well as a model of a recurrent neural network. As a result, the forecast of peaks and declines in demand for cash at the Bank's ATMs was obtained. Based on the forecast load management of ATMs ensures minimal maintenance costs and keep money in the ATM. The algorithm can be replicated to the entire ATM network, as well as applied to another commercial banks.