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ECONOMICS
УДК: 338.27
Алексина Д.В.
Владимирский государственный университет имени Александра Григорьевича и Николая Григорьевича Столетовых
ОСОБЕННОСТИ ПРИМЕНЕНИЯ ЗАРУБЕЖНЫХ МЕТОДИК ОЦЕНКИ БАНКРОТСТВА В
РОССИЙСКИХ КОМПАНИЯХ
Aleksina D. V.
Vladimir State University
FEATURES OF THE APPLICATION OF FOREIGN BANKRUPTCY TECHNIQUES IN RUSSIAN
ENTERPRISES
Abstract
The article considers the problem of the adequacy of the risk assessment models bankruptcy Patriotic governmental organizations. Based on actual data offinancial statements of do enterprise-quality, shows the inconsistency of estimates obtained using different models. The emphasis is placed on the incorrect use of formal foreign models of risk assessment when the bankruptcy of domestic enterprises. It is emphasized the need for research on the development of a unified methodology in the assessment of bankruptcy of the various organizations.
Keywords: bankruptcy risk assessment model, the bankruptcy, the probability of bankruptcy, the organization, discriminated analysis.
During the economic crisis problems of reliable forecasting of the probability of bankruptcy become more urgent. Over the years, economists of different countries have been trying to develop a universal model that allows to accurately predict the risk of the emergence and development of an unfavorable financial situation in the entity. Unfortunately, there is practically no such model. Therefore, the problem of reliability of the results obtained by various models of bankruptcy remains relevant.
In foreign and domestic economic science, many models are used to assess the bankruptcy of enterprises and organizations, built on different principles and methods. Models of forecasting bankruptcy are usually built on the aggregates of economic indicators of individual organizations that most fully reflect the state of their financial and economic activities and take into account the national characteristics of the economy in the country in which this sample is made. However, due to the fact that a lot of external and internal factors influence the activity of the enterprise, the results obtained by different models do not always adequately reflect the actual state of the financial and economic activity of a particular firm. It should be noted that the models built for organizations located in one country cannot adequately take into account the specific conditions for the development of the economy of another country.
Thus to date there has not yet emerged a single universal method for assessing the bankruptcy of organizations, which could be used both in international and domestic practice.
Among the foreign models of the assessment of bankruptcy of organizations the following models were most widely used: two-factor Altman, five-factor modified Altman, Fulmer model, Springate, Chesser, Tuffler and Fox.
In Russian practice, the following models are considered adapted to our economic conditions: the O.P. Zaitseva model; the model of R.S. Saifulin and G.G Kadykov; The Irkutsk model.
The object of research of this work is LLC «Diesel». LLC «Diesel» is a trading company that has the right to be engage in the following types of activities:
S retail sale of motor fuel,
S wholesale of fuel,
S storage and storage of oil and products of its processing,
S activity in the field of law, accounting and audit, advising on business and enterprise management.
This company was chosen because for several years it did not reflect the net profit on the reports, all the financial indicators were filed.
Based on the financial reporting data, all models of the probability of bankruptcy were applied.
Let's analyze the Altman model of forecasting the probability of bankruptcy of an enterprise. Edward Alt-man is an American exercise that was one of the first to propose to evaluate the financial state not using coefficients, but using an integrated model[1, c.24-26].
The two-factor model is a model that takes into account the impact of two indicators: the ratio of current liquidity and the ratio of debt to obligations. The formula has the following form:
Z=-ü.3877-1.0736*Kcl+0.0579*(LC/O), (1)
where Rcl - coefficient of current liquidity;
LK - loan capital;
O - obligations.
- if Z = 0 - approximately equal to 50%;
- if Z <0 - less than 50% and decreases along with a decrease in Z;
- if Z> 0 - more than 50% and increases with increasing Z.
Consider the Altman model for enterprises whose shares are traded on the exchange market. This model Z = 0.717 Xi + 0.847 X2 + 3.107 X
where Xi - the ratio of the difference between current assets and current obligations to the total amount of all assets;
X2 - the ratio of retained earnings to the total amount of assets;
X3 - the ratio of profit before interest and taxes to the total amount of all assets;
X4 - the ratio of the book value of capital to loan capital;
H = 5.528 Vi + 0.212 V2 + 0.073 V V7 +1.083 V8
is a modified version of the five-factor model [2, c. 351].
+ 0.42 X4 + 0.995 X5, (2)
X5 - the ratio of proceeds from sales to the total amount of assets.
- if Z <1.23 the enterprise is declared bankrupt;
- if Z is from 1.23 to 2.89 the situation is not defined;
- If Z is more than 2.9 the situation in the enterprise is stable.
The model of the Danish economist Fulmer, developed in 1984, contained 40 coefficients, but the final version contains only 9.
+ 1.270 V4 - 0.120 V5 + 2.335 V6 + + 0.575 (3)
+ 0.894 V9 - 3.075,
where V1 is the ratio of retained earnings to assets; V2 - the ratio of revenue to assets; V3 - the ratio of profit before taxes to assets; V4 - the ratio of cash flow to loan capital; V5 - the ratio of loan capital to assets; V6 - the ratio of short-term obligations to assets; V7 - the ratio of tangible assets to assets; V8 - the ratio of working capital to loan capital; V9 - the ratio of profit before payment of interest and taxes to paid interest.
Z = 1.03X1 + 3.07X2
The model of the Canadian scientist Sprange, built on the basis of a step-by-step discriminant analysis developed by Altman, was described in 1978. Springate singled out the four main coefficients by which it is possible to predict bankruptcy:
X1 - the ratio of current assets to the total assets;
X2 - the ratio of profit before payments to the total assets;
X3 - the ratio of profit before payments to current obligations;
X4 - the ratio of revenue to total assets + 0.66X3 + 0.4X4 (4)
American economist Chesser has developed one of the first statistical models, which is used for the probability of bankruptcy by adjustment of data to a logistic curve. His idea was called the logit-model of assessing the financial condition of the firm [3, c. 178-183]. The function has the form:
Z = 1 / [1 + e-Y] (6)
where E = 2.71828
If the value of Z> 0.5, the probability of bankruptcy is high.
British scientists Tuffler and Tishou in 1977 developed their model of forecasting bankruptcy. The
Y = -2.044 - 5.24Xi + 0.0053X2 - 6.6507X3 + 4,40Q9Xn firfaMXindicliMft Xï this model are: (5)
where Xi - (Cash assets + Sell-Off) / Total assets Xi = Profit on sales / Short-term obligations
X2 - Sales / (Cash + Sell-Off) X3 - Income / Total assets X4 - Total debt / Total assets X5 - Fixed capital / Net assets X6 - Working capital / Net sales
T = 0.53 * X1 + 0.13 * X2 + 0.18 * X3 + 0.16 * X4
X2 = Current assets / (Short-term obligations + Long-term obligations)
X3 = Long-term obligations / Total assets X4 = Total assets / Revenue on sales
(7)
According to the tests conducted, this model iden- The model of the Fox takes into account such fac-
tifies the firm bankrupt with a probability: 98% per tors as liquidity, profitability and financial independ-year; 71% in two years; 60% in three years; 33% in four ence of the enterprise. The function looks like this: years.
Z = 0.063 * X1 + 0.092 * X2 + 0.057 * X3 + 0.001 * X4 (8)
where: X4-equity / loan capital.
Xi - working capital / total assets; O.P. Zaitseva in Novosibirsk has developed a
X2 - profit on sale / amount of assets; comprehensive bankruptcy ratio.
X3 - undistributed profit / total assets;
K = 0,25Xi + 0,1X2 + 0,2X3 + 0,25X4 + 0,1X5 + 0,1X6 (9)
Xi = loss ratio of the enterprise, characterized by the ratio of net loss to equity;
X2 = coefficient of the ratio of accounts payable and receivables;
X3 = ratio of short-term obligations to the most quickest assets;
X4 = unprofitable sales of products, characterized by the ratio of net loss to the volume of sales of these products;
X5 = debt capital ratio (long-term and short-term obligations) to own sources of financing;
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X6 = ratio of total assets of the enterprise (total bal- To determine the probability of bankruptcy, need
ance sheet) to revenue. to compare the actual value with the normative one [4,
c.336].
Kn = 0,25 * 0 + 0,1 * 1 + 0,2 * 7 + 0,25 * 0 + 0,1 * 0,7 + 0,1 * X6 (last year) (10)
If the actual value is large regulatory, then the probability of bankruptcy is extremely high.
Rating model RS Sayfulina and G.G. Kadykova can be applied to any industry and organization of various scale.
R = 0.2 * Xi + 0.1 * X2 + 0.08 * X3 + 0.45 * X4 + X5 (11)
Irkutsk model, developed by scientists of the Irkutsk State Economic Academy. The function has the following form:
R = 8.38 Xi + X2 + 0.054 X3 + 0.63 X4
(12)
Xi - working capital / assets;
X2 - net profit / equity;
X3 - net income / total balance sheet;
X4 - net profit / total costs.
The results of calculation by average annual indicators confirming the inadequacy of estimates of the probability of bankruptcy of this enterprise, received by means of ten models are given in table 1.
Five out of ten models show a low estimate of the probability of bankruptcy. These are models of Altman,
Table 1.
Results of calculation of probability of bankruptcy of the entity on foreign and domestic models of LLC
Diesel
the Fulmer model, Tuffler model, and Sprange. Foreign scientists developed all models. Also, 5 models out of 10 gave a high probability. These include the model of Chesser, Sayfullin and Kadykov, Lisa, Zaitseva and the four-factor model of the IGEA.
And five foreign models from the above-named gave a low estimate of the probability of bankruptcy for this enterprise, and two - high. All domestic models showed similar estimates.
Model Estimation of the probability of bankruptcy of an enterprise
2015 2016 2017
The two-factor Altman less 50% less 50% less 50%
The five-factor modified Altman unlikely 50% 50%
The Fulmer's model low high low
The Tuffler-Tishaw model low low low
The Springage model low low low
The Chesser model high high high
The Irkutsk model 90-100% 60-80% 90-100%
The Lis model unstable unstable unstable
The Zaitseva model - high high
The model of Saifulin and Kadykov sustainable insufficient insufficient
It is possible to explain such a discrepancy in estimates because it is incorrect to spread the data obtained for some specific samples that were used to build the model for the whole of the general set of enterprises and organizations, that is, the patterns that are inherent in one sample cannot mechanically extend to other samples. Therefore, it is necessary to build models taking into account the specifics of the organizational forms of enterprises, their industry accessory, the actual state of development of the economy of a particular country or region, taking into account the established regulatory framework and many other internal and external factors. Secondly, each model has its own measurement scale to assess the risk of bankruptcy probability, and the gradations of these scales in a number of cases differ significantly not only in terms of quantitative characteristics, but also in the number of gradations themselves. Such a spread in the estimates may impose a
negative impact on the results of forecasting the bankruptcy of enterprises. With this in mind, it is advisable to further investigate the problem of unification of scales for measuring the level of probability of bankruptcy of organizations, to carry out their taring and to justify the normative values of complex indices of bankruptcy of organizations.
Foreign models were built on obsolete data and do not take into account the specifics of the development of our economy, because of what they are not able to adequately reflect the real situation in the financial and economic activities of domestic organizations. Therefore, they should not be used in Russia without preliminary testing on experimental data, and they can only be used as an auxiliary analysis tool. In this regard, it should be noted that there is a need to develop a single methodological approach in assessing the risk of bankruptcy of domestic organizations on the basis of various
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approaches that ensure high reliability of the results obtained.
References:
1. Comprehensive economic analysis of economic activity: textbook / L. G. Gilyarovskaya [and others]. M., 2016.
2. Management of the financial condition of the organization (enterprise): studies. benefit / under total.
ed. E. I. Krylov, V. M. Vlasova, I. V. Ivanova. M., 2017.
3. Accounting and analysis of bankruptcies: studies. manual / L. V. Popova, I. A. Maslov. M., 2015.
4. Accounting and analysis of bankruptcies: studies. allowance. Ed. 3rd, rev. and add. / ed. I. G. Kukina. M., 2018.
Серебрякова Т.А.,
Кандидат экономических наук, доцент, Тихоокеанский государственный университет в г. Хабаровске
Серебряков В.Г., Старший преподаватель, Тихоокеанский государственный университет в г. Хабаровске
Алексин К.В. ORCID: 0000-0001-8657-7334, магистр, Тихоокеанский государственный университет в г. Хабаровске
СРАВНИТЕЛЬНЫЙ АНАЛИЗ МЕТОДОЛОГИЙ AGILE И WATERFALL ПО РАЗРАБОТКЕ ИНФОРМАЦИОННЫХ СИСТЕМ В БАНКОВСКОЙ СФЕРЕ.
Serebryakova T.A.,
Candidate of Economic Sciences, Associate Professor, Pacific State University in Khabarovsk Serebryakov V.G., Senior Lecturer, Pacific State University in Khabarovsk Aleksin K. V.
ORCID: 0000-0001-8657-7334, Master, Pacific State University in Khabarovsk
COMPARATIVE ANALYSIS OF AGILE AND WATERFALL METHODOLOGIES FOR THE DEVELOPMENT OF INFORMATION SYSTEMS IN THE BANKING SPHERE.
Аннотация
Приведены особенности гибкой и каскадной методологии разработки информационных систем в банковской сфере. Результаты сравнительного анализа методологий Agile и Waterfall показали, что гибкая методология будет только популяризироваться в банковской сфере, поскольку рынок, финансовые тенденции, технологические достижения и конкуренция ускоряют свой темп и требуют результатов и изменений за более короткие сроки.
Abstract
The features of a flexible and cascade methodology for developing information systems in the banking sector are given. The results of a comparative analysis of the Agile and Waterfall methodologies showed that the flexible methodology will only be popularized in the banking sector, as the market, financial trends, technological advances and competition accelerate their pace and require results and changes in a shorter time.
Ключевые слова: проектирование и разработка информационных систем, современные методологии разработки ПО, Agile, Waterfall, банковская сфера.
Keywords: design and development of information systems, modern software development methodologies, Agile, Waterfall, banking.
Гибкая и каскадная методологии разработки информационных систем (Agile и Waterfall соответственно) — одни из наиболее популярных среди прочих методологий разработки программного обеспечения. Но достаточное количество банковских организаций при разработке информационных систем используют каскадную модель, не зная или не понимая гибких моделей. Поэтому в данной работе будет рассмотрен сравнительный анализ двух методологий. Перед тем как перейти к анализу, необходимо дать определения каждому подходу.
Гибкая методология разработки (англ. Agile) — серия подходов к разработке программного обеспечения, ориентированных на использование итеративной разработки, динамическое формирование требований и обеспечение их реализации в результате постоянного взаимодействия внутри самоорганизующихся рабочих групп, состоящих из специалистов различного профиля [1].
Каскадная методология (англ. Waterfall) — модель процесса разработки программного обеспечения, в которой процесс разработки выглядит как
