The arbitration manager is a highly paid and sought-after type of professional activity

The question of employment, the choice of the type of professional activity arises before any person who is looking for a new job, or is trying to find a job, or is preparing for dismissal, including from law enforcement agencies.

How to adapt and find a job in the conditions of unemployment in a new place? How to get a highly paid, and not least, a prestigious and sought-after profession in the labor market?

In Russia, practitioners, managers and employees of commercial organizations, banks, employees of government agencies, employees of law enforcement agencies and law enforcement agencies constantly ask themselves these questions, striving to improve the quality of their lives, to career growth, to improve their well-being.

Trying to understand these difficult issues, we decided to tell our readers about such a highly paid, sought-after, but obscure profession for many Russians as arbitration manager.

And today we are having our conversation with the Deputy Director of the Private Educational Institution of Additional Professional Education (PHOU DPO) "Academy of Personal Security", Candidate of Economic Sciences, Associate Professor, Honorary Worker of Higher Education of the Ministry of Education of the Russian Federation Perfiliev Alexander Borisovich, having rich experience in training arbitration managers .

Alexander Borisovich, at the beginning of our conversation, let's clarify the essence of the very concept of "arbitrator" and determine its possible legal status.

The arbitration manager in the exercise of his powers, first of all, relies on the norms and provisions of the Federal Law "On Insolvency (Bankruptcy)" dated October 26, 2002 No. 127-FZ, in Art. 2 of which it is said that “an arbitration manager is a citizen of the Russian Federation who is a member of a self-regulatory organization of arbitration managers.” At the same time, it must be understood that, depending on the types of bankruptcy procedures being carried out, the status of an arbitration manager may be different.

In the event of a bankruptcy proceeding such as observation» the arbitration manager acquires the status of "interim manager", when conducting the procedure " financial recovery» he acquires the status of "administrative manager", and if a procedure is introduced with respect to an insolvent debtor " external management”, then in this case the arbitration manager acquires the status of “external manager”.

When the case against an insolvent debtor reaches bankruptcy, that is, a procedure is introduced "competitive production" and the mechanism for the sale of his property is launched, then the arbitration manager acquires the status of a “bankruptcy manager”.

Well, if a bankruptcy procedure has been initiated in relation to an insolvent citizen, then the arbitration manager acquires the status of " financial manager».

Here it is appropriate to note that the introduction of a particular bankruptcy procedure in relation to an insolvent debtor and the appointment of a particular candidate as an arbitration manager is carried out by the Arbitration Court of the Russian Federation, and accordingly, we can say that the arbitration manager this is the legal representative of the Arbitration Court carrying out bankruptcy proceedings.

Please tell me, Alexander Borisovich, how much are arbitration managers in demand on the labor market in modern Russia?

Judge for yourself. Over the past two decades in our country, the Arbitration Courts of the Russian Federation annually recognize from 30 thousand to 80 thousand organizations of various forms of ownership as financially insolvent (bankrupt), as evidenced by the statistics of the Arbitration Court itself, published on its official website.

In addition, it is necessary to take into account the fact that, starting from October 15, 2015, amendments to bankruptcy legislation regarding the bankruptcy of citizens (individuals) came into effect, and according to preliminary estimates of specialists, in the coming years they will be recognized as financially insolvent, and even bankrupt from 800 thousand. before 1.2 million Russians, in respect of which the relevant bankruptcy procedures will be carried out - the procedure for "debt restructuring" or the procedure for "realization of property".

At the same time, one cannot fail to note the aspect that mass processes associated with the bankruptcy of individuals have already begun, and the fact that citizens and individual entrepreneurs who have lost the opportunity to fully pay off loans, who have lost the ability to repay debts to business partners in a timely manner, debts for mortgages and housing and communal services, they themselves seek to initiate an appropriate bankruptcy procedure against themselves.

This, strange at first glance, circumstance is due to the fact that if the arbitration financial manager competently, observing all the requirements of the law, conducts such a bankruptcy procedure as “realization of property” against a citizen, then all debts of a citizen, even if they reach millions of values , will be “written off” from him by the decision of the Arbitration Court and he will not owe anything to anyone.

Of course, in all these cases, bankruptcy procedures for legal entities and individuals are carried out and will be carried out, which last from six months to 2 years, only by representatives of the Arbitration Court of the Russian Federation - arbitration (temporary, administrative, external, competitive and financial) managers.

At the same time, it should be borne in mind that there are about 12,000 arbitration managers currently practicing in Russia. Based on the number of initiated insolvency (bankruptcy) cases and the number of active arbitration managers, it is not difficult to conclude that the modern labor market is in need of tens of thousands of trained arbitration managers, and this need is only growing.

Alexander Borisovich, this may be the most important question for our readers: “What is the salary of an arbitration manager”?

First of all, I want to clarify that the arbitration manager does not receive a salary, but a monetary reward, the amount of which is established not by the director of a financially insolvent organization, not by creditors, not by a bankrupt citizen, but directly by the Arbitration Court.

Moreover, the monetary remuneration of the arbitration manager is formed from two components- from fixed amounts which is paid monthly throughout the course of the bankruptcy proceedings, and from the sum paid to the anti-crisis manager upon completion of a particular bankruptcy procedure.

When setting the amount of the monetary reward, the Arbitration Court of the Russian Federation, of course, is guided by the norms set forth in Art. 20.6 of the Federal Law "On Insolvency (Bankruptcy)" dated October 26, 2002 No. 127-FZ, which reflects the minimum amount of a fixed amount of remuneration for an arbitration manager established during the relevant bankruptcy procedure.

In particular, the minimum fixed amount of remuneration is for:

temporary manager - 30 thousand rubles per month;

administrative manager - 15 thousand rubles per month;

external manager - 45 thousand rubles per month;

bankruptcy trustee - 30 thousand rubles a month;

financial manager - 25 thousand rubles at a time.

The second part of the reward, paid to the arbitration manager upon completion of a particular bankruptcy procedure, is calculated in percentages from the value of the property of an insolvent organization or from the amount of repaid debts.

I draw your attention to the fact that the second part of the remuneration, which is completely legally received by the arbitration manager who has completed the bankruptcy procedure, very significant and can reach tens of thousands, or even several hundred thousand rubles. The curious and interested reader himself can determine the amounts of the second part of the remuneration of the arbitration manager by looking, using the Internet, in paragraphs. 9-13 Art. 20.6 of the Federal Law "On Insolvency (Bankruptcy)" dated October 26, 2002 No. 127-FZ.

Determining the income that a practicing arbitration manager may have, it cannot be said that an experienced anti-crisis manager can simultaneously carry out several bankruptcy procedures for various legal entities and several bankruptcy procedures for individuals.

It is quite clear that the total monetary reward of such an experienced arbitration manager can be very significant, even by the standards of the capital.

The following questions follow from the logic of our conversation: “Who can obtain the status of an arbitration manager and what professional requirements are placed on him”?

The main professional requirements for arbitration managers are defined in Art. 20 of the Federal Law "On Insolvency (Bankruptcy)" dated October 26, 2002 No. 127-FZ, which states that a person who can become an arbitration manager must:

1. Be a citizen of the Russian Federation.
2. Have a higher (no matter what, but higher) education.
3. Pass a theoretical exam on the "Unified training program for arbitration managers".
4. Be a member of one of the self-regulatory organizations of arbitration managers.
5. Have at least one year of senior management experience.
6. Complete an internship as an assistant arbitration manager in a bankruptcy case for at least two years.
7. Not to be punished in the form of disqualification for committing an administrative offense or in the form of deprivation of the right to hold certain positions or engage in certain activities for committing a crime.
8. Not have a criminal record for an intentional crime.
9. Alexander Borisovich, the next question is also ripe: “Where can I get training and pass a theoretical exam in the training program for arbitration managers”?

First of all, I would like to draw your attention to the fact that, in accordance with the requirements of Decree of the Government of the Russian Federation of May 28, 2003 N 308, the state theoretical exam in the "Unified training program for arbitration managers" is conducted by the Federal Service for Registration, Cadastre and Cartography of the Russian Federation (Rosreestr) together with teachers and on the basis of the educational institution in which the student studied. True, when submitting a corresponding application to the Rosreestr, the state theoretical exam can be assigned to applicants for passing the exam directly in the region in which they live.

But, in order for a candidate to be allowed to pass such a theoretical exam, he must first undergo professional retraining and successfully master the “Unified Training Program for Arbitration Managers”, approved by order of the Ministry of Economic Development dated December 10, 2009 No. 517.

Moreover, it should be noted that Rosreestr takes the state exam only for students of those educational institutions that have “Agreements on cooperation in the field of training (retraining) of arbitration managers” concluded with it.

Judging by the information posted on the website of the Federal Service for Registration, Cadastre and Cartography of the Russian Federation, the number of educational institutions in Russia that have concluded a "Cooperation Agreement ..." is no more than a hundred.

Such an “Agreement on cooperation in the field of training and retraining of arbitration managers” is also provided by the Private Security Academy, where I work.

A distinctive feature of teaching the "Unified training program for arbitration managers" in the Private Security Academy is that the entire educational process takes place remotely, using the Internet, e-mail, webinars and recorded video lectures.

As my practice shows , a modern educated person in the twentiethIcentury, in the age of information technology, simply does not want, or even does not have the opportunity to study, sitting at a desk 2-3 evenings a week for 3 months, while training courses for arbitration managers last.

Usually students of professional retraining courses, including potential arbitration managers, located anywhere in the world, wish to study in modeson- lineoroff- linelooking at monitors their favorite computers and reviewing the learning material at their convenience as many times as they see fit.

When deciding on training, your readers need to be aware that training under the “Unified Training Program for Arbitration Managers”, approved by order of the Ministry of Economic Development of December 10, 2009 No. 517, is paid in all educational institutions.

In the PEI DPO "Academy of Personal Security", the tuition fee for this academic year is set at 28 thousand rubles. for one listener. True, the cost of training sometimes changes, which can be found out by “going” to our website.

The issue of future employment is particularly acute for officers preparing for dismissal and for members of their families. Officers transferred to the reserve, as a rule, are healthy, have rich practical experience in managerial activities, have a higher education, but it is difficult for them to adapt and find a job in the so-called "citizen". I can judge this from my own experience - after 23 years of service in the Russian Armed Forces, having retired with the rank of lieutenant colonel, I had to "taste all the delights" of finding a decent job. There was only one conclusion - only professional retraining, only an increase in the level of one's own competencies, and not personal acquaintances and so-called "connections", will allow one to find a decent job.

Taking into account the fact that during the development of the "Unified Program for the Training of Arbitration Managers" students study a wide range of issues and topics related to: legal support for entrepreneurial activity; bankruptcy laws; taxation of legal entities and individuals; accounting and reporting; analysis of the financial condition of organizations; evaluating the effectiveness of investment projects; appraisal activity, etc., I would recommend mastering this program for employees of financial and economic structures, and practicing lawyers, and heads of organizations.

And especially to managers, since it is they who are responsible for the results of the financial and economic activities of the organizations entrusted to them, and it is they who, in the event of the loss of the solvency of their firms, can bear both material and administrative, as well as criminal liability for fictitious, deliberate bankruptcy, and for illegal actions during bankruptcy proceedings.

Of course, I recommend training under this program to bank employees, employees of insurance companies, and representatives of microfinance organizations, where the risk of bankruptcy, and, accordingly, the risk of dismissal is very high.

In my opinion, having mastered the “Unified training program for arbitration managers” in 3 months and having received a diploma on professional retraining in the field of anti-crisis management, both unemployed people and university graduates will significantly increase their chances of finding a job.

When deciding to study under this program, students, in my opinion, should not pay attention to their initial basic higher education - anyone with a higher education can master this program.

As my practice shows, not only people with a higher legal or economic education, but also engineers, and former military personnel, and military pilots, and, to my surprise, people with a higher medical education, work very successfully as arbitration managers.

Upon completion of professional retraining, persons receive a Diploma of Professional Retraining (see Diploma form).

If your readers have any questions, feel free to contact me using my personal e-mail: or phone 8-915-969-60-12

Perfiliev A.B.

1

The diversity and diversity of anti-crisis measures makes it difficult to identify the most effective and efficient ways to overcome the crisis. The development of a model of anti-crisis personnel management and its inclusion in the activities of the management system is due to the crisis itself and the subsequent decline in economic indicators and development prospects. The essence of anti-crisis personnel management, including employees, employers and other owners of the enterprise, is to establish the main factors for the effectiveness of management in a crisis. These relations are based on the principles, methods and forms of influence on the interests, behavior and activities of employees in order to maximize their use. The anti-crisis management model is associated with the disclosure of the necessary potentials of the individual and includes professional and personal blocks.

control

anti-crisis personnel management

crisis response model

professional and personal potential

1. Gutsykova S.V. Interrelation of integrative professionally important qualities and personal characteristics of specialists with different performance efficiency: Ph.D. dis. ... cand. ps. Sciences. - M.: Institute of Psychology of the Russian Academy of Sciences, 2012. - 30 p.

2. Zabrodin, Yu.M., Kulapov M.N., Odegov Yu.G. Human psychology and personnel management // Bulletin of the Russian Economic University. G.V. Plekhanov. - 2005. - No. 2. - P. 53-67.

3. Okhotnikov O.V. Philosophical foundations of the personnel policy of the organization // Personnel policy of the organization: scientific notes of the department of personnel management and psychology. - Issue. 1. - Yekaterinburg: UrFU, 2015. - P. 8–19.

4. Ponomareva O.Ya. Application of the competency model as a direction of personnel policy: from theory to practice // Personnel policy of the organization: scientific notes of the department of personnel management and psychology. - Issue. 1. - Yekaterinburg: UrFU, 2015. - S. 29–39.

5. Prozorova, O.N. "Psychology of the self" by E. Erickson and V. Frankl's logotherapy in personnel management: a comparative analysis // Actual problems of the humanities. - Tomsk, 2013. - S. 269-271.

6. Ryabov O.A. Modeling of processes and systems: a tutorial. - Krasnoyarsk, 2008. - 122 p.

7. Smirnov V.K. Psychology of personnel management in extreme conditions: textbook. - M., 2007.

8. Tokareva Yu.A. Management consulting as an element of system personnel policy // Personnel policy of the organization: scientific notes of the department of personnel management and psychology. - Issue. 1. - Yekaterinburg: UrFU, 2015. - S. 148–155.

At the present stage of development of the psychological side of economic processes, the problem of developing a model of anti-crisis personnel management, which reveals the idea of ​​maintaining a stable social form during the economic crisis experienced by Russia, is being actualized. Along with the fact that such developments are not uncommon for research work in the field of personnel management, the great merit of scientists is to pay attention to the analysis of the psychological component of the activities of personnel management services (A.P. Gradov, Yu.M. Zabrodin, O. N. Prozorova, V. K. Smirnov and others). The psychology of management and the task of psychological modeling associated with it is just beginning to be developed by the domestic psychological school, and a significant contribution to this area is made by studies containing guidelines necessary for understanding the processes of the personnel component of enterprises (O.E. Alekhina, Yu.I. Bogdanov, T.Yu. Bazarov, A. Ya. Kibanov, O. V. Okhotnikov and others). Modeling the process of anti-crisis management, including the development of the professional and personal potential of the personnel of the enterprise, is based primarily on the established didactic essence and features of this process, which have their own specifics during the period of reforms and social crises (T.K. Kovalenko, O.A. Ryabov , Yu.A. Tokareva, A.E. Fedorova and others).

A model is understood as such a mentally represented or materially realized system that, displaying or reproducing the object of study, is able to replace it so that its study gives us new information about this object. The basis of the anti-crisis personnel management model is the development of the professional and personal potential of employees through psychological technologies, various forms, methods, principles, criteria, components, functions and educational modules.

Considering the existing developments in the field of anti-crisis management based on the personal and professional implementation of a specialist, by now the contradictions between:

Numerous research works that reveal the issues of professional activity in conditions of crises and stress and the requirements for its implementation, and insufficient representation of works that characterize the idea of ​​the integrity of personal and professional readiness to solve problems of an increased level of complexity;

The multidimensionality of the knowledge of the problem of anti-crisis management and the fragmentation of studies that study the professional and personal side of a specialist, the psychological aspect of its implementation in a crisis;

The need to model the process of anti-crisis management, taking into account the professional and personal component of the development of a specialist and the fragmentation of ideas about targeted models of personnel development in a crisis.

The search for ways to resolve these contradictions determined the problem of our study, which theoretically consists in developing a model of anti-crisis personnel management in a socio-economic crisis based on personal and professional potential, taking into account its structural organization and content, which ensures the successful implementation of professional activities.

The theoretical basis for modeling anti-crisis personnel management based on professional and personal potential are works in the field of scientific modeling (B.V. Biryukov, V.A. Venikov, Yu.A. Gastev, E.S. Geller, O.Ya. Gelman, A. .I. Uemov, V.V. Chavchanidze, V.A. Shtof and others), modeling in psychology (P.K. Anokhin, N.A. Bernstein, V.P. Zinchenko, I.M. Kondakov, B .G. Meshcheryakov and others).

Modeling as a method of scientific knowledge is based on similarity, in which not the object itself is studied, but its analogue, its substitute, and then the results obtained during the study of the model are extrapolated to the object under study. The model can be objectively built and implemented only taking into account the mission, goals and strategy of anti-crisis response, because at its core, is an ideal model of a specialist who can be effective in conditions of professional stress and crisis.

The actualization of the model of anti-crisis personnel management will be complete if a number of external (created by a psychologist) and internal (depending on a specialist) conditions are observed:

1. A systematic approach, which consists in the mandatory participation, in a crisis, of all components of professional and personal potential. In personal: cognitive, emotional and behavioral. In the professional: motivational-need, executive and control-evaluative.

2. A facilitative approach associated with adequate psychological tactics for updating personal resources, since this approach focuses on creating conditions for the individual and collective realization of all components of personal potential in a crisis.

3. Responsible attitude to the process of anti-crisis response. The model will be effective only if the professional himself is aware of the degree of responsibility for the actions taken, wants to make efforts and efforts to his own development and level of professionalism.

An analysis of existing developments in the field of psychological modeling and support made it possible to form a number of clear guidelines for theoretical modeling of anti-crisis management:

1) the personal level comes to the fore, i.e. not a ready-made set of professional skills and abilities, but personal and organizational activities, the ability of a specialist to "grow" by solving complex problems, the ability to analyze one's personal qualities, to find conditions for personal growth;

2) the professional level is associated with the ability to quickly create, "design" a way out of the current crisis situation using one's own professional competencies. The implementation of a professional level is associated with the availability of new knowledge and professional skills in a specialist in accordance with the requirements of the market situation.

The generalization of the conducted studies allows us to state that the process of anti-crisis response requires the following set of personal and professional qualities and progressive structural changes in the personality:

1. Changing the direction of the personality:

Expanding the circle of interests and changing the system of needs;

Actualization of achievement motives;

Increasing need for self-realization and self-development.

2. Increasing experience and advanced training:

Increasing competence;

Development and expansion of skills and abilities;

Mastering new algorithms for solving professional problems;

Increasing the creativity of activities.

3. Development of complex private abilities.

4. Development of professionally important qualities determined by the specifics of the activity.

5. Development of personal and business qualities.

6. Increasing psychological readiness for professional activities under stress. It is known that human activity as a conscious form of diverse behavioral activity is determined not only by the professional qualities of the subject, but also by his personal characteristics.

Rice. 1. Model of anti-crisis personnel management in the conditions of socio-economic crisis

Based on the principles of systemic and activity approaches in the development of the model, it is possible to single out structural elements that make it possible to qualitatively assess both the content and the nature of the psychological readiness of the personnel in terms of personal and professional response. Thus, personal response and readiness to resist crisis processes includes: the cognitive component - contains a body of knowledge about oneself as a professional, about global trends in professional activities, which allow one to withstand and effectively overcome various, including stressful situations. The cognitive component determines the effectiveness of professional activity both independently and in a team. During the period of social overcoming, the structure of the cognitive component undergoes changes with the accumulation of the necessary knowledge, skills, and includes the representation of oneself in difficult situations, knowledge about oneself as a person, one's strengths and weaknesses, one's attitudes, abilities; emotional component - awareness of signs of emotional comfort, understanding of signs of emotional tension, internal readiness to experience certain professional situations, the ability to empathize, sympathize, express and understand the emotions of others; behavioral - practicality, independence, confidence, allowing you to make decisions independently, the implementation of individual preferences in choosing behavior strategies in problematic situations of social interaction, the formation of certain skills that allow you to successfully complete professional tasks, the ability to adequately express yourself in unexpected situations, the ability to control and manage your reactions . Vocational education includes: a motivational-need component - the leading determinants of professional activity, the desire to realize oneself in a situation of instability, individual activity, awareness of the need for self-development; executive component - the presence of formed skills related to professional activities, the ability to apply them in practice; control and evaluation - a conscious attitude to the results of one's professional behavior, professional development, the ability to evaluate and adjust individual personal and professional skills, planning and achieving a higher level of professionalism and competence.

The problem of modeling the anti-crisis process, taking into account the professional and personal potential of the staff, is a modern formulation of questions traditional for psychology about psychological criteria, about the relationship between personal and professional.

Rice. 2. Model of professional and personal potential of anti-crisis regulation

In our opinion, personal qualities form an important foundation for the professional success of a specialist. Taking into account the professional and personal qualities, the peculiarities of their professional activity, we can say that the successful behavior of a specialist will depend on the consistent achievement of a professional and personal potential sufficient for anti-stress regulation.

Reviewers:

Bannikova L.N., Doctor of Social Sciences, Professor of the Department of Sociology and Social Technologies of Management, Ural Federal University named after the first President of Russia B.N. Yeltsin, Yekaterinburg;

Vasyagina N.N., Doctor of Psychology, Professor, Head of the Department of Educational Psychology, Ural State Pedagogical University, Yekaterinburg;

Kozlova OA, Doctor of Economics, Professor, Head of the Center for Research on Socioeconomic Dynamics, Institute of Economics, Ural Branch of the Russian Academy of Sciences, Yekaterinburg.

Bibliographic link

Tokareva Yu.A., Kovalenko T.K. MODEL OF ANTI-CRISIS PERSONNEL MANAGEMENT OF AN ENTERPRISE DURING THE SOCIO-ECONOMIC CRISIS // Fundamental Research. - 2015. - No. 8-3. – S. 616-619;
URL: http://fundamental-research.ru/ru/article/view?id=38951 (date of access: 01/05/2020). We bring to your attention the journals published by the publishing house "Academy of Natural History"

Bankruptcy diagnostics is a system of targeted financial analysis aimed at identifying the parameters of the crisis development of an enterprise that generate the threat of its bankruptcy in the coming period.

Depending on the goals and methods of implementation, the diagnostics of the bankruptcy of an enterprise is divided into two main systems:

• 1) a system of express diagnostics of bankruptcy;
• 2) a system of fundamental diagnostics of bankruptcy.

The system of express diagnostics of bankruptcy provides early detection of signs of the crisis development of the enterprise and allows you to take prompt measures to neutralize them. Its preventive effect is most noticeable at the stage of a slight financial crisis of the enterprise.

The main objectives of the fundamental diagnostics of bankruptcy are:

• - deepening the results of assessing the crisis parameters of the financial development of the enterprise, obtained in the process of express diagnostics of bankruptcy;
• - confirmation of the obtained preliminary assessment of the scale of the crisis financial condition of the enterprise;
• - forecasting the development of individual factors that generate the threat of bankruptcy of the enterprise, and their negative consequences;
• - assessment and forecasting of the enterprise's ability to neutralize the threat of bankruptcy due to internal financial potential.

There are two main approaches to predicting bankruptcy.

The first is based on financial data and involves the operation of some coefficients: the increasingly famous Altman Z-factor (USA), the Taffler coefficient (UK), and others.

The second one starts from data on bankrupt companies and compares them with the corresponding data of the company under study.

In the West, the method of E. Altman, proposed by him in 1968, is widely used to predict the probability of bankruptcy. - multiple discriminant model that takes into account the action of the five most significant factors:

X 1 - liquidity indicator (working capital / total assets);

X 2 - profitability indicator (retained earnings / total assets);

X 3 - sustainability indicator (income before taxes and interest / total assets);

X 4 - solvency indicator (market value of shares / book value of debt obligations);

X 5 - activity indicator (sales volume / total assets).

The Altman model has the following form:

Z = 1.2X 1 + 1.4X 2 + 3.3X 3 + 0.6X 4 + 0.999X 5

The results of numerous calculations using the Altman model showed that the generalized indicator Z can take values ​​ranging from -14 to +22, while enterprises for which Z > 2.99 fall into the category of financially stable, and enterprises for which Z< 1,81 - безусловно несостоятельных; интервал 1,81 - 2,99 составляет зону неопределенности.

The British scientist Taffler proposed a four-factor predictive model of the species (formula 16):

Z = 0.53x1 + 0.13x2 + 0.18x3 + 0.16x4 (16)

where x 1 - the ratio of profit from sales to short-term liabilities;

x 2 - the ratio of current assets to the amount of liabilities;

x 3 - the ratio of short-term liabilities to the amount of assets;

x 4 - the ratio of revenue to the amount of assets.

With a value of Z greater than 0.3, the company has good long-term prospects, with a value of Z less than 0.2, bankruptcy is more than likely.

There is also a model for predicting the probability of bankruptcy, developed by scientists from the Irkutsk State Academy of Economics (formula 17):

Z = 8.38K 1 + K 2 + 0.54K 3 + 0.63K 4 (17)

where K 1 - the ratio of working capital to assets;

K 2 - the ratio of net profit to equity;

K 3 - the ratio of proceeds from sales to assets;

To 4 - the ratio of net profit to integral costs.

Russian discriminant bankruptcy forecasting models are represented by a two-factor model by M.A. Fedotova and the five-factor model of R.S. Saifulina, G.G. Kadykov.

Bankruptcy Probability Estimation Model M.A. Fedotova is based on the current liquidity ratio ( X 1 ) and the share of borrowed funds in the balance sheet currency (X 2 ):

Z = -0.3877-1.0736 X 1 + 0,0579 X 2 .

With a negative index value Z it is likely that the company will remain solvent.

R.S. equation Saifulina, G.G. Kadykova looks like:

Z = 2.x 1 +0,1X 2 +0,08X 3 +0,45X 4 +X 5 ,

where x 1 - coefficient of provision with own funds (normative value X G >0,1);

X 2 - current ratio (X 2 >2);

X 3 - the intensity of the turnover of the advanced capital, characterizing the volume of sales per 1 rub. funds invested in the activities of the enterprise (x 3 > 2.5);

X 4 - management ratio, calculated as the ratio of profit from sales to revenue;

X 5 - return on equity (x 5 >0.2).

With full compliance of the values ​​of financial ratios with the minimum standard levels, the index Z equals 1. The financial condition of an enterprise with a rating number less than 1 is characterized as unsatisfactory. The disadvantages of such models are the overestimation of the role of quantitative factors, the arbitrariness of the choice of a system of basic quantitative indicators, high sensitivity to the distortion of financial statements, etc.

To diagnose the financial condition of an enterprise in the anti-crisis management system, various domestic and foreign methods are used, each of which has certain features and disadvantages. Different methods of predicting bankruptcy actually predict different types of crises. It seems, however, that none of the methods can claim to be used as a universal one precisely because of "specialization" in any one type of crisis. Therefore, it seems appropriate to track the dynamics of changes in the resulting indicators for several of them. The choice of specific methods, obviously, should be dictated by the characteristics of the industry in which the enterprise operates. Moreover, even the methods themselves can and should be subject to adjustment taking into account the specifics of industries.

Thus, based on the study and analysis of literary sources, the following conclusions can be drawn.

Anti-crisis management is the process of applying forms, methods and procedures aimed at the socio-economic improvement of the financial and economic activities of an enterprise, the creation and development of conditions for overcoming a crisis.

Like any socio-economic system, the enterprise strives for sustainability. However, external and internal factors force him to constantly adapt, adapt to new conditions and situations. A crisis in an enterprise occurs when the existing business structure cannot adapt to the changed operating conditions. As a result, the work of the existing system is disorganized, but at the same time, the prerequisites for a new system appear.

In anti-crisis management of an enterprise, diagnostics of the financial condition of an enterprise plays an important role. Financial condition is a characteristic of the economic activity of an enterprise in the external environment. The main task of diagnosing the financial condition of an enterprise is to determine the quality of the financial condition of an enterprise, as well as to determine the reasons for its improvement or deterioration; further, as a rule, recommendations are prepared on the solvency and financial stability of the enterprise.

To date, the world practice has developed quite stable approaches to the analysis of the financial statements of enterprises and the formation of conclusions and recommendations based on the results of the analysis. The methods used in this process can be divided into four groups: transformational, qualitative, coefficient and integral.

The profitability of the enterprise is directly related to the financial condition. If the solvency of an enterprise mainly depends on the turnover of assets, then financial stability depends on profitability, since equity is replenished from profits.

Under the conditions of increasing competition, economic instability, declining solvency of the population and business entities, diagnostics of the financial condition of CJSC "XXX" is of particular importance in order to develop directions for the further development of the organization. As part of the anti-crisis management of an enterprise, it is necessary to conduct a financial analysis, which will include: analysis of working capital; assessment of the need for advanced capital; analysis of the need for equity capital; capital structure analysis; analysis of the validity of the policy of distribution and use of profits; investment feasibility analysis; business and financial risk analysis, etc.

Muzlova Victoria Andreevna, Butrina Yulia Vladimirovna
1. Higher Master student of the faculty "Higher School of Economics and Management"
2. Candidate of Economics, Associate Professor of the Department of Finance, Money Circulation and Credit
South Ural State University, Chelyabinsk

Muzlova Victoria Andreevna
1. Master student of the faculty "Higher school of Economics and management"
South Ural State University, Chelyabinsk
2. c.e.s., assistant professor of the pulpit "Finance, monetary circulation and credit"
South Ural State University, Chelyabinsk

Annotation: In modern conditions of economic instability of the banking sector, the issue of assessing the financial stability of the bank is of particular importance. The growth of banking risks worsens the problem of maintaining the financial stability of the bank, turning this problem into one of the most relevant theoretical and practical aspects of the modern economy. Therefore, there is a need to create such a model with the help of which the bank will be able to accurately assess its financial stability.
The article describes the main stages of creating an author's model for assessing the financial stability of a bank based on economic and mathematical modeling.

abstract: In modern conditions of economic instability of the banking sector, the issue of assessing the bank's financial stability becomes particularly important. The growth of banking risks worsens the problem of maintaining the financial stability of the bank, turning this problem into one of the most relevant theoretical and practical aspects of the modern economy.
The article describes the main stages of creating an author's model for assessing the bank's financial stability on the basis of economic and mathematical modeling.

Keywords: bank financial stability, financial stability factors, correlation, multivariate regression model, regression equation, Student's t-test, Fisher's test, multicollinearity.

keywords: financial stability of the bank, financial stability factors, correlation, multifactorial regression model, regression equation, Student's t-test, Fisher criterion, multicollinearity.

An objective and accurate assessment of the bank's financial stability is an integral part of ensuring its competitiveness, increasing the potential for business cooperation, and assessing the extent to which its economic interests are guaranteed. That is why banks need a model that will allow them to make an accurate assessment of financial stability in a timely manner.

At present, modeling is an effective technique for understanding the essence of the phenomena being studied. Since it makes it possible to get a clear idea of ​​the object under study, allowing a quantitative description of its internal structure and external relations, acting as the main tool for financial analysis, and it is also actively used in practice to predict bankruptcy. The main task of modeling is to construct a model based on its preliminary study and selection of essential characteristics, on the basis of which modeling will be carried out.

The development of a multi-factor regression model for assessing financial stability will be carried out in five stages, a brief description of which is presented in table 1 below.

Table 1

Stages of developing a multivariate regression model

Stage	Brief description of the stage
The first stage is the selection of factors.	The first stage is the selection of factors that formed the basis of financial analysis. When selecting factors, the main emphasis is placed on the definition of a universal integral criterion or the resulting indicator Y.
The second stage is bringing the data to a reliable form.	All selected factors were expressed as a percentage using mathematical transformations. This stage of the study made it possible to determine the composition of the sample that satisfies the requirement of representativeness, homogeneity and integrity.
The third stage is the development of a multivariate regression model.	The main task is to determine a number of top-priority financial indicators needed for further use in the model development process. One of the mandatory requirements for factors is the absence of intercorrelation (i.e., correlation between explanatory variables) and an exact functional relationship between them. The inclusion of factors with high intercorrelation in the model may lead to undesirable consequences - the system of normal equations may turn out to be ill-conditioned and lead to instability and unreliability of estimates of regression coefficients. If there is a high correlation between the factors, then it is impossible to determine their isolated influence on the performance indicator, and the parameters of the regression equation turn out to be uninterpretable. After that, all factors should be checked for the presence multicollinearity, when more than two factors are interconnected by a linear relationship, therefore, there is a cumulative effect of factors on each other. As a result, the variation in the original data is no longer completely independent, and it is impossible to assess the impact of each factor separately. As a result of the transformations, we bring the model to the form we need, after which we perform a regression analysis.

Since traditionally, the assessment of the financial stability of a bank involves the use of a certain set of indicators, which we grouped as follows:

– capital adequacy ratios ( X1);

– liquidity indicators ( X2);

– indicators characterizing the quality of assets ( X3);

– profitability indicators ( X4);

– profitability indicators ( x5);

Calculation of the resulting indicator ( Y) was produced using the formula:

However, since the evaluation of some indicators includes a number of specific coefficients, therefore, there is a need to convert them to one indicator.

For example, liquidity assessment occurs by fulfilling liquidity ratios through the determination of coefficients, such as the instant liquidity ratio, current liquidity and long-term liquidity.

With the help of mathematical transformations, we bring the model to the form we need. Thus, we obtain the following data presented in Table 2.

table 2

The main indicators of the bank's financial stability.

	Indicators	2015		2016 2016
		1st half	2 semester	1st half	2 semester
X1	Capital adequacy, %	12,67	11,87	11,81	11,80
X2	Liquidity, %	128,23	123,90	117,32	133,31
X3	Asset growth rate, %	93,34	113,13	97,07	99,16
X4	Profit growth rate, %	56,48	163,57	97,10	164,18
x5	Profitability, %	7,67	10,30	19,83	21,27
X6	People's rating	28,0	27,3	26,7	25,9

Banki.ru Analytics information portal http://www.banki.ru/.

As a result, we have received data that satisfies the requirement of representativeness, homogeneity and integrity, therefore, we can begin the process of developing a multivariate regression model.

However, before proceeding with the regression analysis, it is necessary to check the data for multicollinearity.

The requirement for the absence of multicollinearity is due to the fact that if there is a close relationship between the two factors that meet the first three requirements, then there is no need to include both factors in the model, since one can be expressed through the other. In addition, when interrelated factors are imprudently included in one multifactorial model, computational difficulties arise due to the fact that the system of normal equations becomes unsolvable.

Checking for the absence of multicollinearity was carried out using MS Excel formulas and did not reveal multicollinearity of factors.

Thus, after making sure that the data we have identified are correct, we can begin the process of developing the financial stability assessment model itself.

We will build a multiple regression model using correlation-regression analysis.

To identify the dependence of indicators, we will use the capabilities of MS Excel. The simplest form of dependence is linear, that is, a dependence of the form:

It should be determined whether all variables need to be included in the equation, or whether there are variables that do not significantly affect the value of Y and it is not advisable to include them in equation (1).

To calculate the cumulative correlation coefficient, it is necessary to determine the paired correlation coefficients r 0 i between all factors x i included in the model and the resulting indicator at and all pairwise correlation coefficients between factors. All correlation coefficients are written in a square symmetric matrix.

As a result of the conducted multiple correlation, the following correlation coefficients were revealed:

Table 3

Correlation coefficients

Based on the data obtained in the table, it can be concluded that the relationship of factors X1, X2, X3, X4, X5, X6 with a factor Y significant, therefore, all factors are significant.

Thus, the regression equation took the form:

As a result of processing this equation, it is necessary to exclude insignificant factors using the Analysis Package function in MSExcel. It is necessary to carry out regression until all factors are significant.

The result of the analysis of multiple regression showed a high significance of the regression equation, based on the indicator R-squared = 0.986601403

Figure 1. Regression statistics of the main indicators of the bank's financial stability

In the end, we got the following data presented in table 2:

table 2

Assessment of the adequacy of the main indicators of the financial stability of the bank by their successive exclusion

Regression 1
t theor	3,182446305
t calculated	2,409094938	inadequate
t calculatedX1	-1,449843444	inadequate
t calculatedX2	2,488840673	inadequate
t calculatedX3	0,022463051	inadequate
t calculatedX4	9,24292477	adequate
t calculatedX5	11,58373036	adequate
t calculatedX6	1,93536583	inadequate
Regression 2
t theor	2,776445105
t calculated	1,740909057	inadequate
t calculatedX2	1,885216947	inadequate
t calculatedX3	0,69870852	inadequate
t calculatedX4	9,664627508	adequate
t calculatedX5	10,20949772	adequate
t calculatedX6	1,164203243	inadequate
Regression 3
t theor	2,570581836
t calculated	3,668614396	adequate
t calculatedX2	1,87762487	inadequate
t calculatedX4	11,51882755	adequate
t calculatedX5	10,76263218	adequate
t calculatedX6	1,055131849	inadequate
Regression 4
t theor	2,446911851
t calculated	8,486455956	adequate
t calculatedX2	1,556634214	inadequate
t calculatedX4	11,75762476	adequate
t calculatedX5	11,81927966	adequate
Regression 5
t theor	2,364624252
t calculated	28,43433612	adequate
t calculatedX4	11,27183451	adequate
t calculatedX5	12,69145947	adequate

In the course of the correlation-regression analysis, it was found that the most significant indicators are the indicators X4 and x5 These are indicators of profit and profitability. Thus, we can draw the following conclusions that the concept of developing a regression model for assessing the financial stability of a bank was disclosed, which made it possible to obtain a multifactorial regression model that meets the main features that characterize the financial stability of banks and makes it possible to adequately assess the financial stability of any bank.

As a result, the resulting regression model is characterized by:

– firstly, the high quality of estimation from the standpoint of the standard error of the estimate of the free term, which is equal to 0.82%.

- secondly, the significance and reliability of factors from the position of including them in the regression model, which are characterized by the coefficient of determination R 2 = 98.6% and Fisher's F-test, in the analysis of which F calc. >F theor, hence the equation is adequate.

Thus, we will evaluate the financial stability of the bank in the sequence of significant factors, that is, in the sequence in which the factor was excluded. The methodology for assessing financial stability is presented in Table 3.

Table 3

The developed methodology for assessing financial stability

Financial stability indicators of the bank			Brief description of financial stability indicators of the bank
	x5	Profitability	An indicator of the effectiveness of the use of funds or other resources
	X4	Profit	This is a positive financial result of the activity of a credit institution for a certain period of time. The main performance indicator of the bank
	X2	Liquidity	The ability of an asset to be sold quickly with minimal monetary loss associated with the speed of sale
	X6	People's rating	This is an independent assessment of the work of banks, the level of their service and the quality of the services provided. It is formed solely on the basis of votes and user reviews.
	X3	Assets	Various objects in which he places his own and borrowed resources
	X1	capital adequacy	The main standard that all credit organizations must comply with. This is one of the most important indicators of a bank's reliability. It characterizes the bank's ability to offset possible financial losses at its own expense, without harming its customers.

The developed methodology for assessing financial stability will make it possible to determine how stable the bank is, since on the basis of these indicators, the integral coefficient of the financial condition of the bank is calculated, according to which the assessment will be made.

The calculation of the integral coefficient is made according to the formula:

Table 4

Characteristics of the financial condition of the bank depending on the value of the integral indicator

The value of the integral indicator (U)	Characteristics of the financial condition of the bank
0-15	Unstable: Illiquid balance sheet, i.e. unsatisfactory structure of assets and liabilities; negative financial result; non-compliance with regulations; negative dynamics of financial reporting indicators and others
15-30	With signs of trouble: Short-term deviation from the standards, low profit margins; temporary positive dynamics of financial indicators
30-60	Relatively stable: liquid balance; positive financial result; compliance with regulations; relatively stable resource base; there is a positive trend in financial indicators
60-100	Sustainable: Optimal structure of assets and liabilities; high profit margins; compliance with regulations; positive financial result; stable resource base

As can be seen from Table 4, the integral coefficient has a range of values ​​from 0-100, the larger its value, the better the financial condition of the bank.

0-15 , therefore, the financial condition of the bank unstable.

If the value of the integral indicator is in the range from 15-30 , therefore, in the financial position of the bank there are signs of a problem.

If the value of the integral indicator is in the range from 30-60 relatively stable.

If the value of the integral indicator is greater than 60 , therefore, the financial position of the bank is sustainable.

Thus, a decrease in the value of the integral indicator will mean a deterioration in the financial position of the bank and vice versa. As a result of the data obtained, it will be possible to easily determine your financial situation and, if it turns out to be unstable, carry out a more detailed analysis in time to identify the causes of financial instability.

Bibliographic list

1. Analysis of banks / Banking analyst portal [Electronic resource]. – Access mode: http://analizbankov.ru/index.php
2. Banki.ru Information portal analytics [Electronic resource]. – Access mode: http://www.banki.ru/
3. Bobyl V. Methodology for applying indicators of the risk management system / V Bobyl // Bank Bulletin 2014 [Electronic resource]. – Access mode: https://www.nbrb.by/bv/articles/9999.pdf
4. Voloshchuk L.A., Tkachev S.I., Monina O.Yu. Educational and practical guide / Statistics // Saratov 2016 - P. 140 - 153.
5. Evseeva, A.V. Financial sustainability of the bank, methods of its assessment and ways to improve [Text] / A.V. Evseeva, N.A. Ponomareva // Science, education, society: trends and development prospects: materials of the III Intern. scientific-practical. conf. (Cheboksary, December 11, 2016) / editorial board: O. N. Shirokov [and others]. - Cheboksary: ​​CNS Interactive Plus, 2016. - P. 166–169.
6. Soroka Ya.A. The concept of developing a regression model for analyzing and forecasting the financial condition of industrial enterprises / Ya.A. Soroka // Mathematical and instrumental methods of economics (47) UEKS, 11/2012 [Electronic resource]. – Access mode: http://uecs.ru/uecs47-472012/item/1663-2012-11

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abstract

dissertations for a degree

Fuzzy Modelsin the tasks of anti-crisis management

Specialty 08.00.13

"Mathematical and Instrumental Methods of Economics"

Candidate of Economic Sciences

Suvorov Mikhail Konstantinovich

Ivanovo 2007

The work was carried out at the Vladimir State University.

Scientific Supervisor Candidate of Technical Sciences, Associate Professor

Chernov Vladimir Georgievich

Official opponents Doctor of Economics, Professor

Ilchenko Angelina Nikolaevna

Candidate of Economic Sciences, Associate Professor

Stoyanova Tatyana Alexandrovna

Leading organization Vladimir branch

Russian Academy of Public Administration under the President of the Russian Federation

The defense will take place on April 07, 2007 at ____ hours at a meeting of the Dissertation Council D 212.063.04 at the Ivanovo State University of Chemical Technology (153460, Ivanovo, pr. F. Engels, 7, G 101).

The dissertation can be found in the library of the Ivanovo State University of Chemical Technology.

Scientific Secretary

dissertation council E. Dubova

crisis management forecasting

general description of work

Relevance of the research topic. Modern economic reality forces business leaders to constantly make decisions in the face of uncertainty. Uncertainty becomes a serious barrier on the way to an efficient market, leading to significant expenditure of effort, money, time and energy, and non-optimal distribution of goods and resources. In conditions of financial and political instability, commercial activity is fraught with various crisis situations, the result of which may be insolvency or bankruptcy.

The bankruptcy procedure, the very term "failed enterprise" in the perception of most people is associated with destruction. Declaring an enterprise insolvent means declaring it bankrupt as a fait accompli and excludes any other path than liquidation.

However, this picture is already almost the end of the insolvency process, which by this point in time often lasts several months. But it's not a mandatory ending. Throughout the entire period of time when a bankruptcy case is being heard in an arbitration court, the law gives the company the opportunity to stop this process and choose a different path if there is hope that the company can be saved. In practice, this is exactly what happens for every sixth enterprise, and their own rescue plan is launched for them. This rescue plan is based on the possibility of applying various reorganization procedures provided for by the current legislation.

Thus, it is obvious that there are a number of reorganization procedures applied in case of insolvency. However, there are also a number of related issues of enterprise restructuring. Reorganization procedures are a struggle to save the life of an enterprise that is on the verge of bankruptcy. Unfortunately, it must be recognized that the huge potential inherent in the reorganization procedures has not yet been fully used in practice.

Only the application of a set of methods from various sectors of the economy can today give the necessary economic effect and bring crisis enterprises out of the state in which they are.

The works of such Russian and foreign scientists as Ackoff R., Ansoff I., Balabanov I., Drucker P., Ilyenkova S., Utkin E. and many others are devoted to the general problems of management.

Particular attention should be paid to anti-crisis management. The works of Alexandrov G., Andreev C., Ivanov G., Panagushin V., Gryaznova A., Korotkov E., Blyakhman L. and many others are devoted to solving problems arising within its framework.

But there are very few works devoted to the use of mathematical, instrumental tools and information technologies in the field of anti-crisis management. Some publications focus on the crisis as such, other publications mainly deal with problems descriptively, without algorithms and calculations.

Therefore, there is a need to pay attention to the development of such methods and models that could ensure the adoption of more effective anti-crisis decisions.

Determining the behavior of economic systems over time is becoming more and more popular. Forecasting development requires the ability to anticipate the consequences of an action and create plans that are inherently "preemptive" rather than "corrective." In addition, it is required to be able to analyze situations that cannot be accurately foreseen.

Decision-making problems in complicated conditions currently occupy a special place in information technology. Mathematical methods have become widely used to describe and analyze complex economic, social and other systems. Optimization theory has created a set of methods that help, when using a computer, to make decisions effectively with known and fixed parameters. There are certain successes in the case when the parameters are random variables with known distribution laws.

However, the main difficulties arise when the parameters of the situation turn out to be uncertain and at the same time they strongly influence the results of the solution.

Due to the fact that when building formal models, deterministic methods are most often used, they thereby introduce certainty into situations where it does not actually exist. The inaccuracy of setting certain parameters in the calculations is practically not taken into account or, taking into account certain assumptions and assumptions, unknown values ​​of the parameters are replaced by average values.

Such situations can arise both as a result of insufficient knowledge of objects, and because of the participation in the management of a person or a group of persons. A feature of such systems is that a significant part of the information necessary for their mathematical description exists in the form of ideas or wishes of experts. But in the language of traditional mathematics there are no objects with the help of which it would be possible to operate with fuzzy representations of experts with an acceptable level of rigor.

Conventional quantitative methods for analyzing systems are inherently of little use and are not effective for such systems. This is determined by the so-called principle of incompatibility: the more complex the system, the less we are able to give accurate and at the same time practical judgments about its behavior. For systems whose complexity exceeds a certain threshold level, accuracy and practicality become almost mutually exclusive. It is in this sense that an accurate quantitative analysis in real economic, social and other systems associated with human participation does not provide the required level of validity.

Another approach is based on the premise that the elements of human thinking are not numbers, but elements of some fuzzy sets or classes of objects, for which the transition from "belonging to a class" to "not belonging" is not abrupt, but continuous. Traditional methods are insufficiently suitable for the analysis of such systems, precisely because they are not able to capture the fuzziness of human thinking and behavior. This statement suggests that for models of control processes, fuzzy mathematical methods would be more suitable than classical ones.

The theory of fuzzy (fuzzy) sets was first proposed by the American mathematician Lotfi Zadeh in 1965 and was intended to overcome the difficulties of representing inaccurate concepts, analyzing and modeling systems in which a person participates.

The approach based on the theory of fuzzy sets is, in fact, an alternative to the generally accepted quantitative methods of systems analysis. It has three main distinguishing features:

1. Instead of or in addition to numerical variables, fuzzy values ​​and so-called "linguistic" variables are used.

2. Simple relationships between variables are described using fuzzy statements.

3. Complex relationships are described by fuzzy algorithms.

This approach provides approximate, but at the same time effective ways of describing the behavior of systems that are so complex and poorly defined that they are not amenable to precise mathematical analysis. Before the works of L. Zadeh, such qualitative information was, in fact, simply lost - it was not clear how to use it in the formal schemes of the analysis of alternatives.

The theoretical foundations of this approach are quite precise and rigorous in the mathematical sense and are not in themselves a source of uncertainty. In each particular case, the degree of accuracy of the solution can be matched to the requirements of the problem and the accuracy of the available data. This flexibility is one of the important features of the method under consideration.

A feature of anti-crisis management is that decisions have to be made with insufficient, inaccurate and often distorted information. This makes it impossible to use deterministic models, and there are no necessary conditions for the correct application of probabilistic models, because crisis situations are unique and it is rather difficult to find analogues. As a result, the following statement will be true: in the problems of anti-crisis management, the use of fuzzy logic gives more reliable results than the results obtained using traditional statistical (probabilistic) methods.

Purpose and objectives of the study. The purpose of the work is to develop and test mathematical models that facilitate decision-making on anti-crisis management.

The goal set in the work necessitated the solution of the following tasks:

Summarize domestic and foreign experience in applying the methods of the theory of anti-crisis management to prevent and exit the enterprise from the crisis;

Conduct a comparative analysis of existing methods for localizing crisis phenomena, identify and evaluate the effectiveness and limitations of classical and non-classical (modern) mathematical methods for predicting and overcoming crisis situations;

Analyze the possibility of using decision support systems in the field of anti-crisis management;

Determine the main problems in the implementation of anti-crisis enterprise management programs;

Prove the need to use DSS based on fuzzy statements in the field of anti-crisis management, as the most uncertain area of ​​management theory;

Develop an algorithm for predicting the emergence of a crisis state of an enterprise based on soft computing;

Develop decision-making models to bring an enterprise out of a crisis state in conditions of uncertainty.

Object and subject of research. The object of the study is an enterprise in a crisis situation.

The subject of the research is the processes taking place in the conditions of the developing crisis.

The choice of the object and subject of research is due to the fact that at present, in the current conditions of the national economy, many enterprises are at risk of bankruptcy and falling into a crisis, regardless of the industry and the size of the enterprise itself.

Theoretical and methodological basis of the study. The theoretical and methodological basis of the dissertation work was the work of the authors in the field of economic and mathematical sciences, statistics, management theory.

The dissertation work uses materials from economic, statistical and mathematical literature, thematic materials of periodicals, as well as materials obtained in the course of the author's practical work.

Scientific novelty of the research. In relation to the analysis of the state of the enterprise for the emergence of a crisis situation, the advantages of using the fuzzy logic apparatus for analyzing processes and making decisions in the course of anti-crisis management are identified and scientifically substantiated.

A technique for recognizing the possibility of a crisis situation at an enterprise based on conditional fuzzy rules is proposed as a tool for predicting the occurrence of negative phenomena.

An algorithm for assessing the prospects of an innovative product has been developed, which uses conditional fuzzy statements about the predictive values ​​of factors.

A technique for assessing the personnel potential of an enterprise in a crisis using the methodology of fuzzy sets is proposed.

An integrated approach has been developed for the analysis and assessment of financial risks in the implementation of anti-crisis measures by using the project stage risk assessment method based on convolution of fuzzy hypotheses.

The practical significance of the study. The appearance of this work was due to the need to develop fuzzy methods for analyzing the state of the enterprise and decision support models for the implementation of anti-crisis measures.

With the help of the methods developed in this paper, enterprises in a crisis or pre-crisis state get the opportunity to systematically apply the methodology for monitoring and evaluating their activities, as well as a set of methods used in case of detection of signs of an internal crisis.

Methods for analyzing and predicting negative phenomena in an enterprise, as well as decision support systems in the field of anti-crisis management, can be used in the field of anti-crisis management by relevant specialists to eliminate possible errors in conditions of high uncertainty of the situation; the methodological developments obtained in this work can be used in the educational process, when teaching disciplines related to anti-crisis management, fuzzy sets in management and decision-making problems.

Approbation of the research results. The main provisions and conclusions of the dissertation research were reflected in six scientific papers with a total volume of 4.1 p.p., including the contribution of the applicant 2.8 p.p.

Research structure. The dissertation consists of an introduction, three chapters, a conclusion and a list of references.

The main content of the work

In the introduction the relevance of the research topic, goals and objectives, object and subject of research, scientific novelty, practical significance are substantiated, the methodological and theoretical basis of the research is given.

In the first chapter- "Modern problems of managing insolvent enterprises" - various views of various authors on the concept of "anti-crisis enterprise management" are explored; the main causes of a crisis situation at the enterprise; crisis stages. The methodology of management of insolvent enterprises is considered.

The analysis of various points of view of domestic authors on the concept of anti-crisis management of an enterprise allows us to speak about the commonality in their approaches to the concept of anti-crisis management, as a set of interrelated measures from early diagnosis of a crisis to measures to overcome it. The basic principles on which the anti-crisis management system is based and which distinguish anti-crisis management from the usual one are considered: the possibility of a crisis should be diagnosed at the earliest stages in order to use the possibilities of its neutralization in a timely manner; in the context of a developing crisis, urgent response to crisis phenomena is necessary; the system of mechanisms used to neutralize the threat of bankruptcy is associated with financial costs or losses, and at the same time, the level of these costs and losses must be adequate to the level of the threat of bankruptcy of the enterprise - otherwise, the expected effect will not be achieved, or the enterprise will incur unreasonably high costs; in the fight against the threat of bankruptcy, the enterprise should rely solely on internal financial capabilities, that is, it is necessary to fully realize the internal potential to exit the enterprise from a crisis state.

Despite the variety of external and internal causes of the crisis situation at the enterprise, the factors that have the greatest impact on the state of the enterprise have been identified. These are managerial: lack of strategy in the activities of the enterprise and focus on short-term results to the detriment of medium and long-term ones; low qualification and inexperience of managers; low level of responsibility of the company's managers to the owners for the consequences of the decisions made.

As a result of the study of the subject area, the qualifying signs of the main stages of the crisis are indicated. The first stage of crisis phenomena is characterized by a decrease in profitability and the volume of profits received in the event of stable (i.e. fixed for a sufficiently long time, for example, several reporting periods) tendencies of deterioration in the financial position of the enterprise. The qualifying sign of the second stage of the crisis is the insufficient effectiveness of current production activities - the profitability (profitability) of capital and the profitability of all operations on profit after taxation has a small positive or negative value, which leads to an insufficient level of self-financing of the enterprise and requires the involvement of additional borrowed sources. In the third stage of the crisis, the main qualifying feature is insolvency.

In the second chapter- “Characteristics of existing methods of anti-crisis management and the transition to fuzzy-multiple descriptions” - a comparative analysis of the most commonly used methods for diagnosing, analyzing and forecasting the financial condition of an enterprise was carried out, and a justification was made for the possibility of using soft computing in modeling anti-crisis management.

In the course of the study of traditional approaches to forecasting the financial condition of enterprises: methods of expert assessments, methods for processing spatio-temporal sets and situational methods, the shortcomings of each of them were identified. The disadvantage of expert assessments is that they contain a subjective element and the possibility of an erroneous judgment. Methods for processing space-time sets imply that the predicted random process is stationary, i.e. in each time section of this process there is a random variable, the probability distribution of which contains constant parameters that do not change in time (in practice, external and internal factors constantly have a strong influence on the activity of the enterprise, which does not allow us to consider the parameters of the environment as constant and unchanged in time). Due to the fact that the uncertainty factor has a huge influence in the theory of anti-crisis management, the use of situational analysis methods, where it is supposed to generate probabilistic economic scenarios often using a decision tree, may become irrational.

The classification of economic indicators used to assess the property and financial condition of companies (liquidity, financial stability, business activity, profitability, position in the securities market), including complex coefficients characterizing the position of an economic entity as a whole - the Wall indicator, the Altman model, Lisa, Chesser, Argenti's qualitative approach. It is obvious that these approaches are not resistant to variations in the initial data that are observed in firms with different organizational and technical specifics, with their own unique market niches, strategies and goals, life cycle phases, etc., which is certainly the main lack of such complex indicators.

Due to the fact that in the course of analyzing the financial condition of an enterprise, as well as in the process of making decisions on its recovery, analysts are faced with the uncertainty of a real system that does not allow them to make an optimal decision, it is advisable to use soft calculations in modeling anti-crisis management.

The analysis of tasks on anti-crisis management, performed in the previous chapters, made it possible to identify a number of tasks in which the use of the apparatus of fuzzy sets is most appropriate, since in this case it is possible to obtain new results that increase the efficiency and validity of anti-crisis solutions.

In the third chapter- “Fuzzy-multiple models for anti-crisis management of an enterprise” - the solution of the following problems in the field of anti-crisis management is proposed:

1) recognition of the possibility of a crisis situation;

2) assessment of the prospects of an innovative product;

3) assessment of human resources;

4) assessment of financial risks in the implementation of anti-crisis measures.

A well-known technique for recognizing a crisis situation, developed by the economist G.V. Savitskaya. It is based on the construction of classes of enterprises with different financial indicators (Table 1).

Table 1. Grouping of indicators according to the criteria for assessing the financial condition

Index	Class boundaries according to criteria
Absolute liquidity ratio Ka	0.25 and above -					Less than 0.05 -
Quick liquidity ratio Kkl	1.0 and above -					Less than 0.5 -
Instant liquidity ratio Ktl	2.0 and above -					Less than 1.0 -
Financial independence ratio K1	0.6 and above -	0,59-0,54 - 15-12	0,53-0,43 - 11,4-7,4	0,42-0,41 - 6,6-1,8		Less than 0.4 -
The coefficient of security of own. rev. means of Koss	0.5 and above -					Less than 0.1 -
Equity capital ratio K4	1.0 and above -					Less than 0.5 -
Minimum border value

The assignment of a crisis enterprise to a specific class is based on the sum of points assigned for the previous and current periods. For a complex system, such as a modern enterprise, the genetic transfer of the past to the future cannot give reliable results. Of interest is the possibility of predicting the future state of the enterprise on the basis of expert assessments, without waiting for the reporting documentation. Since uncertainty is fundamentally inherent in expert assessments, which is not subject to probabilistic axiomatics, soft calculations are used to process expert opinions, and expert opinions themselves are presented in the form of fuzzy numbers. In order to assess the possible situation at the enterprise at the end of the reporting period, the expert needs to give an assessment of what the following indicators will be in absolute terms (respectively, they are components of the indicators given in Table 1): A1 - the most liquid assets; A2 - quickly realizable assets; A3 - slow-moving assets; P1 - the most urgent obligations; P2 - short-term liabilities; Сс - sources of own funds; B - balance sheet currency; EU - own working capital; I eat - the cost of inventories; Ep - cash, short-term financial investments, receivables and other current assets.

Suppose that the expert indicated the possible level of the A1 indicator to be approximately 13,000 rubles, limiting the allowable limits of change [A1 - A1/5] and [A1 + A1/5]. This makes it possible to interpret the expert's answer not as a point number, but as a fuzzy number, for example, as shown in Fig. 1. There are other options that the expert will prefer.

Rice. 1. Representation of expert assessment A1 by a fuzzy number

Indicator A2, one of the components contains short-term receivables, therefore, special attention is paid to it in the work, since it can be of considerable importance for an enterprise to analyze the solvency of debtors in order to predict what funds they can return to the enterprise under study in the near future, since a crisis enterprise , like no other, needs a refund. The formation of the remaining indicators is also carried out with the help of expert opinions. The corresponding membership functions are determined by analogy with the parameter A1. Having the forecast values ​​of all the indicators necessary for the calculation, taking into account inflation, fuzzy coefficients are calculated (Table 1) according to known formulas. For an adequate assessment of each coefficient, the distribution functions of the coefficients relative to the scores are compiled according to Table 1, after which the value of a particular coefficient is projected onto the corresponding distribution function, as a result, the number of points for each coefficient is obtained. The integral indicator of the final assessment of the financial condition of the enterprise is calculated by summing the points received.

This approach makes it possible to obtain a scenario estimate, which presents the worst, best, and also the most expected result. On fig. 2 shows a specific example of the implementation of this approach.

Rice. 2. Membership functions of classes

Projecting the final score onto the class membership functions, we obtain the following conclusion. The enterprise belongs to the first class with a truth value of 0.19; to the second class with a truth value of 0.8. This result allows us to solve the problem even in those cases when the enterprise cannot be unambiguously correlated with any of the classes.

Rice. 3 Price value given by a fuzzy number

Rice. 4. Price value given by a clear number

The choice of an innovative product, as a rule, is carried out on the basis of a comparative assessment with a prototype product. There is always market uncertainty in this process, since the prototype has been marketed in the past, and the innovative product is only planned to be marketed in the future market. In this regard, it is possible that past conditions may differ from future ones. A fuzzy model for evaluating an innovative product is proposed.

The solution of this problem is carried out according to the vector indicator "quality-price". A multiplicative convolution is proposed as a complex indicator

where is the normalized price of the goods; -- the normalized value of the quantitative assessment of the quality of the goods.

Indicator (1) is used within the methodology, the algorithm of which is conveniently illustrated by the following example.

Consider the choice of analogues, the price of which is given below:

(*) - product - innovation with a forecast price in cu.

Due to the fact that T1, T4 products have not yet entered the market, at this point in time we can only talk about price estimates, which, obviously, will be of an approximate nature. One way to represent approximate, imprecise (vague, fuzzy) estimates is fuzzy numbers.

So, for T1, a fuzzy number can graphically look like shown in Fig. 3, i.e. the price is in the range from CU 160 up to CU 240, but the most expected value (the top of the function) is CU 200. Similarly, the price of the product T4 is set (if desired, the interval and form of the function can be set by the expert based on his own considerations).

Unlike products T1 and T4, goods T2, T3 and T5 have been on the market for a long time and the price is set by a clear number: T2 = CU 113. (Fig. 4). Similarly, as for T2, we set the price of goods T3 and T5.

According to the results of expert assessments, in terms of quality, the goods are ranked as follows:

where R i is the rank of the product with the number i (set by a fuzzy number).

As a result, we represent the ranks of goods as fuzzy numbers shown in Figure 5. Based on the ranking results, fuzzy weight coefficients of quality (K) were calculated using the formula:

where N is the number of compared goods.

Rice. 5. Product ranks

Rice. 6. Modified product ranks

As a result, from the initial fuzzy ranks of goods (Fig. 5), we will obtain modified rank values ​​that will be in the range from 0 to 1, and in reverse order (Fig. 6).

At the next step, the values ​​of K i are normalized, for which each value of K i is divided by the sum of all values. As a result, we have:

Finally, complex quality indicators are calculated according to the expression (1):

W 1 \u003d 0.05242; W 2 =0.03711; W 3 =0.03226; W 4 =0.04583; W 5 \u003d 0.01542.

Rice. 7. Comprehensive indicators

Graphically, fuzzy complex quality indicators are presented in Fig.7.

The comparison procedure W is performed using the weighted cardinality of fuzzy sets.

Thus, the calculations gave the following values:

M W 1 = 0.0634605; M W 2 = 0.0438562; M W 3 = 0.0369195; M W 4 = 0.0562902; M W 5 = 0.0199427.

As follows from the calculations, T1 and T4 innovation products significantly outperform analogue products in terms of the value of the complex indicator "quality - price" and can be recommended for production.

Overcoming a crisis situation is impossible without the right selection of an anti-crisis team. One of the options for solving this problem is to use the profile method, the essence of which is that each employee can be represented as a given set of qualities in their specific space, where the assessment for each criterion is given in the form of points. Table 2 shows the criteria by which the candidates will be evaluated, as well as their weights, which, if the expert wishes, can be set in fuzzy numbers.

Table 2 Groups of requirements and their specific weights gi

Let's assume that the expert characterizes the candidate with linguistic variables of the following form: 1) "requirements do not appear" - ne_pr; 2) “not showing up enough” - pr_ned; 3) "manifested quite clearly" - pr_dost; 4) "manifest with medium activity" - pr_sr; 5) “appear well” - pr_hor; 6) "appear very well" - pr_och_hor; 7) "appear excellent" - pr_otl. Graphically, their membership functions are presented as follows (Fig. 8):

Rice. 8. Representation of linguistic variables

Let's assume that the expert has set the following values:

	Candidate A
	Requirements
	Specialist. knowledge		Rice. 9. Expert evaluation of candidate A
	Education
	Character
	Appearance
	Candidate B
	Requirements
	Specialist. knowledge		Rice. 10. Expert evaluation of candidate B
	Education
	Character
	Appearance

On fig. Figures 9 a) and 10 a) show the membership functions of linguistic values, Figures 9 b) and 10 b) show the same values, taking into account the weights specified in Table 2. To analyze alternatives, the operation of finding intersections of fuzzy sets given for the i-th candidate is performed. Then, the resulting fuzzy sets are compared (for each of the candidates A, B) to determine the best solution using the weighted power of the fuzzy sets.

For candidate A, we will have the following linguistic scores with the corresponding membership functions:

( pr_dost (x), pr_sr (x), ne_pr (x), pr_och_hor (x)) - (Fig. 9 b)

For candidate B we have:

( ne_pr (x), pr_hor (x), pr_dost (x), pr_ned (x)) - (Fig. 10 b)

If the evaluation system of any of the candidates contains non-intersecting sets, then groups of sets with non-empty intersection are determined and the power value is calculated for each group separately, and then these powers are summed up.

H A \u003d min ( pr _ dost (x), pr _ sr (x), ne _ pr (x), pr _ och _ hor (x)) - (Fig. 11 a)

H B =min( ne_pr (x), pr_hor (x), pr_dost (x), pr_ned (x)) - (Fig. 11 b)

Rice. 11. Presentation of the final membership functions reflecting the assessment of candidates

It can be expected that candidate A is preferable to candidate B.

Power values: for the intersection A1 - M A 1 =0.005326; for the intersection A2 - M A 2 =0.110967; for the intersection B1 - M B1 = 0.014762; for the intersection B2 - M B2 = 0.019108.

Overall score for candidate A - M A = M A 1 + M A 2 = 0.1163;

Overall score for candidate B - M B = M B1 + M B2 = 0.0339.

Thus, comparing the values ​​of M A and M B, it is obvious that candidate A is better suited for a vacant position, which confirms the preliminary conclusion.

Within the framework of anti-crisis management, the task of analyzing and programming risks is of great importance. As an object of application of the method under consideration, a risk assessment methodology for the project stage is used, based on work with expert sheets and linguistic risk assessment.

As a result of the analysis of the submitted documents of the project, for each issue, the expert gives his assessments, which are formulated in a linguistic form:

if<оценки>, then<вывод=?>(2)

and the task is to find the output value that best matches the scores on the left side of rule (2).

Suppose that the following are accepted as linguistic values ​​of the assessments (Fig. 12):

very bad- (VB);

mean-(M);

very good- (VW). bad- (B);

good- (W);

Let the first part of the rule (2) have the form:

if 1f=W> and 2f=W> and 3f=M> and 4f=W>

and 5f=M> and 6f=W> and 7f=VW> and 8f=W>and

9f=W> and 10f=W> and 11f=B> and 12f=W> and 13f=W>.(3)

Rice. 12 Intersection of membership functions.

With known membership functions for convolution of estimates, in accordance with the used logical connectives and modifiers, the resulting membership function is calculated. For expression (3), this is the intersection operation.

Non-zero intersections, for example, can be formed by estimates

A 1f= (q 3f, q 11f) ; A 2f= (q 5f, q 1f, q 2f, q 4f, q 6f, q 8f, q 9f, q 10f, q 12f) ; A 3f= (q 7f, q 13f)

These intersections in Fig. 12 are represented by the corresponding shaded areas. Let's assume for simplicity that the level of risk is estimated by three linguistic values:

High Level(HL);

Middle Level(ML);

Low Level(LL),

Graphs of the corresponding functions are shown in Fig.13. The same figures also show the membership functions corresponding to the intersections A1, A2, A3 (dashed lines):

A 1f= (q 3f q 11f) ; A 2f= (q 5f q 1f q 2f q 4f q 6f q 8f q 9f q 10f q 12f) ; A 3f= (q 7f q 13f) .

Obtaining the conclusion of interest to us requires the calculation of the implication. The simplest is the calculation by the formula

Rice. 13 (1) Intersection with "high".

Rice. 13 (2) Intersection with "middle level".

Rice. 13 (3) Low level crossing.

The implementation of transformations according to relation (4) for the assessment of "high risk" is represented by a fuzzy set H, for the assessment of "medium risk" - a fuzzy set M, for the assessment of "low risk" - L. To select the most reliable assessment of the risk level, it is necessary to compare fuzzy sets H, M, L. This procedure is performed using the weighted cardinality of fuzzy sets.

For the example shown in Fig. 12, 13 the following results were obtained:

M (high level) = 0.2; M (average level) = 0.4; M (low level) = 0.3.

Thus, the level of risk is assessed as medium, therefore, this proposal can be accepted for further development.

The processing of linguistic assessments allows one to obtain more reliable data and new information that is not explicitly contained in the judgments of experts and allows one to build effective models of intuitive-logical analysis in combination with quantitative methods of assessment and processing.

The main results of the dissertationrotational work

1. A model for recognizing the possibility of a crisis situation has been developed, which makes it possible to predict the future state of an enterprise based on expert assessments without waiting for the full reporting documentation. In this work, soft calculations are used to process expert opinions. The expert opinions themselves are presented in the form of fuzzy numbers. As a result of this approach, a scenario assessment is obtained, in which the worst, best, and also the most expected result are presented, which ensures the choice of the most reasonable decisions.

2. A fuzzy model for evaluating an innovative product is proposed, which allows taking into account not only the incomplete correspondence of the innovative product to the prototype, but also the fact that the innovative product and the prototype will be in different market conditions.

3. Fuzzy modifications of the profile method used to select an anti-crisis team have been developed - which is one of the main ways to overcome a crisis situation. Profile scores are presented either as fuzzy numbers or as linguistic statements.

4. In connection with the great importance of the problem of analysis and risk management for anti-crisis management, the dissertation work proposes models for assessing the risks of not returning receivables, as well as the risk of investing in order to overcome a crisis situation based on a fuzzy-multiple approach.

5. A software module has been developed that implements the task of qualitatively assessing the possible risks associated with investing the company's own funds, as well as with the return of receivables.

Publications in journals from the VAK list:

1. Chernov V.G., Suvorov M.K. Bankruptcy Forecasting Using a Rating Method Based on Fuzzy Models. Instruments and Systems. Management, Control, Diagnostics. - 2006. - N4. - With. 57-63.

Other publications:

1. Suvorov M.K. Assessment of the quality of preparation of investment documents based on fuzzy rules of conditional inference // Young science: materials of the scientific conference of young scientists and students (April 8-10, 2003, Vladimir). - Vladimir: VlGU, 2003. - p. 131. - ISBN 5-89368-447-8.

2. Chernov V.G., Suvorov M.K. Fuzzy models in anti-crisis management // Modern problems of applied mathematics and mathematical modeling: materials of the international scientific conference (December 12-17, 2005, Voronezh). - Voronezh: Voronezh State Technological Academy, 2005. - p.237.

3. Chernov V.G., Suvorov M.K. Analysis of the professional qualities of applicants for a position based on linguistic assessments // Socio-economic systems and processes: methods of study and development problems: materials of the international. scientific-practical. conf. (May 24, 2005, Vladimir): Branch of VZFEI in Vladimir. - Vladimir, 2005. - p. 415-418. - ISBN 5-93350-109-3.

4. Chernov V.G., Suvorov M.K. Evaluation of innovative products according to the criterion "quality-price" with fuzzy assessments of criterion compliance // Dynamics of scientific research 2005: materials of the international. scientific-practical. conf. (June 20-30, 2005, Dnepropetrovsk): V. 15: Economics. - Dnepropetrovsk: Science and education, 2005. - p. 85-89. - ISBN 966-7191-99-0.

5. Chernov V.G., Suvorov M.K. Fuzzy-multiple methods and models in the problems of anti-crisis management // Scientific research: information, analysis, forecast: monograph / ed. O.I. Kirikov. - Voronezh: VSPU, 2006. - Book 10. - p. 185-217. - ISBN 5-88519-304-5.

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