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2012 | Buch

Fundamentals of Risks Management Technologies Kapitel lesen Erstes Kapitel lesen

Risk Management Technologies

With Logic and Probabilistic Models

verfasst von: E.D. Solozhentsev

Verlag: Springer Netherlands

Buchreihe : Topics in Safety, Risk, Reliability and Quality

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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Über dieses Buch

This book presents intellectual, innovative, information technologies (I3-technologies) based on logical and probabilistic (LP) risk models. The technologies presented here consider such models for structurally complex systems and processes with logical links and with random events in economics and technology.
The volume describes the following components of risk management technologies: LP-calculus; classes of LP-models of risk and efficiency; procedures for different classes; special software for different classes; examples of applications; methods for the estimation of probabilities of events based on expert information. Also described are a variety of training courses in these topics.
The classes of risk models treated here are: LP-modeling, LP-classification, LP-efficiency, and LP-forecasting. Particular attention is paid to LP-models of risk of failure to resolve difficult economic and technical problems. Amongst the discussed procedures of I3-technologies are the construction of LP-models, LP-identification of risk models; LP-risk analysis, LP-management and LP-forecasting of risk.
The book further considers LP-models of risk of invalidity of systems and processes in accordance with the requirements of ISO 9001-2008, LP-models of bank operational risks in accordance with the requirements of Basel-2, complex risk LP-models for preventing ammunition depot explosions, enterprise electric power supply systems, debugging tests of technical systems, etc. The book also considers LP-models of credit risks, securities portfolios, operational risks in banking, conteraction of bribes and corruption, etc.

A number of applications is given to show the effectiveness of risk management technologies. In addition, topics of lectures and practical computer exercises intended for a two-semester course “Risk management technologies” are suggested.

Inhaltsverzeichnis

Frontmatter
Chapter 1. Fundamentals of Risks Management Technologies
Abstract
And it is right—returning to the basics, logics and arithmetic (sets) in order to solve complex problems.
E.D. Solozhentsev
Chapter 1, in essence, is the theoretical basis of Risk management technologies. Here we describe components of Risk management technologies (RMT): logic and probabilities (LP) calculus, classes of LP-models of risk and efficiency, procedures classes, special software, samples of applications, the training course. LP-calculus contains more than twenty new positions. The classes of LP-models are: modeling, classification, efficiency, and forecasting. Procedures are: building models, identification of models, analysis, management and risk prediction, special logical software. We describe 30 applications. The training course is designed for 2 semesters, has 16 laboratory works on the PC.
We describe: the LP-risk model for solving difficult problems with connection AND, OR, NOT, data structure and statistical database, events-parameters and events-gradations in risk models, the transition from databases to knowledge bases, types of variables in LP-risk models, types of events in the tabular knowledge base, incompatible events groups, knowledge bases and systems of L-equations, the connections of LP-risk models of different classes. We formulate the problems of development and research of RMT.
E. D. Solozhentsev
Chapter 2. Building LP-Risk Models of LP-Modeling Class
Abstract
The problem “data → the model, explaining the data” should be considered as the basic one for any area of science.
Kalman
For the construction of the logic and probabilistic (LP) risk model of the LP-modeling class we describe the following methods: complete disjunctive normal form, the shortest paths of successful performance, minimum cuts of failures, associative LP-risk models, tabular setting of LP-models, LP-risk models for several aims, scenario, complex and dynamic LP-risk models.
We also describe the procedure of building the LP-model of this class: development of the risk scenario, writing down the L-risk model according to the scenario, transition from the L-risk model to the P-risk model by orthogonalization.
The LP-models of the LP-modeling class is used as the basis for building risk model of classes LP-classification, LP-efficiency and LP-forecasting. Therefore the description of the issues concerning building the model of LP-modeling class is of greatest importance. The development of scenario can be make by experts well knowing and understanding the functioning of the system.
LP-risk models are transparent, very good for risk analysis of systems and for management purposes. Neither scoring techniques, nor neural networks does not comply with these requirements and the Kalman’s rule.
E. D. Solozhentsev
Chapter 3. Building LP-Risk Model of LP-Classification Class
Abstract
The real logic of our world is the calculation of probabilities.
Maxwell
For the construction of logic and probabilistic (LP) risk models of the LP-classification class we formulate identification tasks on statistic data, describe peculiarities and methods of identification and iterative algorithms, carry out research results, estimate computational complexity of algorithms and accuracy of training and testing LP-risk models.
The identification of the LP-risk model was the first and, perhaps, the most difficult task, solved for economics and it had all the basic components of the intelligent, information, innovative technologies. The problems of building LP-risk model of LP-classification class are important a number of reasons. The classification problem (objects, system states, companies, banks, countries) is one of the basic ones in science and is solved by statistical data. We build knowledge bases as a system of logical equations. We transit to the LP-risk model of this class broadening the possibilities for LP-models of the classes LP-efficiency and LP-forecasting for solving the tasks of analysis and management.
E. D. Solozhentsev
Chapter 4. Building LP-Risk Models of LP-Efficiency and LP-Forecasting Classes
Abstract
The knowledge of certain principles often compensates the ignorance of certain facts.
Helvetius
We describe the building logic and probabilistic (LP) risk models of the classes LP-efficiency and LP-forecasting, consider the role of this LP-models in applied tasks. Building the models of the LP-efficiency class was the second and definitely, the most important task, which was solved for economics and had all basic components of the intelligent, information, innovative technologies (I3-technologies).
The risk models of classes LP-efficiency and LP-forecasting are the important part of I3-technologies of managing risk and efficiency in structurally complex systems. We use the following fundamentals: representation of economic systems and processes as structurally complex with random events, L-links and variables; representation of initiating parameters and the efficiency parameter by finite sets of values, and their distributions—by discrete series; using incompatible events groups; building the database and the knowledge base and systems of L- and P-equations; introduction of two types of events for system states in statistical data (appearance and failure); development of the special LP-software.
E. D. Solozhentsev
Chapter 5. LP-Analysis of Risk and Efficiency in Systems
Abstract
We are tied to the chariot of complexity and have lost all abilities to see the obvious.
Thomas J. Peters
We describe logic and probabilistic (LP) analysis of risk and efficiency in classes: LP-modeling, LP-classification, LP-efficiency and LP-forecasting. LP-risk models make the analysis of risk and efficiency in systems by simple and correct methods. This is their advantage compared to scoring models, neural networks models, etc.
In risk analysis a special place is occupied of ideas of LP-calculation concerning the determination of Boolean differences, weights and contributions of initiating events. The technique is analogously to the calculation of derivatives for functions in mathematical analysis. Significations and contributions of initiating events are easily calculated by algorithmically, using P-risk function and software. The differences in the risk of the final event are determined by excluding the event-parameter from the P-risk functions, as well as frequency and probabilistic contributions of event-gradations for the interval of the efficiency parameter distribution. In practical applications this is usually the left or the right tail of the efficiency parameter distribution. Such analysis ensures the transparency of results and offers big opportunities for managing and forecasting risk by statistical data in the space of system states. LP-analysis of system risks is demonstrated in various applications: credit risk, restaurant business, risk of bribery and corruption, successful development of Russia, etc.
E. D. Solozhentsev
Chapter 6. LP-Management of Risk and Efficiency
Abstract
Risk and efficiency management is the main task of economics.
Encyclopedia
We consider procedures of logic and probabilistic (LP) management of risk and efficiency in classes of modeling, classification, efficiency, and forecasting and also describe operative and strategic management of risk.
The management of social and economic processes is performed by managers by investing resources for changing influencing processes and events and their probabilities, including personnel training.
We calculate contributions and significance of initiating events in the final event of social, engineering and economic systems and processes and in their distribution tails.
LP-management of the system risk and efficiency is demonstrated in various applications: credit risk, restaurant business, risk of portfolio assets, risk of bribery and corruption, etc. Strategic management of development is carried out by the scheme of management of a complex object. We manage traffic on the chosen path and correction of deviation from it.
E. D. Solozhentsev
Chapter 7. LP-Forecasting of Risk and Crisis in Systems
Abstract
However difficult the problem may be, it will become more difficult, if you look at it in the wrong way.
P. Anderson
We describe logic and probabilistic (LP) forecasting of risk in classes LP-modeling, LP-classification, LP-efficiency, LP-forecasting and also the special cases: forecasting with the exclusion of incorrect data; forecasting of the wear of the technical system; forecasting by the weights of initiating parameters distributions.
Forecasting is the most difficult procedure in science and, one can say, the crown of intellect and knowledge. In Risks management technologies we forecast by statistical data in time and in the space of system states.
On the one hand, we predict the system states, which are not present in statistical data, i.e. they are predicted in the space of system states. On the other hand, we predict the system states in the time function with the assumption that a number of time dependent factors influence the probabilities of initiating events.
E. D. Solozhentsev
Chapter 8. Software for Risks Management Technologies
Abstract
The computer makes it possible to solve all the problems, which did not exist before its invention.
Computer News
We describe software for the logic and probabilistic (LP) models of classes: LP-modeling, LP-classification, LP-efficiency, LP-forecasting.
We use special software: ACM 2001 and ROCS 2 for structural and logic modeling; ASP-3W for assessment of event probabilities; software for risk classification and software risk portfolio.
Software for Risk management technologies are so important for the assessment, analysis, management and forecasting of risk, that without them the problems themselves do not exist. In other words, computers makes it possible to solve new problems.
The construction of LP-models of risk and efficiency, their identification by statistical data, analysis, management and forecasting of risk have high computational complexity and can be performed only using computers and special logical software.
E. D. Solozhentsev
Chapter 9. Axioms and Definitions of Risks Management Technologies
Abstract
Any built algorithm reflects a certain general theory, from which it follows as a particular case.
A.V. Yaroshenko
We consider the basic axioms, axioms of logic and probabilistic (LP) calculus by Ryabinin, axioms and theorems of Risks management technologies, basic definitions, peculiarities of technologies, the formal LP-theory of risk for the LP-classification class. The development of axioms of Risks management technologies is significant for understanding, substantiating, validating and developing this new science discipline.
The phenomenon of LP-calculus consists in the fact that it is not described in mathematical handbooks and encyclopedias as a science discipline and at the same time it is used in various applications.
E. D. Solozhentsev
Chapter 10. Risk Management Technology of Building Company
Abstract
We describe Risk management technologies for managing risk and efficiency of a building company: task setting; risk management of a company, the logic and probabilistic (LP) risk model of the failure to solve the tasks of a company.
The L-function of a failure risk of solving a difficult problem takes in account of failure risks of subjects (the state, business, banks, scientists and public opinion) and tasks, constituting the core of a problem.
Management tools, effective in the past, are generally ineffective now. A manager of today should be able to use up-to-date business technologies and information resources.
An important factor, influencing the management of enterprises, is the transition from their systematic and consecutive development to accelerated cyclic development. It happens due to the following reasons: business processes are accelerated, consumers’ needs develop, the relations between an enterprise and other market entities become more complex, and the environment turbulence increases.
E. D. Solozhentsev
Chapter 11. Risk Management Technology of Transport Company
Abstract
The subject of logistics is organization and regulation of the distribution of goods from producers to consumers, the creation of the infrastructure of such distribution.
We describe Risks management technologies for the transport company: analysis of managing risk and efficiency of a company; logic and probabilistic (LP) model of the company’s failure risk; LP-analysis of a company and its branches’ failure risk; analysis of a company’s efficiency from external factors and from internal factors.
In the course of industrial development logistics has been gaining a large-scale character, encompassing now not only separate enterprise, but whole cities and countries. Big corporation appeared, which dealt only with the problems of carrying goods by a contractor’s order. Logwin Road + Rail Rus is one of such companies. The tasks of risk and efficiency analysis are of primary importance for transport companies. LP-risk models are viewed both for the parent company and its main branches.
E. D. Solozhentsev
Chapter 12. Risks Management Technologies for Analysis of Company Efficiency
Abstract
We describe Risk management technologies for a company’s efficiency by economic indices: traditional data analysis; logic and probabilistic (LP) analysis of data; the transition from data to a knowledge base; frequency data analysis.
We use data of the site www.​skrin.​ru which has quarterly statistical data concerning 40 000 enterprises of the Russian Federation for 11 years. We use Gasprom quarterly statistical data for 11 years from the site.
E. D. Solozhentsev
Chapter 13. Credit Risks Management Technology
Abstract
We describe Risk management technologies for credit risks: task setting; the choice of admissible risk; price for risk; accuracy and robustness of logic and probabilistic (LP) model; transparency of LP-risk model.
Building the LP-model of credit risk by the identification method was the first and, perhaps, the most difficult task, which was solved for economics and had all the basic components of Risks management technology.
We describe Risk management technology for assessment, analysis and management of the bank credit risk, using the LP-risk model of the LP-classification class. The peculiarities and advantages of the LP-model of LP-classification class are their accuracy, robustness and transparency.
All banks are different, as they provide services to different social groups in different cities and regions of the country and enterprises of various industries and sizes, with different forms of ownership. Competing also stimulates the differences of banks.
Technology has the following advantages: twice as more precise assessment of good and bad credits, seven times as greater stability of the classification of credits, absolute transparency of the credit risk assessment and analysis, solving the tasks of risk analysis, forecasting and management.
E. D. Solozhentsev
Chapter 14. Portfolio Risk Management Technology
Abstract
We describe Risk management technologies for managing the investment portfolio risk: task setting; the optimum portfolio choice; logic and probabilistic (LP) models of the portfolio risk; LP-analysis of the portfolio risk and efficiency; portfolio risk management.
The construction and research of the LP-investment portfolio risk model belonging to the LP-efficiency class, was the second and, perhaps, the most important problem, solved for economics, with all the basic components of Risks management technologies. The solution of this problem led to the appearance of the class of LP-forecasting tasks gave opportunities to solve various applied tasks in economics with regard to risk and efficiency analysis and management.
The choice and analysis of an investment portfolio is one of the examples of the LP-efficiency class. Investments in the investment portfolio form the basis of the market economy of developed countries. The theory of the investment portfolio formation is the most widely spread investments theory. This theory makes it possible to optimize, simulate and control investments risk. It solves the tasks of forecasting and optimizing the returns and risk of the assets portfolio.
E. D. Solozhentsev
Chapter 15. Risks Management Technology of Company Management
Abstract
Dedicated to the memory of the outstanding economist Peter Drucker.
We consider Risk management technologies for a company management failure risk: the problem state; risk of management failure in the achievement of targets and in performance quality by functions and business directions.
We have analyzed the Risk management technology of a company management failure, employing the logic and probabilistic (LP) risk model of the LP-modeling class. The LP-risk models of a failure of a (company, government, project, etc.) control are essential for managing the success of a business. We present the following LP-models of failure risk management: by functions, directions of activities, achieving one target and a group of targets, managing the performance quality.
E. D. Solozhentsev
Chapter 16. Logical Probabilistic Models of Banks Operational Risks
Abstract
We describe Risk management technologies for bank operational risks: initiating and derived events; representation of the structural risk model; logical and probabilistic model of the operational risk; reservation for the operational risk; the influence of internal initiating and repeated events on operational risk; contributions of initiating events.
In accordance with the Basel’s agreement we consider the following logic and probabilistic (LP) models in order to estimate the capital reserve for operational risk: the LP-failure risk model for solving the operation risk problem; the LP-model of assessing the operational risk by the standardized Basel method; the LP-model of assessing operational risk by the advanced Basel method; the technique of the LP-analysis of operational risk; estimation of the reserve for operational risk by Basel and LP-model; the LP-bank risk model which takes into account internal and external events; the LP-bank risk model which combines of other bank risks; the technique of direct and inverse estimates of probabilities of events in operational risk by expert information.
E. D. Solozhentsev
Chapter 17. Risks Management Technologies of Counteracting Bribery and Corruption
Abstract
We describe Risks management technologies for counteracting bribery and corruption: the LP-bribery risk model in an institution; the LP-model of the officials’ bribery and fraud risk; the LP-risk model of bribes during service; analysis of bribery risk in the kindergarten.
We consider the general scheme for solving problem of bribes and corruption (Sect. 1.​2). In this problem the subjects (the state, business, banks, scholars, public opinion) and objects—the tasks, making up the core of the problem, are logically connected as events. It has been shown that without scientists, I3-technologies and public opinion it is impossible to solve this difficult economic problem in Russia.
LP-risk models of objects-tasks of counteracting bribery and corruption refer to classes LP-classification and LP-efficiency, which employ statistical data bases. We carry out the following LP-risk models of bribery and corruption: institutions with regard to their operation parameters, officials with regard to their behavior parameters, institutions and officials with regard to service parameters. These models are meant for: economic crime departments of cities, services of internal control and safety of banks and companies, development of rules and laws for service parameters.
E. D. Solozhentsev
Chapter 18. Invalidity Risks Management Technologies of Systems for Standard ISO 9001-2008
Abstract
Standard ISO 9001-2008 requires an assessment of invalidity (quality) of economic and engineering systems and processes. The invalidity is the inconsistency between parameters and elements of a system and qualifying technical conditions and requirements.
We consider Risks management technologies for analysis and management of the processes invalidity risk: the description of invalid events and variables; the logic and probabilistic (LP) model of the system invalidity risk; the assessment and analysis of the system invalidity risk; the management of the system states invalidity risk; the management of the systems development invalidity risk.
We propose a general scheme of building an LP-risk model of invalidity of economic, technical and organizational system and processes. We consider the technologies of building LP-models of validity on the examples: management of development of economical and technical systems; flight tests of machines, processes and systems; the electric metallurgical plant electrical power supply system and the system of an ammunition depot explosion prevention.
We consider the following problems regard to the construction of LP-invalidity risk models: (1) engineering, methodological, logical and calculation aspects; (2) taking into account the replication of elements and events in LP-models of invalidity risk in complex systems and processes; (3) taking into account the peculiarities of LP-risk models of invalidity, built on the basis of technical documentation and by the events scenarios; (4) the technique of building the LP-model of invalidity proposes ten different representations of LP-model of invalidity.
E. D. Solozhentsev
Chapter 19. Risks Management Technologies of Restaurant
Abstract
We describe Risk management technologies for the risk and efficiency management of a restaurant (shop): parameters and gradations of parameters, data and knowledge about the states of a restaurant, identification of LP-risk and efficiency models, frequency analysis of risk and efficiency; LP-analysis of the risk and efficiency of a restaurant.
For managing risk and efficiency of a restaurant we use LP-risk models of classes LP-efficiency and LP-classification is used. Thus, the management of the risk and efficiency of a restaurant is performed by solving the tasks of forecasting by monitoring results.
The study was conducted using the statistical data concerning the operation of a real restaurant, but the conclusions also refer to managing risk and efficiency of shops.
The condition of a restaurant is determined by the efficiency parameter Y and influencing parameters Z, which can be quantitative and qualitative, have different character and dimensionality. Parameters Z and Y are viewed as random variables. The distribution of each of them cannot be considered normal even to a first approximation. A task is posed with regard to the analysis by the statistics of parameters Z influencing the efficiency parameter Y and risk and efficiency management.
E. D. Solozhentsev
Chapter 20. Risks Management Technology for Insurance of Fire Hazardous Objects
Abstract
We consider Risks management technologies for the insurance of fire hazardous objects: the risk scenario, the logic and probabilistic (LP) risk functions, analysis of risk.
For the insurance of fire hazardous objects Risks management technologies with the LP-risk model of the LP-modeling class is used.
In the insurance of fire hazardous objects the main problem is the problem of assessing the risk of the appearance of a hazardous state of an object. Below we provide the example of modeling, assessing and analyzing the risk of an explosion and fire in the accumulator bay area of a submarine. Similar risk scenarios are used in case of fires in an apartment, in the premises, in oil and gas transfer plants of main gas pipelines, chemical complexes, as well as ammunition depot explosions.
E. D. Solozhentsev
Chapter 21. Risks Management Technology for a Bank
Abstract
We consider Risks management technologies for managing risk and efficiency of a bank: the logic and probabilistic (LP) risk model of problem solving failure; objects—tasks in problem of the bank management risk; the subjects in problem of the bank management risk.
A number of works on financial mathematics and bank business management deal with separate problems, including optimization problems. A general problem of bank management we consider below, namely Risks management technologies for managing the risk and efficiency of a bank. It is a difficult economic problem.
We carry out the diagram of Risks management technologies solving difficult economic problems was analyzed earlier in the problem solving subjects (the state, business, banks, scientists, public opinion), and objects—the tasks, forming the core of the problem are connected logically as events. It was shown that to solve this problem effectively without scientists I 3-technologies and public opinion is impossible.
E. D. Solozhentsev
Chapter 22. Assessment of Events Probabilities on Expert Information
Abstract
Decision-making is often connected with non-numeric, inexact and incomplete expert information.
N. Hovanov
We consider assessment of events probabilities with the help of the decision taking support system ASPID-3W.
The formulas for calculating risks include the probabilities of initiating events, which should be evaluated either by the statistical data or by expert information.
In Risks management technologies when building LP-risk models one has to assess the probabilities of events on the basis of expert information in the following cases: in LP-models of the LP-modeling class, which do not use statistical data; the probabilities of initiating events are given; LP-models of the LP-classification, LP-efficiency and LP-forecasting classes, using statistical data, in problems, if the statistical data are not enough.
The method of summary indices (MSI) by N. Hovanov allows obtain the assessment by expert information from a number of experts. The method employs non-numerical, inaccurate and incomplete information.
The assessment of the events probabilities and losses from the appearance of events is performed by several experts who use expert information. The experts’ assessment is combined taking into account the weights of the experts themselves. One can also use statistical data as the information from another expert.
The method includes: the synthesis of estimate of events probabilities and the analysis of estimate of events probabilities and losses from the occurrence of events.
E. D. Solozhentsev
Chapter 23. Training Course: Risks Management Technologies
Abstract
You may leave science and this world, but not before you write a textbook.
Advice to Professor
We describe the list of lectures with names of chapters of this book, control questions and the subject index and give some information from logic algebra.
Laboratory works in the training course Risks management technologies are based on lectures. Special logic and probabilistic (LP) software was developed and is used for their performance, laboratory works are done according to the classes of LP-risk models.
1.
LP-modeling (4 works). The students develop the scenario, the LP-risk model and, using ACM 2001 software, do the research of one scenarios. Students developed about 200 scenarios: risk of the recovery failure of the Russian Federation economy, risk of a company development failure, LP-model of increase in population in Russia, LP-model of increase in housing construction in Russia. Then the students develop the LP-risk model, including several scenarios.
 
2.
LP-classification on LP-credit risk models (5 works).
 
3.
LP-efficiency on LP-risk models of the investment portfolio (4 works).
 
4.
Assessment of probabilities of events by expert information: synthesis and analysis of estimations of probabilities (3 works).
 
E. D. Solozhentsev
Chapter 24. Risks Management Technologies as Business Object
Abstract
Risks management technologies in economic and engineering systems have been conducted for more than 15 years. This research field is new, extensive and constantly developing.
Why would you buy this book?
1.
The book presents the innovative technology with LP-models for evaluation, analysis, management and prediction of risk and efficiency in engineering and economics.
 
2.
The book describes components, models and procedures of information, intellectual, innovation technologies for risk management in a wide range of real problems.
 
3.
The book describes the classes of risk models: LP-modeling, LP-classification, LP-efficiency and LP-forecasting and the procedures for classes: construction of LP-models, LP-identification of risk LP-models according to statistical data, LP-analysis of risk, LP-management of risk, and LP-prediction of risk.
 
4.
The book gives many examples of effective applications of Risk management technologies: banking risks, analysis and risk management on economic indexes companies, the risk of explosion ammunition depot, the risk of providing electrical steel plant, etc.
 
5.
The book describes the failure risk LP-model of solution of difficult economic and engineering problems and projects, elements of which are subjects (government, business, banks, academics, public opinion) and objects (tasks in real problem).
 
6.
The book describes the specific Software for computationally complex problems in Risk management technologies.
 
7.
The book contents the training course Risk Management Technologies for university students, which has 40 lectures and 16 labs on PC.
 
8.
The book proposes the technique of construction of LP-models for estimation of the quality and validity of the functioning systems and processes in ISO 9000-2008.
 
9.
The book proposes LP-models for operational risk of banks and assess reserve by requirements of BASEL-2.
 
E. D. Solozhentsev
Backmatter
Metadaten
Titel
Risk Management Technologies
verfasst von
E.D. Solozhentsev
Copyright-Jahr
2012
Verlag
Springer Netherlands
Electronic ISBN
978-94-007-4288-8
Print ISBN
978-94-007-4287-1
DOI
https://doi.org/10.1007/978-94-007-4288-8

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