Risk Management Tasks Research Articles

Selection of representative natural hazard scenarios for engineering systems

AbstractRepresentative hazard scenarios are essential for many tasks in risk management, such as preparedness and emergency response planning. However, criteria and methods for systematically selecting such scenarios for natural hazards are lacking. From a risk perspective, such scenarios should be selected considering the losses they incur. Hence, we propose to define a scenario that is representative for a certain degree of loss, for example, the 100‐year loss, as the most likely one among all possible scenarios leading to this loss. Taking basis in a generic model of natural hazards and their impact on engineering systems, we formally introduce the representative scenarios. We then develop algorithms that enable an efficient evaluation of these scenarios. The method and algorithms are demonstrated on a hypothetical example considering a spatially distributed infrastructure system subjected to earthquakes.

데이터 보안의 함의(含意)와 입법방향에 관한 소고

In this article, data security is considered almost identical to cybers ecurity. The development of information and communication technolo gy contributed to the transition to an information society. However, t he protection of information security, privacy, and freedom of inform ation in cyberspace has become an important role for the nation. However, Korea does not have a legal system that governs data se curity in cyberspace yet. Therefore, it is impossible to systematically carry out risk management tasks for cyberspace. Against this backgr ound, the need to legislate the data security law is being raised. In this article, the author analyzed the implications of data securit y. And the data security laws of major countries were analyzed and compared with that of Korea. Through this process, implications we re drawn. The result is as follows. Firstly, an integrated data security law that encompasses the public and private sectors should be enact ed. Secondly, the data security law should include special provisions on the processing of personal information. Thirdly, cooperation with the international community should be strengthened. Fourthly, comm unication should be strengthened in the legislative process to reach a social consensus. In addition, the subject of political disputes in the legislative proc ess should be avoided. And the basic values of the constitution must be protected.

Gold future forecasting based on HAR model from 2019 to 2021

In the international monetary system, gold plays a significant role. Predicting gold prices is a useful and unique skill for anybody. As a result, improving one's ability to anticipate gold futures is critical. The study presented in this paper relates to gold futures predictions, based on heterogeneous autoregressive (HAR) theory, and Heterogeneous Autoregressive model of Realized Volatility (HAR-RV model), coupled with gold's daily trade volume and CBOE Volatility Index (VIX) to create three unique models: Heterogeneous Autoregressive model of Realized Volatility and Trading volume (HAR-RV-T model), Heterogeneous Autoregressive model of Realized Volatility and Volatility Index (HAR- RV-VIX model), and Heterogeneous Autoregressive model of Realized Volatility, Trading Volume, and Volatility Index (HAR-RV-T&VIX model). This paper mainly explores a method to predict the volatility of gold futures. Improve the ability to forecasting the volatility of gold prices is obviously conducive to effectively play the futures, including hedging, risk management, price analysis, and other tasks. The research concludes that adding trading volume and sentiment indicator contributes to a more robust HAR model and performs better on forecasting.

RISK MANAGEMENT IN AGRICULTURE: ACCOUNTING AND ANALYTICAL ASPECT

Enterprise risk management enables agricultural organizations to anticipate risks that could affect productivity and performance and take the necessary steps to minimize adverse factors and maximize competitive opportunities. Obtaining reliable risk information enables in resource-constrained settings to assess overall resource needs, prioritize resource use, and improve resource allocation. In addition, the viability of an organization in the medium and long term depends on its ability to anticipate and respond to changes, not only for stable functioning, but also for progressive development. This determines the relevance of the study, the task of which is to analyze and study the prospects for building a risk-based accounting, monitoring and management system. The risk management systems of a number of agricultural organizations in two agro-oriented regions were studied: the Rostov Region and the Altai Territory. The logic of the study consisted in a consistent and interconnected consideration of the problems of the functioning of agriculture in the regions; threats of violation of the economic security of organizations in the analyzed industry; issues of organizing an information system that meets the tasks of risk management; methods and strategies of risk management in agriculture. The authors concluded that it is necessary to transform the accounting and analytical system of agricultural organizations. The main direction of this transformation is the integration of strategy development, management methods and management accounting tools. The measurement of the underlying performance factors and the organization’s response to risk generate strategic opportunities and key competitive capabilities for agricultural organizations.

Модельный риск и базовые подходы к его численному измерению на примере моделей оценки рыночного риска

Model risk is currently a topic of great interest both to the academic community and to the financial industry; however, there is not yet any generally accepted approach to measuring it as of now. We give a review of basic model risk definitions and different indicators and approaches to model risk estimation and calculation within a common setting. The subject of this work is model risk itself that arises while using models to estimate financial risk and its quantitative indicators. The study is of particular relevance to financial institutions which for a long time have been actively applying different risk models. Since there is no generally accepted way to do so, choosing the exact approach becomes an important step in modelling. The aim of the paper is to demonstrate different approaches to model risk estimation on the same example of estimating the model risk of Value-at-Risk models and compare them within one setting. Methods used: analysis of time series, theoretical distribution parameters estimation. The result of the work is a list of methods and approaches for estimating and calculating model risk with the examples of applying these methods to a real risk-management task with appropriate interpretation. This work can be useful for researchers and risk managers of financial institutions.

Dynamic importance allocated nested simulation for variable annuity risk measurement

AbstractEstimating tail risk measures for portfolios of complex variable annuities is an important enterprise risk management task which usually requires nested simulation. In the nested simulation, the outer simulation stage involves projecting scenarios of key risk factors under the real-world measure, while the inner simulations are used to value pay-offs under guarantees of varying complexity, under a risk-neutral measure. In this paper, we propose and analyse an efficient simulation approach that dynamically allocates the inner simulations to the specific outer scenarios that are most likely to generate larger losses. These scenarios are identified using a proxy calculation that is used only to rank the outer scenarios, not to estimate the tail risk measure directly. As the proxy ranking will not generally provide a perfect match to the true ranking of outer scenarios, we calculate a measure based on the concomitant of order statistics to test whether further tail scenarios are required to ensure, with given confidence, that the true tail scenarios are captured. This procedure, which we call the dynamic importance allocated nested simulation approach, automatically adjusts for the relationship between the proxy calculations and the true valuations and also signals when the proxy is not sufficiently accurate.

УПРАВЛІННЯ ФІНАНСОВИМИ РИЗИКАМИ ПІДПРИЄМНИЦЬКОЇ ДІЯЛЬНОСТІ В УМОВАХ КРИЗИ

Nowadays, entrepreneurial activity in the field of small business plays an important role in the development of the Ukrainian economy. Economical activity of enterprises in the sphere of small business is connected with financial risks, management of which is considered to be the indispensable condition for ensuring its stable and effective functioning. The article examines the key aspects of the management of financial risk of entrepreneurial activity under crisis. The analysis of business development in Ukraine was carried out. The meaning of definition "financial risk" is presented. It is indicated that one of the most important areas of financial policy of small businesses at the present stage is the formation of key conditions for the management of financial risks, which are aimed at ensuring profit growth, minimization of financial costs, ensuring the necessary liquidity, etc. The key factors of financial risk have been identified. An assessment of financial risk factors has been carried out. The main functions of financial risk management have been identified. The methods for determining the probability of financial losses were established and analyzed, and their advantages and disadvantages were defined. It is indicated that one of the main functions of financial risk management in small business sector is to optimize financial flows. Optimization of financial flows involves the selection and application of the most optimal forms of organization of financial activities taking into account the specifics of the implemented enterprise strategy. Measures for the improvement of income receipts have been requested. An algorithm for assessing financial risks of the enterprise on the basis of the analysis of the sensitivity of cash flows was developed. The article offers suggestions on the optimal way of assessing financial risks in small business. As a result, it is noted that the management of financial activity in the sphere of small business is one of the main tasks of risk management of the enterprise. However, the financial management system of such a business activity has its own specifics and for ensuring the development of the business it has to be extensive.

An integrated approach for evaluating and improving the performance of surgical theaters with resilience engineering

Operating rooms are among the most high-risk and vital parts of a hospital. Therefore, one of the most fundamental tasks of risk management is maintaining the safety of operating rooms. Resilience engineering (RE) can be introduced as a model for overcoming problems, and it seeks ways to raise success rates by focusing on and addressing complexities. To this end, an RE-based framework is presented to evaluate the performance of operating rooms. First, the RE indicators are identified, and the relative importance of each is calculated via the best-worst method (BWM). Subsequently, the required data are collected from operating room experts using a standard questionnaire. Next, a data envelopment analysis (DEA) method is employed to evaluate the performance of operating rooms in the study case. Lastly, drawing upon the sensitivity analysis and statistical tests, the effect of each RE indicator is examined on the surgical department. Accordingly, some improvement approaches are proposed. Besides, SWOT (strengths, weaknesses, opportunities, and threats) analysis is used to extract appropriate strategies to improve performance. To the best of our knowledge, this paper is the first to evaluate the performance of operating rooms quantitatively in terms of RE indicators, and the framework presented in this paper can have practical applications in different operating rooms.

Analysis of methods for assessing and managing cyber risks and information security

Global trends to increase the threats to information and cybersecurity, increasing the level of vulnerability of information and telecommunications systems (ITS) necessitate the development and implementation of new standards and regulations on information security, the introduction of new technologies and best practices in information security. The main approach to information and cybersecurity in ITS is the Risk-Based Protection Strategy. The main task of information risk management (IR) is to identify and assess objectively the most significant risks for the company's business, as well as the need to use risk controls to increase the efficiency and profitability of the company's economic activities. It is believed that quality risk management allows you to use the optimal efficiency and cost of risk control and information protection measures, adequate to the current goals and objectives of the company's business. The paper presents results of solving the current problem of finding optimal methods for assessing the risks of information and cybersecurity. Criteria for selecting the best methods of risk assessment are proposed. The analysis of known methods of risk assessment for compliance with these criteria is performed. Proposals have been formulated to create promising methods for risk assessment, their application to modern information security management systems, especially those designed for critical infrastructure, will most effectively address the problems of information and cybersecurity, as well as privacy.

Asset criticality and risk prediction for an effective cybersecurity risk management of cyber-physical system

Risk management plays a vital role in tackling cyber threats within the cyber-physical system (CPS). It enables identifying critical assets, vulnerabilities and threats and determining suitable proactive control measures for the risk mitigation. However, due to the increased complexity of the CPS, cyber-attacks nowadays are more sophisticated and less predictable, which makes risk management task more challenging. This paper aims for an effective cybersecurity risk management (CSRM) practice using assets criticality, predication of risk types and evaluating the effectiveness of existing controls. We follow a number of techniques for the proposed unified approach including fuzzy set theory for the asset criticality, machine learning classifiers for the risk predication and comprehensive assessment model (CAM) for evaluating the effectiveness of the existing controls. The proposed approach considers relevant CSRM concepts such as asset, threat actor, attack pattern, tactic, technique and procedure (TTP), and controls and maps these concepts with the VERIS community dataset (VCDB) features for the risk predication. The experimental results reveal that using the fuzzy set theory in assessing assets criticality supports stakeholder for an effective risk management practice. Furthermore, the results have demonstrated the machine learning classifiers exemplary performance to predict different risk types including denial of service, cyber espionage and crimeware. An accurate prediction of risk can help organisations to determine the suitable controls in proactive manner to manage the risk.

What do we still need to learn on digitally assessed biomarkers?

What do we still need to learn on digitally assessed biomarkers?

Application of FTA Analysis for Calculation of the Probability of the Failure of the Pressure Leaching Process

European Union legislation requires organizations to assess their processes in the context of risk management. The main task of risk management is to manage all risks that can significantly affect the outcome of processes. The article is focused on risk evaluation in pressure leaching at elevated temperature using the method Fault Tree Analysis (FTA). The effectivity of pyrite and arsenic pyrite decomposition by oxidative pressure leaching is influenced by the duration of the process, by the temperature, concentration of the leaching solution and by a density of the slurry. It was found that, under equitable conditions, the arsenic pyrite decomposes more intensely than pyrite. Under laboratory conditions, leaching is performed in an autoclave. Due to the aggressive environment, increased pressure and temperature, process failure is possible. Its probability was calculated by FTA. It has been found that the probability of the top event in the examined process was disproportionately high (0.057) and represents an invitation to take corrective actions. The Monte Carlo method was used for the simulation of the effect the probability of basic events on the probability of the top event—the failure of the leaching process.

Probabilistic Flood Hazard Maps from Monte Carlo Derived Peak Flow Values—An Application to Flood Risk Management in Zamora City (Spain)

All flood hazard and risk assessment suffer from a certain degree of uncertainty due to multiple factors, such as flood frequency analysis, hydrodynamic model calibration, or flood damage (magnitude–damage functions) models. The uncertainty linked to the flood frequency analysis is one of the most important factors (previous and present estimation point to 40%). Flood frequency analysis uncertainty has been approached from different points of view, such as the application of complex statistical models, the regionalization processes of peak flows, or the inclusion of non-systematic data. Here, we present an achievable approach to defining the uncertainty linked to flood frequency analysis by using the Monte Carlo method. Using the city of Zamora as the study site, the uncertainty is delimited by confidence intervals of a peak flow quantile of a 500-year return period. Probabilistic maps are derived from hydrodynamic results, and further analysis include flood hazard maps for human loss of stability and vehicle damage. Although the effect of this uncertainty is conditioned by the shape of the terrain, the results obtained may allow managers to achieve more consistent land-use planning. All those Zamora city results point out the probable underestimation of flood hazard (the higher hazard areas increase around 20%) and risk when the uncertainty analysis is not considered, thus limiting the efficiency of flood risk management tasks.

Метод оптимизации техногенных рисков в электроустановках производственного объекта

The level of technogenic safety at the production facilities of the Russian Federation is expressed by low values. In this regard, the fire situation is a major hazard: a significant share is represented by the fires that occur at the electrical installations (up to 30 %). Fire risk analysis includes the determination of the probabilities of the occurrence of a fire and its consequences in order to obtain the risk numerical value that determines the fire safety of the object, and its comparison with an acceptable (tolerable) level. The use of a semantic description of risk-forming factors characterizing a hazardous event, their linguistic assessment and the level of significance allows to obtain a range of numerical values for the fire risk of electrical installations. Mathematical modeling is accompanied by the construction of a two-dimensional vector characteristic of the quantitative and qualitative criteria for the integral risk of fire in the electrical installations, which represents a functional dependence on the indicators of the probability of a fire occurrence and the severity of its consequences (material damage). Description of the dynamic model a «human — electrical installation — environment», its life cycle, determines the characteristics of the system considering the fire conditions, and represents five stages: dynamic balance; violation of dynamic balance; destructive action (explosion, fire); restoration of normal functioning; the acquisition of a normal state. Based on this description, the fire risk numerical values at the electrical installation are obtained. When calculating fire risks, it is required to consider the nature of the «human — electrical installation — environment» system, since it is subject to the action of random processes and risk-forming factors that are caused by the presence of electrical installations and the external environment. Improvement of the electrical installations safety system requires using the new technical solutions, and the development of an algorithm for a technogenic safety management system. The main task of fire risk management is to optimize its level. The fire risk is used as a criterion determined by the totality of risk-forming factors of the human-machine system.

Risk assessment for contagion path in complex loan network

Small and medium-sized enterprises (SMEs) loans play an essential role in many aspects: including technological innovation, economic development, employment, and peoples livelihood, etc. In order to meet the loan evaluation criteria of commercial banks, many SMEs choose to guarantee each other to obtain loans, thus forming a complex guarantee network. If the borrower defaults on the loan, the risk will be diffused to its guarantors along with the contagion path, which may lead to systemic risk across the loan networks. This has brought severe challenges to the nations financial security and regulation. Thus, accurately rating the contagion path is an urgent task for systematic risk management in the loan network. Therefore, we present a deep learning-based approach to the risk rating of contagion paths in the bank industry. We leverage the graph neural network and attention mechanism on graph-structured loan behavior to learn high-order representations, which do not require handcraft feature engineering. We demonstrate that our approach outperforms the existing baselines with 2%$\\sim$15% improvements in risk rating and 3.5% in the newly constructed path rating problem. The result demonstrates the effectiveness of our proposed approach, which provides an effective method and theory basis for regulatory commissions and financial institutions to monitor systematic risks in networked-guarantee loans.

Ризик менеджмент надзвичайних ситуацій

The article is devoted to risk management of emergencies. Approaches to the interpretation of the terms "risk" and "risk management" are studied. The factors influencing the process of making managerial decisions and the principles of implementation of risk management tactics and strategies are considered. The stages of risk development, the main tasks of risk management are considered. The construction of the risk management process and the factors influencing the formation of the risk management system of emergencies are studied.

The expected-based value-at-risk and expected shortfall using quantile and expectile with application to electricity market data

Forecasting risk measures in order to minimize and prevent a worse risk is an important and challenging task in quantitative risk management. Methodology and assessment of forecast accuracy are still developed to give a better risk measure forecast. In this paper, we provide a simple procedure to forecast expected-based risk measures of Value-at-Risk (VaR) and Expected Shortfall (ES). These risk measures may be determined by not only quantile but also expectile. By extending the Historical Simulation (HS) method and adopting the Monte Carlo (MC) principle, we build alternative algorithms without disregarding the (estimated) probability and/or distribution function(s) of the loss distribution. Based on the illustration for return data from New South Wales (NSW) Australian and Iranian electricity markets, it is found that our proposed method gives the expected-based risk measure forecast with better accuracy, instead of using the conventional HS method. The accuracy is getting higher when we consider the model able to capture the features of heavy-tailedness and conditional heteroscedasticity in the data.

Reconstruction of ER Network from Specific Academic Texts for the Governance of MSW-NIMBY Crisis in China

Along with urban development globally, the NIMBY (Not-In-My-Backyard) crisis has been a complex social problem, which requires urgent remedial action. The inevitable management of Municipal Solid Waste (MSW) has been one of the toughest risk management tasks in the worldwide modernization process. At present, certain fuzzy and unstructured results and methods have been formed for MSW-NIMBY crisis response, mainly focusing on the sociology and politics which scatter in complex and sensitive reports and news. Aiming at enhancing the effectiveness of data mining from specific sparse text of MSW-NIMBY crisis, an improved knowledge extraction method is developed. Through rule-based text mining and complex network analysis, the Entity Relationship (ER) network of MSW-NIMBY crisis is reconstructed. Meanwhile, a novel transitivity for relationship between entities in semantic analysis is proposed to improve the feasibility and accuracy of information extraction. Characteristics and regularity of MSW-NIMBY crisis evolution and experience of crisis governance could be identified effectively. Results show that knowledge integration and ER transitivity can enhance knowledge recognition and major other factors, which could help formulate the governance strategies of NIMBY crisis from academic texts.

Security Is a Surrogate for Development Management

The desire to avoid the consequences of extreme social and economic situations under capitalism and globalization, including financial relations, encourages the state authorities to use various measures of protection from threats. This has been reflected in the creation of many relevant doctrinal and conceptual documents. The public demand has stimulated the development of risk management theory and security studies. The real science and practice of management to achieve goals in this environment is pragmatically replaced by regulation to prevent border-critical situations. However, no system of scientific knowledge has been obtained in applied scientific research on the security of socio-economic systems, explaining some set of special phenomena and reducing the open natural connections in the field of security, if there were any, to a single unifying principle. The search for such a beginning leads to the task of management. It was not possible to find objective grounds for determination of safety space boundaries (threshold values) of social and economic systems. Applied research methods are not specific to security and risk management issues and are used in management theory. Either maintenance of safety appears a private subtask in a context of the decision of a boundary problem of management of development of system, or at expanded interpretation of safety within the limits of the vital approach, as a desirable condition, actually merges with management problem for achieving the target condition. Artificial separation of the security task from the management task generates an imaginary contradiction between security and development, in the practical aspect leads to substitution of strategic management by security, creation of parallel institutions, and dispersion of resources. It is advisable in the scientific and practical spheres of management of socio-economic systems to concentrate efforts on solving the problems of strategic management of the system development in order to achieve a favorable (desired) future. Security and risk management tasks should be considered as local subtasks of ensuring the integrity of the system under specific impacts.

An Exceedance Probability of Financial Return and Its Application to the Risk Analysis

This paper studies a new specification of the autoregressive binary choice model for estimating the exceedance probability of return and its application to the risk management tasks, especially for Value-at-Risk calculation. The author proposed a new parametrization of the volatility equation, which implies the presence of an additional random term. Such a model could not be estimated using the methods of classical statistics; therefore the Bayesian NUTS algorithm was chosen as an appropriate toolkit. Estimated exceedance probabilities were applied in calculating VaR. As a data set, it was taken the daily return of PAO «Sberbank» shares and the one-minute return of the USD-RUB currency pair. The results of VaR estimation were tested for asymptotic convergence to the true value by Engle and Manganelli’s dynamic quantile test.