Academic literature on the topic 'Probabilistic statistical method for estimating the risk of financial losses'

The reform of the energy sector in the Republic of Belarus, which in the last few years has moved to the stage of active implementation, will bring significant changes in the management of energy enterprises. The introduction of risk management for energy enterprises will become a necessary stage, which is justified by the transition of the energy sector to market relations. In this regard, it is necessary to consider the main issues of risk assessment for energy enterprises. The paper proposes a method for qualitative and quantitative analysis of all the risks that an energy enterprise may face in the process of energy generation. The approaches of various authors to the algorithm of qualitative risk analysis have been considered in the paper. This has made it possible to clarify the main tasks that need to be solved when conducting a qualitative risk analysis. The paper also presents an analysis of methods for quantitative risk analysis. The most commonly used methods include scenario analysis and mathematical statistics, analogy and analytical methods, methods for assessing losses, expert assessments and the theory of statistical games. Each of these methods has its own advantages and disadvantages. The performed analysis of quantitative risks has permitted to substantiate the choice of methods applicable to the energy sector, taking into account the specificity of activity type. The paper has studied various scales for estimating the probability and possible losses from risks. A comparative analysis of these scales is presented and the choice of a scale for energy enterprises is justified in the paper. Attention has been paid to the problem of probability classification pertaining to occurrence of risk events. The methodology for determining the value of possible losses when performing a risk event has been considered in detail. Potential losses are classified into the following groups: interruptions in the technological process, consequences for people, environmental consequences. Possible financial losses, as well as losses from the position of the law and reputation, have been considered separately. A critical review of risk management methods has been performed in the paper. The paper has identified the most promising methods of risk management for energy enterprises

The risk-based capital (RBC) ratio, an insurance company’s financial soundness system, evaluates the capital adequacy needed to withstand unexpected losses. Therefore, continuous institutional improvement has been made to monitor the financial solvency of companies and protect consumers’ rights, and improvement of solvency systems has been researched. The primary purpose of this study is to find a set of important predictors to estimate the RBC ratio of life insurance companies in a large number of variables (1891), which includes crucial finance and management indices collected from all Korean insurers quarterly under regulation for transparent management information. This study employs a combination of Machine learning techniques: Random Forest algorithms and the Bayesian Regulatory Neural Network (BRNN). The combination of Random Forest algorithms and BRNN predicts the next period’s RBC ratio better than the conventional statistical method, which uses ordinary least-squares regression (OLS). As a result of the findings from Machine learning techniques, a set of important predictors is found within three categories: liabilities and expenses, other financial predictors, and predictors from business performance. The dataset of 23 companies with 1891 variables was used in this study from March 2008 to December 2018 with quarterly updates for each year.

Introduction. It is shown that the development of methods for modeling multicomponent risks is a promising direction for improving information and analytical support for control in security systems. The purpose of the study is to develop new approaches to the study of natural, technogenic and anthropogenic risks based on stochastic modeling of the structure of multicomponent risks in socio-technical systems. Methods of stochastic modeling are based on a matrix representation of risk components, detailing the states of the protected object and the probabilistic characteristics of the functioning of security systems. Results and discussion. A method for analyzing multicomponent risks is presented, reflecting in-depth detailing of the states of the protected object and the probabilistic characteristics of the functioning of security systems. A stochastic model has been built that describes the structure of risk as a result of the interaction of two components, a multiplier and an accelerator, associated with various elements of the model, which, respectively, determine the possibility of occurrence of dangerous events, as well as the degree of vulnerability of protected objects. A connection is established between the indicators of expected losses in a certain territory with the presence of forces, means and systems of protection against the effects of hazardous factors and their current state. The procedures for determining the main parameters of the proposed stochastic model based on statistical and expert methods are discussed. A mathematical toolkit has been created for comparative analysis of the effectiveness of measures to reduce risks in socio-technical systems. The problem of multicriteria combinatorial optimization of planned costs and distribution of financial, material, technical and labor resources in territorial security systems is formulated. Conclusions. Methods for modeling multicomponent risks can be used to create effective algorithms for supporting risk-oriented management in security systems. Key words: stochastic modeling, multicomponent risk, socio-technical system, risk management, security system.

Роботу виконано в Інституті прикладного системного аналізу Національного технічного університету України «Київський політехнічний інститут імені Ігоря Сікорського».
У дисертаційній роботі розроблено системну методологію аналізу та оцінювання фінансових ризиків, яка ґрунтується на принципах системного аналізу та менеджменту ризиків, а також запропонованих принципах адаптивного та динамічного менеджменту ризиків. Методологія включає: комбінований метод обробки неповних та втрачених даних, ймовірнісно-статистичний метод оцінювання ризику фінансових втрат, динамічний метод оцінювання ризиків, який передбачає побудову різних типів моделей виживання, метод структурно-параметричної адаптації, застосування скорингової карти до аналізу ризиків фінансових систем і нейро-нечіткий метод доповнення вибірки відхиленими заявками. Містить критерії урахування інформаційного ризику, оцінки якості даних, прогнозів та рішень, квадратичний критерій якості опрацювання ризику та інтегральну характеристику оцінювання ефективності методів менеджменту ризиків. Практична цінність одержаних результатів полягає у створенні розширеної інформаційної технології та інформаційної системи підтримки прийняття рішень на основі запропонованої системної методології.