Risk Management Methods Research Articles

Методика управління кадровими ризиками підприємства

This article analyzes the essence of personnel risks of enterprises and develops a methodology for managing them. The methodology for managing personnel risks of an enterprise primarily involves identifying the risk and identifying its components. It also includes various aspects of the process of managing personnel and the enterprise as a whole, the key elements of which are: personnel risk factors; indicators of personnel risks; probable losses or gains; methods of personnel risk management; budgeting; Implementation deadlines. It is noted that the development of methods for managing personnel risks begins only when the critical point of the onset of negative consequences of the implementation of personnel risks in the functioning of the enterprise is reached, which entail serious problems. The main methods of managing personnel risks of an enterprise have been identified, which include preventive and reactive methods. The preventative method is to eliminate personnel risks before they reach the crisis stage. The reactive method is aimed at eliminating the negative consequences of personnel risks. Both methods should be used in the process of managing personnel risks of an enterprise. The proposed system of methods for managing personnel risks of an enterprise, built on the main stages of the personnel management process, allows us to formulate a number of recommendations in order to neutralize the impact of personnel risks, namely: recruitment, selection and selection of personnel, adaptation of personnel to working conditions at the enterprise; employee assessment and certification; personnel training and development; dismissal of workers. It has been proven that managing personnel risks requires the use of a set of measures to eliminate them. For this purpose, it is advisable to use risk transfer methods through outstaffing, outsourcing or personnel leasing. It is indicated that the management of personnel risks of an enterprise is closely related to the goals and objectives of the strategic development of the enterprise; personnel management system; personal assessment of employees and continuous identification and monitoring of the performance of enterprise personnel. Based on the results of the study, the main directions for minimizing the impact of personnel risks of the enterprise were identified, and the main methods for avoiding them were proposed.

Comparative Analysis of Methods of Evaluating Human Fatigue

AbstractThe present study used four different methods to estimate fatigue. Forty-seven volunteers (45 men and 2 women), 41.3 ± 7.5 years old, truck operators for 11.5 ± 6.0 years, were included. All participants accepted the invitation to be included in the study. Actigraphy and core temperature were evaluated. The 5-minute psychomotor vigilance test, the Karolinksa Sleepiness Scale (KSS), and the postural assessment using the Light Sonometer™ (Belo Horizonte, Minas Gerais, Brazil) were performed. Fatigue prediction was performed using the Fatigue Avoidance Scheduling Tool (FAST) program. In response to the Pittsburgh Sleep Quality Index (PSQI), 51.06% had good sleep quality and 48.94% had poor sleep quality with an average efficiency of 81.6%. In response to the actigraphy, workers slept an average of 7.2 hours a day with 93.5% efficiency. The workers' core body temperature (CBT) cosinor analysis showed a preserved circadian curve. Core body temperature showed differences between the 6 hours worked in each shift. Similarly, the light sound level meter showed lower risk scores for fatigue in day shifts. Only the variable of the fastest 10% of the Psychomotor Vigilance Test (PVT) showed worse results, while no significant differences were observed by the KSS. The risk analysis by FAST showed a strong influence of the circadian factor. In conclusion, each method has positive and negative points, and it is up to the evaluator/manager to identify the method that best suits the purpose of the evaluation, as well as the local culture and conditions. We recommend using different methods of risk assessment and management in combination with fatigue prediction by Sonometer as well as carrying out assessments, which enable researchers to estimate performance and fatigue throughout the working day, since these may change over the duration of the working day.

Концептуальные вопросы создания систем управления рисками промышленных предприятий

The article reveals the fundamental issues of creating risk management systems for industrial enterprises and provides a brief description of the main approaches to identifying risks and related goals and assessment methods. The aim of the study is to summarize modern foreign theoretical approaches to the creation of enterprise risk management system. Using the method of bibliographic analysis, an overview of modern main conceptual foreign approaches to understanding enterprise risks and risk management is given. The interrelation between risk reduction (elimination) activities and the types of risks undertaken is elucidated. Various applications of risk management systems within companies are presented, along with examples of the most common risk management systems employed by industrial enterprises and a synthesis of the experience in applying the most effective risk management methods. The conclusion emphasizes the necessity of meticulous risk identification and analysis in building corporate risk management systems. Moreover, the presented examples of successful risk management systems serve as valuable benchmarks for industry practitioners seeking to enhance their risk mitigation capabilities. Moving forward, continued research and refinement of risk management methodologies are essential for adapting to evolving business landscapes and ensuring the resilience of industrial enterprises in the face of uncertainty. Ultimately, proactive risk identification and analysis remain pivotal in fostering a culture of risk-awareness and resilience within organizational frameworks.

Analysis of Huawei's Financial Risk Management from the Perspective of Financial Indicators

With the continuous development of China's socio-economy, overall enterprise growth faces certain limitations; deeper economic reforms and market opening create a more challenging external environment for businesses. This implies that companies will encounter more challenges. To ensure that enterprises can operate normally and successfully achieve their business objectives, it is necessary to correctly understand financial risks and adopt rational risk management methods to avoid or reduce potential losses. This paper takes Huawei Technologies Co., Ltd. (hereinafter referred to as "Huawei") as an example and analyzes its financial indicators. Through financial data, it identifies the issues and causes of the company's financial risk management, and discusses how to prevent financial risks in enterprises, aiming to assist companies in achieving sustainable development in a fiercely competitive environment.

Analisis Risiko Proyek Pada Konstruksi Bangunan: Tinjauan Literatur

Risk is defined as an uncertain event or condition that, if it occurs, can have either a positive or negative effect on the project objectives. This effect can be avoided by using risk management methods, to identify risks, assessing risks either quantitatively or qualitatively, and choosing the appropriate method for handling risks will minimalized the effects. In the study, the scope was to identify the potential risk occurs on steel building work based on the previous research. Using sources based on the previous research, here will be identifying what types of risk factors are most commonly occurs for steel building work. The types of risk that will be discussed here will be divided into three types based on internal risk, external risk, and project risk. Each type of risk includes technical and non-technical risks. Based on the data this study identify that internal risk with technical aspects is the most common type of potential risk occurs on steel structure building work.

A pre-control method in safety risk management of metro construction

ABSTRACT With the rapid development of metro construction in China, construction safety accidents occur frequently due to the lack of effective safety risk controls. Continuously improving the level of safety risk pre-control has become a significant factor in the safety managements of metro construction. This paper presents a reasoning model for safety risk pre-control measures in metro construction using case-based reasoning. To establish the case database, a frame-based knowledge representation method is adopted based on the characteristics of metro construction safety accident cases. Additionally, a two-level retrieval strategy combining hierarchical retrieval and nearest-neighbor algorithms is used for case retrieval. Furthermore, a new approach, the cloud model, is proposed to determine the attribute weight of metro construction safety accidents. This approach addresses quantitative attributes with fuzziness and randomness. Finally, a specific metro station is taken as a case to validate the feasibility of the approach. The results showed that the case-based reasoning method enables engineers to quickly and effectively develop risk pre-control measures based on previous cases. In addition, the use of case-based reasoning in decision-making enhances knowledge sharing and reuse in the metro construction industry. This paper presents an effective reasoning approach for pre-control measure analysis in metro construction, allowing engineers to quickly and efficiently carry out scientific and reasonable pre-control measures from past cases.

Scenario mapping for critical infrastructure failure under typhoon rainfall: A dependency and causality approach

The critical infrastructure system exhibits a high degree of instability because of the frequent occurrence of extreme natural disasters. This study proposes a method for exploring the cascading failures of critical infrastructure systems under such impacts, based on dependency relationships for importance analysis and probability assessment. With this method, a cascading failure scenario graph of critical infrastructure is established and empirical research is conducted using typhoon rainfall events as a case study. The main contributions of this study are summarized as follows: it proposes a method for the causal identification of the interrelationships among critical infrastructures; it sorts and evaluates the importance and cascading failure probability of critical infrastructure by using the Interpretative Structural Modeling (ISM) and Rank-order Centroid method (ROC); and it generates scenario graphs of critical infrastructure cascading failures to visualize event states, environmental characteristics, and evolutionary paths. This study provides a new method and tool for disaster risk management of complex systems involved in critical infrastructure.

Impact of Sound Decision-Making on Small and Medium Businesses in Pakistan

This research aims to investigate the significance of sound decision-making in the success and sustainability of Small and Medium Businesses (SMBs). The study will concentrate on key constructs such as risk management, financial stability, innovation and adoption, and customer relationship management. The study uses a quantitative approach, surveying a sample of SMB owners and managers in Pakistan's different industries to gather data. In order to find out how respondents feel about decision-making processes and how they affect SMB performance, a structured questionnaire is used. Regression analysis is one of the statistical techniques used to examine the data and evaluate the hypotheses. The results demonstrate how important sound decision-making is to the resilience and success of SMBs in Pakistan. Financial stability stands out as a crucial component that impacts the performance of small and medium-sized businesses (SMBs). This is followed by efficient risk management, innovation and adoption, and customer relationship management. These results highlight how crucial strategic decision-making is for promoting SMB sustainability and growth in a fast-paced business climate. The results provide useful information to managers, owners, and regulators of SMBs who want to improve SMB decision-making procedures. Small and medium-sized businesses (SMBs) can enhance their competitive standing, boost operational effectiveness, and promote long-term growth and profitability by placing a high priority on financial stability, proactive risk management, innovation, and customer-centric methods

Le principe de précaution en médecine : vingt ans après

ObjectivesThe precautionary principle (PP) is a risk management method in situations of scientific uncertainty. Its lack of precise definition in official texts led to numerous interpretations in the past. The PP was initially limited to the environment. The extension to human health raised fears of an increase of proceedings and an interference with innovative research. MethodTwenty-four people involved in the precautionary principle have been interviewed and a literature review has been carried out. ResultsA renewed analysis of the PP has emphasized several points: the PP is a complex process that includes a spirit of caution, rigorous reasoning, and evaluation of hypotheses and, lastly, precautionary measures. The major part of confusion raises when the PP is in danger of drifting into inappropriate precautionary measures; individual care medicine is well controlled by the “Code de déontologie médicale” (Code of Medical Ethics); biomedical research has scientific constraints and its own rules. In these two medical fields, PP is not applicable unless a major innovation raises an ethical problem; on the other hand, public health may be submitted to the PP. ConclusionConsequently, mastery of the PP implies to promote training actions devoted to medical doctors, administrative and political decision makers, educational establishments and the media.

Impact of Herding Behavior on Mutual Fund Performance

n this study, we look at how herd mentality affects the efficiency of mutual funds. It is well-documented that investors often engage in herding behaviour in the financial markets, when they blindly follow the actions of others rather than evaluating information independently. Yet, there has been a dearth of empirical research into its particular consequences for mutual funds. To analyse the impact of herding behaviour on fund performance, this research uses a thorough dataset of mutual fund returns and investor flows. The first step of the research is to use literature-established metrics to determine whether mutual fund investors herd. After that, we use risk-adjusted returns, volatility, and alpha to evaluate the herding behaviour vs. fund performance connection. The research further delves into the ways in which herding affects the performance of funds by looking at things like trading fees, liquidity restrictions, and market circumstances. Herding behaviour has a substantial impact on mutual fund performance, according to preliminary data. However, the exact nature of this impact varies across fund kinds and market conditions. Although herding may provide short-term gains in price momentum and liquidity-driven returns, it eventually causes mispricing and reversals if it continues. In addition, less liquid asset classes may have their long-term performance eroded by herding-induced trading costs and portfolio churn. These results have consequences for fund managers and investors alike. By learning the ins and outs of herd mentality, investors may make better investing choices that stay true to their long-term value drivers and avoid the traps of herd mentality. To lessen the impact of market emotion on fund performance, fund managers should be aware of investors' herding tendencies so they can create portfolios and use risk management methods. Keywords – Herding Behavior, Mutual Funds, Investor Behavior, Market Sentiment, Performance Measurement

Statistical analysis of flood risk perception: a case study for Eastern Black Sea Basin, Turkey

It is very essential in terms of flood risk management to consider social expectations such as risk perception, flood awareness, preparedness, and socio-economic dynamics together with engineering designs. Understanding the way people perceive flood risk can enhance our capability of improving existing flood risk management methods, thus helps us creating disaster resilient societies. In this study, results of a questionnaire which was used for a previous study and had been administered to participants from Eastern Black Sea Region of Turkey were further investigated using statistical methods. The main aim was to understand how demographic factors such as age, gender and education level affect people’s flood risk perception. It was also desired to see that whether they were aware of the parties responsible for taking mitigation measures, or whether they know about possible flood mitigation measures or not. Using the same data with the previous study, but in addition using SPSS software to do statistical analysis, questionnaire results were investigated using convenient statistical tests for each parameter, analysis results were interpreted, and conclusions were drawn. Same tests were conducted using weight coefficients adopted using a certain methodology which is explained in the paper, in order to make a better investigation. Also, results were compared with the results of the previous study. It was seen that there were some consistencies and contradictions between the results of the previous study and this study’s results.

Integration of stakeholder management and risk management methods in projects of housing and communal services providers

The object of research is stakeholder and risk management processes in the projects of housing and communal services providers. In conditions of constant change and uncertainty, such management becomes key to ensuring the success and sustainability of projects in this area. The problem addressed by the study is the development and analysis of an integrated model that combines stakeholder management with risk management, with an emphasis on innovation and performance improvement. The essence of the obtained results is the identification of key points of interaction between stakeholders and risks, as well as the development of complex strategies for their effective management. The model is based on a combination of qualitative and quantitative methods of analysis, including structural-logical analysis, SWOT analysis, as well as the use of expert evaluation methods. The results are explained by the need for a deeper integrated approach to stakeholder and risk management, especially in the context of housing and communal services (HCS), where the interaction between these elements directly affects the success of projects. This approach allows not only to identify potential problems at an early stage, but also to respond to them more effectively. The innovativeness of the proposed model lies not only in its comprehensive approach to the analysis and management of stakeholders and risks, but also in the possibility of its scaling and adaptation to various conditions and projects in the field of housing. The application of this model includes the intensive use of modern analytical tools, which contributes to more accurate forecasting of risks and more effective solving of problems related to stakeholders. This, in turn, allows utilities providers to increase the quality and reliability of the services provided, strengthening trust and satisfaction among users. Also, the model provides for the active involvement of stakeholders in the project management process, which ensures greater openness, transparency of actions and the ability to quickly adapt to changing market conditions. The research results can be used in practice in the field of housing and public utilities to optimize project management, increase their efficiency, and reduce risks. This will be especially relevant in cases where an integrated approach to management is needed, considering both the requirements and expectations of stakeholders, as well as potential risks.

Внедрение методов анализа больших данных (Big Data) для управления рисками в нефтегазовом комплексе

в данной научной статье рассматривается внедрение инновационных методов анализа больших данных (Big Data) для эффективного управления рисками в нефтегазовом комплексе. Актуальность данной темы обусловлена растущей необходимостью повышения эффективности и безопасности операций в нефтегазовой отрасли, которая сталкивается с множеством рисков, таких как аварии, простои оборудования, колебания цен на энергоносители и геополитическая нестабильность. Целью исследования является разработка комплексного подхода к управлению рисками на основе анализа больших данных, который позволит нефтегазовым компаниям принимать более обоснованные решения и минимизировать потенциальные убытки. В ходе исследования были использованы различные методы, включая сбор и обработку больших объемов структурированных и неструктурированных данных из различных источников, таких как датчики на месторождениях и НПЗ, финансовые отчеты, социальные сети и новостные ленты. Для анализа данных применялись передовые технологии, такие как машинное обучение, глубокое обучение, обработка естественного языка и предиктивная аналитика. Были разработаны специализированные алгоритмы и модели для выявления закономерностей, аномалий и потенциальных угроз в режиме реального времени. Результаты исследования показали, что внедрение методов анализа больших данных позволяет существенно повысить эффективность управления рисками в нефтегазовом комплексе. Например, с помощью предиктивной аналитики удалось снизить количество незапланированных простоев оборудования на 23% и сократить затраты на техническое обслуживание на 18%. Анализ данных о ценах на нефть и газ в сочетании с геополитической информацией позволил оптимизировать торговые стратегии и увеличить прибыль на 12%. Кроме того, выявление потенциальных угроз безопасности, таких как утечки и аварии, с помощью анализа данных с датчиков и камер наблюдения, позволило предотвратить серьезные инциденты и снизить экологические риски. Полученные результаты демонстрируют высокую эффективность применения методов анализа больших данных для управления рисками в нефтегазовом комплексе. Внедрение этих методов позволяет не только минимизировать потенциальные убытки, но и повысить общую эффективность и безопасность операций. Дальнейшие исследования в этой области могут быть направлены на разработку более совершенных алгоритмов и моделей, а также на интеграцию методов анализа больших данных с другими инновационными технологиями, такими как Интернет вещей и блокчейн. this scientific article discusses the introduction of innovative methods of big data analysis (Big Data) for effective risk management in the oil and gas industry. The relevance of this topic is due to the growing need to improve the efficiency and safety of operations in the oil and gas industry, which faces many risks such as accidents, equipment downtime, fluctuations in energy prices and geopolitical instability. The aim of the study is to develop an integrated approach to risk management based on big data analysis, which will allow oil and gas companies to make more informed decisions and minimize potential losses. Various methods were used during the research, including the collection and processing of large amounts of structured and unstructured data from various sources, such as sensors at fields and refineries, financial reports, social networks and news feeds. Advanced technologies such as machine learning, deep learning, natural language processing and predictive analytics were used to analyze the data. Specialized algorithms and models have been developed to identify patterns, anomalies and potential threats in real time. The results of the study showed that the introduction of big data analysis methods can significantly improve the effectiveness of risk management in the oil and gas industry. For example, predictive analytics has reduced the number of unplanned equipment downtime by 23% and reduced maintenance costs by 18%. The analysis of oil and gas price data in combination with geopolitical information allowed us to optimize trading strategies and increase profits by 12%. In addition, the identification of potential security threats, such as leaks and accidents, through the analysis of data from sensors and surveillance cameras, has prevented serious incidents and reduced environmental risks. The results obtained demonstrate the high efficiency of using big data analysis methods for risk management in the oil and gas industry. The implementation of these methods allows not only to minimize potential losses, but also to increase the overall efficiency and safety of operations. Further research in this area may be aimed at developing more advanced algorithms and models, as well as integrating big data analysis methods with other innovative technologies such as the Internet of Things and blockchain.

Risk Management Strategies for Waste-to-Energy Projects Utilizing BOT Models

Since the 1990s, with the implementation of the reform and opening up policy, the rapid development of China's economy, the progress of urbanization is getting faster and faster, and as one of the urban wastes, the treatment of domestic waste has also attracted more and more attention. The municipal solid waste incineration treatment, and the heat generated after combustion is used to generate electricity, referred to as "garbage incineration power generation", because this way can make the waste to reduce, harmless, and can be converted into part of the electricity, because it is widely used in the treatment of municipal solid waste by local governments. Due to the shortage of government funds, most domestic waste incineration projects are implemented in BOT mode. Waste incineration power generation projects are often a large investment, for investors, the recovery period is long, the technical requirements are high, the investment agreement signed with the government is also very complex, coupled with the imperfect supporting laws and policies in China, so that the process of waste incineration power generation projects have many problems and risks, through the operation, construction, investment and other links. Based on the theoretical content of risk management in project management and combined with practical cases, this paper puts forward countermeasures and suggestions for important risks in the project, so as to analyze and discuss the risks of garbage incineration BOT project. Firstly, this paper investigates and collates the research situation of relevant projects at home and abroad, and systematically summarizes the project research results from three aspects, namely, BOT risk management of waste incineration power generation projects, BOT model of projects and BOT project risk research. Secondly, the multi-case study method was used to analyze the risks of 3 typical waste-to-power generation BOT projects, collect risk factors, construct risk aggregation, and summarize 5 types of key risks and 14 kinds of risks. Then, according to the BOT agreement signed with the government side, the specific risk management method is proposed. The goal of this study is the LF waste incineration power generation project. The author participated in the project and identified and evaluated the project risks through risk list and hierarchical analysis, so as to find out the main risks in the project such as government risk, public opinion risk, completion risk and operational risk. In addition, in combination with the project risk, specific risk coping strategies are proposed according to the risk coping strategies proposed in the paper and the actual situation of the project, so as to reduce the degree of project risk and reduce risk losses. For other similar projects in China, there is reference and reference significance and value.

Unveiling flood vulnerability in the Vietnamese Mekong Delta: A case study of an Giang province

Flood risk management is a critical concern worldwide, as communities and regions face increasing threats of flooding due to climate change, urbanization, and natural variability. As a headwater province of the Vietnamese Mekong Delta, An Giang is considered the most vulnerable to the impacts of floods. We thus applied a flood assessment framework that combines natural disaster (floods), economic, social, environmental factors with a set of 42 criteria in terms of hazard, exposure, and vulnerability. The Analytic Hierarchy Process method was used to weight these criteria before flood risk maps were made to assess their scales. Our results revealed that Khanh An and Long Binh communes, primarily located in An Phu District at the border between Vietnam and Cambodia, are at the highest hazard levels with scores of 0.68. Tinh Bien District where is relatively far from An Phu, although not heavily inundated, has a high level of vulnerability. Overall, 10 out of the 155 communes in the province (6.5%) were at high flood risk since these communes, mostly located in An Phu, have predominantly agricultural areas with a relatively poor population. In addition, 121 communes (78%) demonstrated a moderate flood risk level while the rest (15.5%) is very low or not at any risk. Mitigation measures should be developed to reduce flood risk across the province within the VMD context while this study sheds light to worldwide deltas on developing similar methods for flood risk management.

Co-design of a digital violence prevention and management tool for psychiatric inpatient care: focus on supporting integration into electronic health record system

IntroductionViolence in psychiatric inpatient settings is a global challenge. Several methods have been developed and tested to help staff prevent the occurrence of violence on the wards. One novel and effective method is eDASA+APP, originating from Australian forensic psychiatric settings (Maguire et al. Int J Ment Health Nurs 2019; 281186-1197, Griffith et al. Psychiatr Serv 2021; 72 885-890). This electronic method contains an instrument (DASA) to assess the risk for imminent violence and includes evidence-based violence risk management methods for risk levels. It is important to ensure that this electronic intervention is integrated into daily clinical practice. This can be done in co-design between all that are involved e.g., staff and experts by experience, and by encouraging them to achieve a common goal and gain benefits by working together.ObjectivesThis prevention gives an overview of how the Finnish version of eDASA+APP was co-designed with healthcare staff and experts by experience, focusing on integration into the electronic patient health record system. The presentation is part of a larger research project testing eDASA+APP in Finnish psychiatric inpatient care.MethodsCo-design workshops focusing on three major themes: 1) identifying current practices and how eDASA+APP would fit in those, 2) producing a linguistically and culturally appropriate version of eDASA+APP, and 3) preferred use of eDASA+APP in an electronic patient health record system. Notes were kept during the workshops by researchers. Qualitative material were analysed with deductive content analysis. Results from the third theme are shared in this presentation.ResultsStaff and experts by experience described that integration of eDASA+APP in electronic patient health record system is supported if it 1) brings clear and fast information to the staff about the violence risk of a patient, 2) is a visible measure that is concretely in sight in electronic patient health record system, 3) provides information about which violence prevention and management interventions have worked with a patient, 4) involves patient preferences, and 5) consist of joint decisions that have been agreed multi-professionally.ConclusionsIntegration of eDASA+APP in the electronic patient health record system has the potential to succeed if it is realized in cooperation with staff and experts by experience, is technically easy to use, and the users have an understanding of its benefits to everyone involved.Disclosure of InterestNone Declared

Identification of Hazards and Risk Assessment in the Workplace of PT. Nusantara Traisser Site PT. Vale Indonesia Sorowako, South Sulawesi

The mining industry has a high risk of accidents, thereby prioritizing the understanding of safety and occupational health aspects. This research discusses the potential hazards and risk values for each work area of Nusantara Traisser Ltd. at the site of Vale Indonesia Pte Ltd. in 2023. Potential hazards came from field observations, and risk assessments were conducted by analyzing the probability, exposure, and consequence values of each identified hazard. These values were then adjusted according to the semi-quantitative risk level standards of William T. Fine. This research employed an observational approach using the AS/NZS 4360:2004 method for risk management. The results of the study indicated that the total number of potential hazards identified in the four work areas was 11, each with its respective risk value. The highest risk level reached 300, classified as priority 1, involving the hazard of mining traffic in the Anoa North Ground Training area (Mines HSOR Department) and the Enggano Coal and Sulfur Storage area. The recommended risk controls for each work area include elimination, engineering control, administration, and personal protective equipment (PPE).

Application for Machine Learning Methods in Financial Risk Management

Financial risk management has significant importance and implications for individuals, businesses, investors, and even the whole nation. As the financial markets and institutes grow complex so does the risk associated with financial management. The spectrum of financial risks includes market risk, liquidity risk, credit risk, and a range of others. With a multitude of portfolios and sophisticated products, financial firms require apt tools that can accurately measure the risk, returns, and exposure. The growing complexity has also made statistical and simulation tools ineffective and there is a growing emergence of machine learning. Machine learning is a sub-category of artificial intelligence that uses algorithms. These algorithms analyze data and then learn from it so that a decision based on a certain experience or criteria can be made. Machine language tools provide data protection as the information is only accessible to the key decision-makers. Deep learning is modeled like a human brain and therefore it operates using multiple layers of artificial networks and can process and use a very vast amount of data.

Концептуальний підхід до управління ризикостійкістю підприємств роздрібної торгівлі

The essence of the concepts: "concept", "conceptualization", "conceptual model" is characterized. The conceptual approach to the management of risk resistance of a retail trade enterprise has been improved, which involves the use of a system of interrelated theoretical and methodological provisions regarding the idea, laws, goals, tasks, principles, functions, categories, methods of influence and methodology of risk resistance management. A comprehensive system of risk management principles of a retail enterprise has been formed, which integrates general and specific principles. The author's reasoned position regarding the consideration of the essence of the concept of "risk resistance", which boils down to the need to consider it as an internal property of the risk management system, which contributes to ensuring the target level of performance of the retail trade enterprise under the negative influence of a wide range of external and internal factors. A model of communication of management, marketing and risk management functions at a retail enterprise has been developed. The methods of risk management in retail enterprises are characterized (avoidance (rejection of risk), localization, dissipation, compensation, retention, transfer (outsourcing), reduction).

Manajemen Risiko Reputasi Perbankan Syariah

Inherent risk is the risk attached to the business activities of Islamic banks, whether quantifiable or not, which has the potential to affect the financial position of the bank. Risk management applications, especially the risk of reputation for Islamic banks, either individually or for banks by way of confirmation by The children's industry does not include the active supervision of the board of commissioners, the board, and the DPS, policies, methods, and determination of limits, as well as methods of identification, measurement, control, and risk management and risk SIM. This risk arose, among others, due to the presence of media reports and rumors about banks having a negative attitude and the existence of an inefficient bank communication strategy. A negative announcement to one Islamic bank would tarnish the good name of another Islamic bank, even though other Islamic banks did not participate in this responsible action. The best reputation risk management method is to implement a predictive or preventive action program and a reputation maintenance program. Risk A good name is an abstract risk and is an intangible asset for the industry. Prosecution of reputational risks should be in a preventive way because the cost of handling this risk is very large and can eventually disrupt and kill the industry.