Operational Risk Analysis Research Articles

RISK MANAGEMENT PRACTICES OF ISLAMIC AND CONVENTIONAL BANKS OF PAKISTAN: A COMPARATIVE STUDY

This paper is the report of a study that has investigated the impact of the risk management process, including liquidity and operational risk, on the risk management practices of Islamic banks and conventional banks in Pakistan. The study compared the risk management practices of both types of banks. Data was collected through the 200 self- administered questionnaires distributed to senior managers and risk officials of both types of banks. The data was analyzed using basic descriptive statistics, One-way ANOVA and Multiple regression analysis. The empirical results showed that risk assessment and analysis, risk monitoring and liquidity risk analysis were the most influential determinants of the risk management practices of conventional banks, whereas risk identification, risk assessment and analysis, credit risk analysis, liquidity risk analysis and operational risk analysis had influenced the risk management practices of Islamic banks. Overall, Islamic banks were better in terms of understanding risk management, risk identification, risk assessment and analysis, risk monitoring and operational risk analysis, while conventional banks were ahead of Islamic banks in credit risk analysis, liquidity risk analysis, and risk management practices. In the context of the emerging economy of Pakistan, the study outcomes can be helpful for investors, potential and existing customers to make prudent investment decisions. Findings are also helpful for strategy managers and regulators in policy formulation, elevation, and implementation of risk management regulations.

Methodological approaches to the construction of a risk structure model for investment construction projects in the field of occupational safety and health

Investment construction projects are implemented under constant changes, which forces managers to assess the uncertainty and risks they generate, to manage changes in their own activities and activities of construction organizations. The article describes the main methodological approaches to the development of a model of risks of investment construction projects in the field of labor safety and protection. The approach is based on the method of quantitative assessment depending on the level of processes being evaluated and data characterizing these processes. The proposed concept will make it possible to develop an algorithm and a computational and analytical model for the subsequent automation of the process of quantitative assessment of risks and the dynamics of their change on the basis of the information-digital system. For example, the Corporate Occupational Safety Management System, developed and used by NIPIGAZ JSC to manage occupational safety processes, ensure industrial and fire safety, environmental protection, will make it possible to put into practice the methods of predictive and operational risk analysis, increasing the efficiency of the investment construction project.

Resilience of Milk Supply Chains during and after the COVID-19 Crisis in Latvia

Abstract The impacts of the COVID-19 pandemic on national economies are characterized as the worst economic turmoil in recent years, as economic growth slowed to the level of the 2008 global financial crisis. At the end of 2019 and the beginning of 2020, economic growth surveys did not project that the novel virus could have a negative impact on economic growth. As a result of the rapid spread of the virus and the increase in the number of infection cases, national governments took strict measures to limit the spread of the virus, which led to a significant deterioration in the economic situation in all industries of the economy. Agriculture plays an important role in providing food to the country’s population, yet the pandemic made a negative impact on sales volumes and prices in the domestic and international markets. The research aims to assess the impacts of the pandemic on milk supply chains in Latvia and come up with solutions to stabilizing the situation in the dairy sector. The national restrictions to combat the pandemic also hampered the dairy sector concerning the sale of raw milk and finished products in foreign markets, thereby leading to overproduction and stockpiling of the finished products, price dumping and a significant decrease in milk purchase prices to or below the production cost level for many dairy farms. Although there is no indication that the pandemic would lead to a decrease in the numbers of livestock and farms or output in early 2021, it is too early to assess the overall impact of the pandemic on dairy farming, as uncertainty over the duration of pandemic restrictions is a major risk to farm survival. The operation of the dairy sector was stabilized by means of the support provided by the government, as well as the farms’ accumulated financial and feed resources. In order to identify future challenges for milk supply chains, the research performed an analysis of operational risks for milk producers and processors to identify the most important risks and design recommendations for their elimination. The longer there is uncertainty about the return of the dairy sector to pre-pandemic output levels, the more likely it is that the pandemic is going to lead to a decrease in the numbers of dairy livestock and farms.

An Analytical Risk Analysis Method for Reservoir Flood Control Operation Considering Forecast Information

Risk analysis is vital for reservoir flood control operation considering forecast because forecast uncertainties may create risks of multiple hazard events, including the single-hazard events, the union and intersection of single-hazard events (UHE and IHE). The probability of UHE and IHE are the major concern of decision-makers. This research proposes an analytical flood risk probability calculation framework for single-hazard event, UHE and IHE caused by uncertainties in flood forecasting and takes Dahuofang Reservoir, located in the Hunhe River basin, Northeast China, as a case study. In the framework, the risk is calculated by the integral of the joint probability density function (Pdf) of the risk sources over the hazard domain, which is the collection of the values of risk sources that cause hazards. The determination method of the hazard domain and the Pdf of risk sources and the procedure of risk analysis are elaborated. Results of single-hazard events show that the proposed methodology is of higher precision compared with the risk analysis method based on the law of total probability. Meanwhile, the flood risks of UHE and IHE are calculated for the reservoir operation under different levels of flood limit water level. The study provides a new method of flood risk analysis for flood control reservoir operation.

A fuzzy logic risk control and self-assessment metrics for e-banking operational risk analysis

Operational risk is the risk of losses arising from the failure or inadequate internal processes, human resources, systems, and external events that affect the bank's operations as defined by Basel Committee on Banking Supervision. Defining a suitable set of risk measurement metrics is considered one of the most important issues for any risk analysis. It enables the quantitative evaluation of the risk exposure level and the effectiveness of internal control system. Risk measurement is needed to provide an effective means to quantify the risk of existing or planned systems to enable understanding of the overall security level and to guide decision making. Given the number of successful attacks against financial Institutions and the sophistication of the tactics used by attackers, existing classical measurement approaches are no longer enough. This study focuses on fuzzy logic-based metric identification to measurement of the risk exposure level, to enable financial institutions to see the overall risk level and security state of their E-banking systems and to assist with decision making. This will provide a newer dimension to risk management by shifting from risk measurement based on probability and classical set theory to Fuzzy Logic (FL) measurement. In this paper fuzzy logic-based metrics is presented and expressed as a function of six factors (triggering events, avoidance, recovery, Undesirable Operational State (UOS), cost of Undesirable Operational State (UOS) occurrence and severity of risk occurrence) as proposed by [1].

Risk Analysis for Short-Term Operation of the Power Generation in Cascade Reservoirs Considering Multivariate Reservoir Inflow Forecast Errors

In the short-term operation of the power generation of cascade reservoirs, uncertainty factors such as inflow forecast errors could cause various types of risks. The inflow to a downstream reservoir is not only affected by inflow forecast errors from upstream reservoirs but also the forecast errors associated with inflow to the stream segment between the reservoirs, such as from a tributary. The inflow forecast errors of different forecast periods may also be correlated. To address this multivariate problem, the inflow forecast error variables were jointly fitted in this study using the Gaussian mixture model (GMM) and a t-Copula function based on the analysis of the error distribution characteristics in different forecast periods. Therefore, a stochastic model that coupled with the GMM and t-Copula to calculate inflow forecast errors in multiple forecast periods was established. Furthermore, according to the simulation results of the stochastic model and the predicted runoff series, a set of simulated runoff processes were obtained. Then they were combined with the existing power generation plan to carry out the risk analysis for short-term operation of the power generation in a cascade reservoir. The approach was evaluated using the Jinguan cascade hydropower system within the Yalong River basin as a case study. For this case study, the risk analysis for short-term operation of the power generation was analyzed based on stochastic simulation of the inflow forecast errors; the results show the feasibility and effectiveness of the proposed methods.

Operational Risk Analysis at Agribusiness and Technology Park (ATP) IPB, Bogor, Indonesia

ATP IPB is an autonomous business unit under Teaching Farm Sub Directorate of IPB’s Business and Entrepreneurship Development Directorate. It produces fruits and vegetables from its own farm and farmers as its partners, and also sells the produces mainly to modern markets. It faces risks in operating its business, especially operational risk. This study aims to: (1) identify ATP operational risk, (2) measure risk based on likelihood and impact, (3) analyze the root causes of ATP operational risk, and (4) provide alternative solutions to the underlying causes. The study was conducted in January to April 2019. Risk level map, risk map, and cause-effect diagram were employed in this study. Results showed three main risks, namely (R1) the output of ATP’s partner did not reach the target, (R2) the output of ATP’s partner exceeded the target, and (R3) the farmer’s production did not reach ATP standard. Risk R2 is included in the low risk level, risks R1 and R3 are included in the extreme risk level. The root causes of the three risks are ineffective penalties, no priority for the screen-house, no priority for increasing the workforce, relationship between supervisor and partner farmers are still transactional. Alternative solutions that can be proposed are participatory assistance, contract review, screen-house implementation, and the formation of farmer groups.\\

Discussion on Operation Risk Analysis and Emergency Management Construction of Urban Large-scale Horticultural Exposition

With the development of society, the urban large-scale horticultural exposition has increasingly become one of the manifestations of enriching people's lives, but the issue of safety management has always been an important research topic. Taking Beijing World Horticultural Exposition as an example, this paper systematically analyzes the operation risk of large-scale horticultural exposition, and expounds on the characteristics of possible risks of the world horticultural exposition from the perspective of the existing nature of risks, and puts forward the construction plan of perfecting the responsibility system of emergency management. It aims to provide a theoretical reference for the operation risk analysis and emergency management of large-scale horticultural fairs.

The concept of global governance in tourism franchises: a case study of TUI group

The study characterizes the global corporate governance in the context of tourism. Risks the TUI Group would face during the implementation of the global governance strategy were assessed. The analysis of management and operational risks revealed that in conditions of global economic uncertainty tourism companies may use risk diversification to ensure flexibility. The risk likelihood assessment justified the need for the use of innovative management models with the aim of reducing the likelihood and impact of risks. An organizational-managerial framework for risk diversification was established that enables companies to cope with the global challenges in a synergistic effort. Finally, the study explored the socio-economic impact of global governance strategy on the competitive regional tourism.

An Operational Risk Analysis Model for Container Shipping Systems considering Uncertainty Quantification

Different uncertain factors obstruct the analysis of operational risks in container shipping, especially those rooted in the subjectivity of multiple risk assessments and their aggregation. This paper proposes a risk analysis model featuring a quantification of the uncertainty. Bayesian probability theory is employed to quantify the risk magnitude, while a dedicated module to handle uncertainty is enabled by Evidential Reasoning and a set of three uncertainty indicators, including expert ignorance, disagreement among experts, and polarization of their assessments. The situation of risk is diagnosed by risk ranking and visualized by risk mapping, using both Risk Magnitude Index and Uncertainty Index. The functionality of the proposed model in identifying critical and uncertain risks was demonstrated in an organizational-scale case study, followed by an examination of validity criteria and a sensitivity test. The case study reveals the physical flow as the dominant origin of high-ranking risks with potential significant consequences such as piracy, dangerous cargoes, and maritime accidents; while information and financial operational risks are more uncertain, especially cargo misdeclaration and unexpected rises of fuel costs.

Operational risk analysis of blowout scenario in offshore drilling operation

Offshore drilling is a complex and hazardous operation. The safety of the drilling operation is a strong function of many time-dependent parameters. The traditional risk analysis model fails to capture the impact of spatial and temporal variations of these parameters. This paper presents a Bayesian Network (BN) model for the offshore drilling operation. The model uniquely considers the evolution of hazards as a function of time and space, and failure of the safety barriers. The model development is explained using the bowtie approach, which is routinely used in the industry for risk management. The bowtie model is subsequently transformed into a BN model and simulated for the well blowout scenarios. The blowout risk is updated based on operational field observations. An uncertainty analysis is also conducted to capture the spatial variability of the parameters. The results of the BN model provide a dynamic risk profile of the blowout accident during the drilling operation. Other possible accident scenarios, such as lost circulation, can also be analyzed using the proposed model. The proposed BN model serves as a robust tool for risk management of offshore drilling operations.

What should urologists know about SARS-CoV-2? Risk analysis for urological operations and recommendations for action in clinical routine

HintergrundDie COVID-19 („coronavirus disease 2019“) stellt Gesundheitssysteme weltweit vor eine große Herausforderung. Mit steigenden Infektionsraten geraten auch Urologen wegen eines Infektionsrisikos mit SARS-CoV‑2 („severe acute respiratory syndrome coronavirus 2“) bei operativen Eingriffen in den Fokus. Hierdurch entsteht die Notwendigkeit über das Coronavirus sinnvolle und umsetzbare Handlungsempfehlungen zu erstellen.Ziel der ArbeitEs wurde eine umfassende Einschätzung des Infektionsrisikos mit SARS-CoV‑2 bei urologischen Eingriffen erstellt. Auf Basis der Datenlage sowie aktueller Empfehlungen nationaler und internationaler Richtlinien soll einerseits das Infektionsrisiko im Umgang mit humanen Geweben und Stoffen beurteilt und andererseits notwendige hygienische Maßnahmen beleuchtet werden. Letztlich sollen hieraus Handlungsempfehlungen und zu treffende Schutzmaßnahmen für die urologische Praxis abgeleitet und erklärt werden.Material und MethodenIn PubMed, bioRxiv und medRxiv sowie den Datenbanken der WHO und des RKI wurde eine Literatursuche über SARS-CoV‑2 und das chirurgische Prozedere bei infizierten Patienten durchgeführt. Der Zeitraum der Literatursuche war bis 21.04.2020.DiskussionAuf Basis der recherchierten Daten können generelle und spezifische Handlungsempfehlungen für die urologische Praxis abgeleitet werden. Zwar bleibt unklar, ob SARS-CoV‑2 letztlich über die entstehenden Aerosole übertragen wird, aber allgemeine Schutzempfehlungen bieten gerade bei chirurgischen Eingriffen in Zeiten der SARS-CoV-2-Pandemie vermutlich keinen suffizienten Schutz und sollten sorgfältig überdacht werden. Entscheidend dürfte hierbei ein konsequenter Einsatz von FFP-2-Masken, Schutzbrillen und Vollkörperanzug sein. Um eine Kontaminationsbelastung von Luft und Oberflächen einzudämmen, sollen komplexe Filtersysteme (HEPA), der Einsatz von zumindest begrenzt viruziden Oberflächendesinfektionsmitteln und intraoperative Absaugvorrichtungen Verwendung finden. Eine Fokussierung auf wenige, aber optimierte eigens hierfür bereitgestellte COVID-OPs ist nicht zuletzt unter dem Gesichtspunkt der Ressourcenschonung sinnvoll. Unter Einhaltung der entsprechenden Handlungsmaßnahmen kann ein für Urologen und medizinisches Personal sicheres Arbeitsumfeld geschaffen werden. Daher sehen die Autoren nach derzeitigem Wissensstand keine Kontraindikation für dringliche und Notfalleingriffe, vorausgesetzt entsprechende Vorsichtsmaßnahmen in ihrer Schutzwirkung werden eingehalten.

Misoperation monitoring and early warning during startup and shutdown of petrochemical units

Most petrochemical units run under extreme conditions, such as high temperatures, pressures, and speeds. Consequently, the equipment operators may commit errors because the startup and shutdown processes usually involve complicated operation steps; moreover, the operators may lack experience in handling abnormal situations. Misoperation can lead to accidents, including fires and explosions. Thus, risk analysis for process operations and the development of preventive measures have become an effective means of avoiding misoperation-related accidents. However, it is challenging to ensure the comprehensiveness of risk-analysis results. In this paper, we present a method for misoperation monitoring and early warning in the startup and shutdown processes of petrochemical units. The mechanisms of misoperation occurrence are summarized based on investigations of serious accidents in the recent past. Knowledge regarding the mechanisms of misoperation is crucial for the risk analysis of petrochemical units. The potential risk information, such as causes, adverse consequences, key monitoring parameters, and prevention control solutions, should be acquired and be employed to construct an early-warning knowledge database. Furthermore, misoperation judgment rules need to be formulated to identify misoperations. The data obtained from the monitoring module, misoperation judgment rules, and analysis results can aid in developing schemes to avoid possible abnormal situations. This paper reports a misoperation monitoring and early-warning system for a hydrogenation unit. As demonstrated, conducting risk analysis to determine the potential operational risks and formulating misoperation judgment rules to analyze the process data are essential for enabling early warning. The application of this method will contribute to operational guidance, economic loss reduction, and accident avoidance.

Risk analysis for reservoir flood control operation considering two-dimensional uncertainties based on Bayesian network

The uncertainty of initial water level being above the designed flood limited water level and the uncertainty of inflow caused by flood forecast error can cause flood risk in real-time reservoir flood operation. A risk analysis model for reservoir flood regulation under two-dimensional uncertainties based on Bayesian network is proposed. The nodes of Bayesian network are determined and the network structure is established with expert knowledge; the parameter learning is conducted with the training samples obtained from Monte Carlo simulation. Thereafter, through the prior probability inference without posterior information and the posterior probability inference with given posterior information, the variation of flood risk is analyzed under singular-factor uncertainty and two-factors uncertainties. The case study of Xianghongdian Reservoir using a flood of 100 years return period indicates: the risk resulted from inflow uncertainty is greater than that of the uncertainty of initial water level; there is a certain complementarity between the uncertainties of inflow and initial water level, and the combination risk is between the results of two single-factor risk levels. Moreover, Bayesian Network is able to conduct bi-directional inferences and infer the probability distribution of any other node, which has practical value for risk assessment and control of reservoir flood control operation.

Loss distribution approach for company operational risk analysis

The measurement of potential operational losses as an assessment of capital adequacy is needed by the company. One value that can be used to measure the potential loss of a company is Value at Risk (VaR). This paper aims to measure VaR based on the loss distribution using the Bayesian method where the loss frequency is assumed to be Poisson distribution and the loss severity is assumed to be the distribution Lognormal. VaR with Monte Carlo (MC) and Fast Fourier Transformation (FFT) simulations are compute using the values of the parameter of distributions that have been obtained by using the Bayesian method. In this paper, a numerical example of VaR estimation of a bank company is demonstrated to find the estimate VaR from several sources i.e. internal fraud, external fraud, business practices, employment practices, process failure, system failure and damage to assets. The results showed that the estimate VaR value equal to $ 8.2336044 with Monte Carlo and and $8.522028 with FFT simulation at 99% confidence level. These means that the company has the opportunity to experience operational risk losses which exceeds $ 8.2336044 and $8.522028 in the coming year by 1%.

HAZOP_LOPA-based operation process risk analysis and management research

At present, HAZOP analysis and LOPA analysis are widely used to analyze and control the risk of process flow, but few people manage HAZOP and LOPA for risk during operation. Through the research of HAZOP and LOPA analysis methods, combined with long-term work experience in the field, the author proposes to combine HAZOP and LOPA analysis methods into operational process safety risk analysis, and use the same subject expert team to identify the risks in the operation process. Control and control results also help to re-revise the operating procedures, conduct risk management and control from the operational level, and improve the completeness of safety evaluation. This paper introduces the basic method of HAZOP_LOPA joint analysis operation process, clarifies the analysis points, and lists the commonly used 8 types of guidance words. Finally, the risk of maintenance and maintenance operation of quick-open blind filter is analyzed by examples. The results show that Based on HAZOP_LOPA, operational risk analysis can quantitatively evaluate the reliability of existing protection measures, eliminate or reduce safety risks, and achieve safety risk review of operational procedures. This method improves the reliability of operating procedures and enhances the safe operation level of employees. It is of great significance.

Toward Business Integrity Modeling and Analysis Framework for Risk Measurement and Analysis

Financialization has contributed to economic growth but has caused scandals, misselling, rogue trading, tax evasion, and market speculation. To a certain extent, it has also created problems in social and economic instability. It is an important aspect of Enterprise Security, Privacy, and Risk (ESPR), particularly in risk research and analysis. In order to minimize the damaging impacts caused by the lack of regulatory compliance, governance, ethical responsibilities, and trust, we propose a Business Integrity Modeling and Analysis (BIMA) framework to unify business integrity with performance using big data predictive analytics and business intelligence. Comprehensive services include modeling risk and asset prices, and consequently, aligning them with business strategies, making our services, according to market trend analysis, both transparent and fair. The BIMA framework uses Monte Carlo simulation, the Black–Scholes–Merton model, and the Heston model for performing financial, operational, and liquidity risk analysis and present outputs in the form of analytics and visualization. Our results and analysis demonstrate supplier bankruptcy modeling, risk pricing, high-frequency pricing simulations, London Interbank Offered Rate (LIBOR) rate simulation, and speculation detection results to provide a variety of critical risk analysis. Our approaches to tackle problems caused by financial services and the operational risk clearly demonstrate that the BIMA framework, as the outputs of our data analytics research, can effectively combine integrity and risk analysis together with overall business performance and can contribute to operational risk research.

Process control system evolution for the LHC Cold Compressors at CERN

The Large Hadron Collider (LHC) operates using superfluid helium provided by eight large refrigeration units (2.4 kW @ 1.8 K each). These units supplied by specialized cryogenic industrial suppliers are composed of serial hydrodynamic cold compressors based on an axial-centrifugal impeller coupled with volumetric warm screw compressors. The process control systems delivered by the suppliers have been installed, commissioned and operated reliably for more than 13 years. However, the implemented process control closed configuration approach limits of the operational diagnostic, and required operational flexibility and adaptability of the cold compressors systems. In the frame of the CERN evolution of process control standards, the LHC cryogenic operational requirements together with the end of electronic components life cycle has motivated an upgrade of the whole process control system.Through a step-by-step analysis process including the initial operational risk analysis, CERN has conceived and engineered two prototypes with their dedicated functional analysis and process control logic to cover the complete range of system operation. These prototypes have been initially fully tested in an off-line configuration and after that validated in real system operation.This paper presents the whole process, the successful results obtained and the perspectives for the future deployment during the LHC Long Shut-Down 2 (2019-2020) period.

Improving barrier and operational risk analysis (BORA) using criticality importance analysis case study: oil and gas separator

PurposeThe purpose of this paper is to show the impact of operational and environmental conditions (risk influencing factors) on the component criticality of safety barriers, safety barrier performance and accidents frequency and therefore on risk levels.Design/methodology/approachThe methodology focuses on the integration of criticality importance analysis in barrier and operational risk analysis method, abbreviated as BORA-CIA. First, the impact of risk influencing factors (RIFs) associated with basic events on safety barrier performance and accident frequency is studied, and then, a risk evaluation is performed. Finally, how unacceptable risks can be mitigated regarding risk criteria is analyzed.FindingsIn the proposed approach (BORA-CIA), the authors show how specific installation conditions influence risk levels and analyze the prioritization of components to improve safety barrier performance in oil and gas process.Practical implicationsThe proposed methodology seems to be a powerful tool in risk decision. Ordering components of safety barriers taking into account RIFs allow maintenance strategies to be undertaken according to the real environment far from average data. Also, maintenance costs would be estimated adequately.Originality/valueIn this paper, an improved BORA method is developed by incorporating CIA. More precisely, the variability of criticality importance factors of components is used to analyze the prioritization of maintenance actions in an operational environment.

Intelligent early-warning analysis of operational risks based on grey Kalman filter

Intelligent early-warning analysis of operational risks based on grey Kalman filter