Operational Risk Analysis Research Articles

Implementation of the budgeting methodology and business planning based on risk assessment in a gas transportation organization

The authors have developed a methodology for budgeting and business planning, taking into account risk assessment, which allows to systematize the process of planning and making managerial decisions taking into account possible risks. The approach is based on an analysis of current and potential operational risks, as well as their integration into the budgeting and business planning process. The approbation of the methodology is carried out in a gas transportation organization.

The Risk Assessment of Banks and Financial Institutions

This thesis investigates the profound impacts of the COVID-19 pandemic on the banking sector, focusing on how the crisis has reshaped risk management and operational strategies. It begins by contextualizing the pandemic's effects within the broader historical challenges faced by the banking industry, drawing parallels with past financial crises to outline the uniqueness of the current situation. Through a detailed analysis of operational, credit, and market risks, this study reveals how banks have responded to the increased volatility and the shift in consumer behaviors towards digital banking solutions. The research adopts a mixed-method approach, combining quantitative data from financial reports with qualitative insights from industry experts to provide a comprehensive overview of the pandemic's impact. Key findings suggest that the crisis has catalyzed significant changes in risk management practices, with banks rapidly adopting technological innovations to enhance resilience and operational efficiency. The conclusion posits that the ongoing challenges require banks to evolve, advocating for a proactive approach to risk management and a strategic embrace of digital transformation. This thesis contributes to the academic literature by providing empirical evidence of the pandemic's impacts and offers practical recommendations for banks and policymakers to mitigate future crises effectively.

A new approach proposal for ensuring security engineering through barrier and operational quantitative risk analysis (BOQRA)

The advancement in petrochemical industry has led to a significant increase in accidents, a concern that cannot overlooked if we aim to ensure the safety of our systems while still meeting production objectives. To address these phenomena, several techniques and models have been developed; the most important of them is Quantitative Risk Analysis (QRA). A QRA is a systematic approach that aims to estimate the likelihood and consequences of hazardous events. Despite its effectiveness, it faces limitations associated with uncertainty, relying on average values within the database. To overcome this limitation, Barrier and Operational Risk Analysis (BORA) is integrated with QRA, incorporating frequency analysis of consequences into the QRA methodology. This developed approach, termed Barrier and Operational Quantitative Risk Analysis (BOQRA), enables the correction of entered data in the database for calculating individual and revised societal risks while counting for human, technical, and organizational aspects. Additionally, it identifies essential measures to control risks and manage the impacts of modifications and configuration changes. The BOQRA sheds the light of the influence of Risk Influencing Factors (RIF) on barriers and their performance within an operational system. As an illustrative case study, we examined the flask ball for separating oil and gas based on density.

Perspectives on risk analysis and control for real-time operation of flood control systems

Flood control operation, a non-engineering measure, can efficiently manage flood disasters within a river basin. However, numerous uncertainties exit in the real-time operation of flood control systems, creating risks in decision-making. As an efficient tool to mitigate these risks, risk management has garnered increasing attention in real-time flood control operation. This communication offers a series of suggestions for future research concerning risk management in real-time flood control operation, including risk assessment, risk diagnosis, and risk control methods.

Balance Analysis of Operational Risk Through the Aggregate Method in the Loss Distribution Approach

Balance Analysis of Operational Risk Through the Aggregate Method in the Loss Distribution Approach

Operational Risk Analysis of Steel Warehouses Using Failure Mode and Effect Analysis (Case Study: PT JKL Cold Rolled Coil Warehouse)

Operational Risk Analysis of Steel Warehouses Using Failure Mode and Effect Analysis (Case Study: PT JKL Cold Rolled Coil Warehouse)

Multimodal knowledge graph construction for risk identification in water diversion projects

The operation risks of water diversion projects involve numerous influencing factors, complex interrelationships, and heterogeneous data from multiple sources. This study presents a multimodal knowledge graph construction approach for water diversion projects, aiming to comprehend and identify the key risks associated with engineering operation and their propagation patterns. Utilizing term-masked pre-trained language models enhances comprehension of specialized terminology and identifies risk entities within the text. Employing high-order residual convolutional neural networks improves the processing capability for complex graph data, extracting risk information from images. Aggregating multimodal knowledge graphs based on the semantic relationships among entities and conditional probability to determine the coupled features of different risks. Employing complex network theory, analyze node degree and betweenness centrality to identify the diffusion effects and propagation levels of risks. The results indicate that the knowledge extraction accuracy of our method is high (with an average F1 score of 95.85%), enabling the qualitative analysis and quantitative calculation of operational risks in engineering. Relevant studies can effectively enhance the reliability of engineering safety management and reduce the impact of engineering risks on water supply security.

Operational risk estimation using system analysis methodology

Financial risks are considered today as popular research topics due to the existing practical necessity for the use of their mathematical models, estimates of possible loss in many areas of human activities, forecasting, and respective managerial decisions in financial and other spheres where capital, obligations, stocks, bonds, and other activities are circulating successfully. Financial processes today exhibit sophisticated forms of evolution in time that require the application of sophisticated modeling, risk estimating, forecasting, and decision-making/support methods, techniques, and procedures. The system analysis approach is applied to solving such problems as a unique and universal research methodology. The financial risks, specifically the operational ones in the study considered, are classified as nonlinear and nonstationary processes that require appropriate methods for analysis and a rather sophisticated analytical description to estimate and forecast possible loss. The results of operational risk analysis are achieved in the form of systemic methodology, models constructed with statistical data, regression analysis, and Bayesian techniques, and estimated loss with the models. The models and system analysis approach proposed for analyzing financial processes are suitable for practical applications, provided the users have appropriate statistical data and expert estimates.

Analisis Risiko Operasional Pada Proses Pembuatan Kerupuk Udang Sanah Kabupaten Tanjung Jabung Barat

The importance of knowledge about operational risks for umkm partners in order to be able to control or handle the risks that must be handled and be able to solve the problems being faced, so this research aims (1) to find out the identification of operational risks in the process of making Sanah shrimp crackers in West Tanjung Jabung district ( 2) to find out the operational risk analysis of the process of making Sanah shrimp crackers in West Tanjung Jabung district, (3) to find out the efforts made by umkm actors to overcome operational risks. This research uses qualitative methods in this research using data sources obtained from the owner of the Sanah shrimp cracker business and the Sanah shrimp cracker employees. The results of this research are: In identifying operational risks, there are four types of risks as follows: human resource risks include risks of events such as unsuccessful steaming, unsuccessful cutting of crackers, long frying of crackers, failed packaging and inadequate training. Technological risks include inappropriate machines and packaging equipment that does not function properly. As well as process risks, there are risks from raw materials that do not match the dosage. And external risks include risks such as unstable raw materials and uncertain weather factors. The risk analysis that occurs in Sanah shrimp crackers has a risk level of high, medium and low. As for the aspects included in the high category, there are three risks, namely inadequate training, inappropriate packaging equipment and raw materials that do not match the measurements. And there are also medium level operational risks including unsuccessful steaming, frying for too long, inappropriate machines, unstable raw materials, weather factors that result in long drying. And there are also two levels of low risk, namely cutting crackers, failed packaging. Efforts to overcome operational risks that occur in the Sanah shrimp cracker business include requiring or providing training to employees about managing shrimp crackers and employees also need to have self-awareness to be more skilled and more thorough.

Decision support system to evaluate a vandalized and deteriorated oil pipeline transportation system using artificial intelligence techniques. Part 2: analysis of the operational and economic risk

Abstract The changing supply and demand of hydrocarbons in recent years, generated by inflation, pandemics, and wars, have impacted its price considerably, developing limitations in maintenance processes in the oil industry worldwide; however, the mechanical deterioration of facilities due to corrosion does not stop. This article contributes original to the knowledge and management of a pipeline transportation system (PTS) without an immediate high impact that would help reduce property loss due to corrosion through the development of intelligent evaluation models that combine field data, laboratory, and cognitive knowledge in a case study in Mexico. The research is divided into Part 1 (Modeling; https://doi.org/10.1515/corrrev-2021-0080) and Part 2 (Operational and economic risk analysis of PTS under corrosive effects, using Monte Carlo simulation, MCS), supported by information and knowledge of 564 km of soils, from cathodic protection studies, essential to determine corrosive profiles of the PTS, considering supply and demand effects, with 1095 data on the price of the Mexican mixture from 2016 to 2019, as well as data monthly inflation rates for the same period, to generate financial estimates representative of the system, in search of replicable exchange actions and practices in international fields.

Capital reserve calculation analysis of operational risk in submarine cable service portfolio

This study analyzes the amount of capital reserves required for the Submarine Cable Service PT AAA to mitigate the risk of delays in completing work without disrupting the company's cash flow. Data used in this paper is the operational loss of delay work in the Submarine Cable Service portfolio from 2016 to 2019. The method and analysis used in this paper are the Monte Carlo simulation to calculate Operation Risk Variance (OpVar) by analyzing the distribution of severity and frequency. The result of the study shows that delayed work is the risk that has the most influence on the company's cash flow. PT AAA needs Rp 2.16 billion per event as capital reserve PT AAA to mitigate the risk of work delays in the Submarine Cable Service portfolio. Risk mitigation needs to minimize the potential loss are choosing the right partner in the operational process, scheduling the cable repair process, and securing the amount of capital reserve that has been counted.

Impacts of Flight Operations on the Risk of Runway Excursions

The Quick Access Recorder (QAR), as an onboard device used for monitoring and recording flight parameters, has been extensively installed on various types of aircraft. Recently, there has been a significant focus on studying the typical flight safety event of runway excursions based on QAR data. However, there is limited research that combines the analysis of runway excursion risks with flight operations, and there is also a scarcity of studies that divide the investigation of the landing phase into multiple key stages. In this paper, we propose a comparative analysis of operational characteristics and risks associated with runway excursions from the perspective of operational styles. A total of 2087 flights were classified on the basis of touchdown distance, taxiing distance, and magnetic heading changes and were divided into three styles based on these indicators. Subsequently, we analyze flight operations and attitudes at five key stages: runway threshold, flare, speed brake deployment, touchdown, and reverse thrust activation. Furthermore, we employ the selection criteria of pilot proficiency levels to filter out standard operational curves. The curve similarity is used to compare the difference between the actual operating curves and the standard curves. Finally, we employ typical correlation analysis to explore the relationship between touchdown distance and operational variances. The findings indicate that Style 1 pilots exhibit the lowest probability of runway excursions, yet their maneuvers potentially elevate the risk of hard landing events.

Dynamic risk analysis for oil and gas exploration operations based on HFACS model and Bayesian network

Oil and gas exploration (OGE) is an important part of the petroleum industry. How to predict and prevent risks of OGE accidents in a targeted way is still a challenge, while few researchers have focused on this issue because of the lack of data from the worksite. Therefore, the accident cases for decades of years in a globally operated OGE company are collected as a basis, a dynamic risk analysis method combining the human factors analysis and classification system (HFACS) and the Bayesian network (BN) has been proposed in this article. First, identify the accident cases, analysis, and divided the risk factors into four levels and 27 classification categories, and setup a HFACS-OGE model. Then, map the factors to the BN and identify the correlation of the secondary level factors. Finally, setup a BN model with the Genie software. Through posterior probability analysis and sensitivity analysis, we conclude the major and sensitive factors leading to OGE accidents. According to the conclusion, administrators could decide on corresponding management and control methods. This method can hopefully provide an effective quantitative basis for the identification and prediction of the factors that may lead to OGE accidents.

Operational Risk Analysis in The Logistics Industry: A Case Study of Jingdong Logistics

With the improvement in technology and economic system, China’s logistics industry continues to innovate and aspire to high-quality development to meet the people's pursuit of a higher quality of life. Still, in the process of innovation and change in logistics enterprises, it is inevitable that a certain degree of operational risk. Taking Jingdong Logistics as the research object, this study discusses the operational risks modern logistics enterprises face and proposes corresponding risk response measures. The study first introduces the importance of logistics in improving the quality of life and promoting national economic development. Then, it analyzes in detail the operation of Jingdong Logistics, as well as the customer management risk, market competition risk and financial risk it faces. Subsequently, the article proposes corresponding risk-coping strategies, including breaking the "bundling" with Jingdong Mall, optimizing the logistics supply chain, and improving profitability. These measures can help Jingdong Logistics cope with risks in the competitive modern logistics market, maintain competitiveness and achieve sustainable development. The article concludes by summarizing the important role of logistics enterprises in the modern economic system and emphasizing the importance of scientific risk management strategies for success in the highly competitive logistics market.

An In-Depth Analysis of Credit, Capital, and Operational Risks on Regional Development Banks' Performance Amidst the Covid-19 Pandemic

The Covid-19 pandemic has hit the world since the end of 2019 and has damaged the world economy, including Indonesia. Banking as a financial institution that provides funding to companies is also affected. Because the pandemic has reduced the company's performance, and this decline in performance has had an impact on banking. The aim of this research is to test whether the Covid-19 pandemic has an impact on the relationship between risk factors and bank performance. Bank performance is measured by profitability which consists of return on assets (ROA) and return on equity (ROE), while bank risk in this study consists of credit risk, liquidity risk, capital, operational risk and the Covid-19 pandemic. The population in this research is the Regional Development Banks (BPD) in Indonesia totaling 34 banks with a sample of 30 banks. The observation period was 4 years with quarterly data so that 320 observation data were collected. Hypothesis testing uses panel data regression, and to select the best regression model, the model will be tested using the Chow-test, Hausman-test, and Lagrange Multiplier test. After the model test was carried out, the fixed effect model was selected as the best model. The research results show that credit risk and operational risk have a significant and negative influence on all profitability, both ROA and ROE. Meanwhile, liquidity risk (LDR) has no effect on both types of profitability, while capital has an effect on ROE but has no effect on ROA. Another interesting result is that the Covid-19 pandemic has no impact on the influence of risk on bank performance.

Free fall drag estimation of small-scale multirotor unmanned aircraft systems using computational fluid dynamics and wind tunnel experiments

New European Union (EU) regulations for UAS operations require an operational risk analysis, which includes an estimation of the potential danger of the UAS crashing. A key parameter for the potential ground risk is the kinetic impact energy of the UAS. The kinetic energy depends on the impact velocity of the UAS and, therefore, on the aerodynamic drag and the weight during free fall. Hence, estimating the impact energy of a UAS requires an accurate drag estimation of the UAS in that state. The paper at hand presents the aerodynamic drag estimation of small-scale multirotor UAS. Multirotor UAS of various sizes and configurations were analysed with a fully unsteady Reynolds-averaged Navier–Stokes approach. These simulations included different velocities and various fuselage pitch angles of the UAS. The results were compared against force measurements performed in a subsonic wind tunnel and provided good consistency. Furthermore, the influence of the UAS`s fuselage pitch angle as well as the influence of fixed and free spinning propellers on the aerodynamic drag was analysed. Free spinning propellers may increase the drag by up to 110%, depending on the fuselage pitch angle. Increasing the fuselage pitch angle of the UAS lowers the drag by 40% up to 85%, depending on the UAS. The data presented in this paper allow for increased accuracy of ground risk assessments.

ANTECEDENTS OF DIGITAL FINANCING ON MSME IN BANK SYARIAH INDONESIA (BEFORE AND AFTER MERGER)

The aim of this research is to analyze the antecedents (factors which influence) of digital financing at Bank Syariah Indonesia (BSI). This study is focus on data before and after merger. The population of this study is employees of BRI (Bank Rakyat Indonesia) Syariah (before merger) and BSI (after merger) This study have eight objectives to analyze the effect of antecedents (accountability, adequacy of funds, accounting information, operational risk, internal control, and credit analysis) on digital financing for MSME at BSI. The sample was determined based on the random sampling method, in which 100 respondents were obtained using the Slovin formula. All respondents were asked to fill out the questionnaire that had been prepared based on indicators of variables. Data analysis was performed using Partial Least Square-Structural Equation Modeling (PLS-SEM). The research results indicate that from eight hypothesis, six of them are affect and two of them are not affect before merger, but after merger the results show that five of them are affect and three of them are not affect.

Simulation of the Gas Distribution Law and Operational Risk Analysis of a Vertical Gas Tank in a Ventilation State

As a type of airtight equipment, vertical gas tanks are prone to accumulations of toxic and harmful gases due to their poor ventilation and narrow space. This poses many safety hazards. Therefore, we conducted a FLUENT simulation for vertical gas tanks with different diameters. The results indicated that the larger the diameter, the longer the required ventilation time. It was necessary to monitor the gas concentration after ventilation for at least 6 h when the tank diameter was 2.6 m, after ventilation for at least 24 h when the tank diameter was 5.2 m, and after ventilation for at least 80 h when the tank diameter was 7.8 m. To ensure comprehensive monitoring, at least one monitoring point was required to be placed at the upper and lower ends of the vertical gas tank, respectively. Monitoring was initiated after these requirements were reached. A theoretical numerical analysis and an experimental verification analysis were conducted on the simulation results. The variation trend of the simulation value, the theoretical value, and the experimental test value were the same. The measured value of the ventilation duration was greater than the theoretical value of the ventilation duration and the simulation value of the ventilation duration. Therefore, the simulation results and theoretical analysis could be used for a risk analysis of gas tanks. The determination of ventilation characteristics via a simulation of vertical gas tanks has a practical significance when guiding on-site operations.

Zeroes of Multifunctions with Noncompact Image Sets

In this article we consider zeroes for multifunctions with possibly noncompact image sets. We introduce the notion of multifunction with K-inf-compact support. We also establish three types of applications: the Bayesian approach for analysis of financial operational risk under certain constraints, occupational health and safety measures optimization, and transfer of space innovations and technologies.

The application of big data technology in the predictive analysis of enterprise capital operation risk

The background of the big data era makes enterprise tax management face many opportunities and challenges, in order to improve the management of enterprise capital operation risks and promote the enterprise to take the road of sustainable development. This paper firstly indexes risk names with the help of web crawler technology, establishes data sources, and then circulates the crawler to obtain the required information. Secondly, a hashing algorithm is applied to compress the massive data into a unique and extremely compact section of hash values by means of constant mapping. Then association rules are used to determine the set of frequent risk items, and the values of the two are continuously changed to derive the final predictive analysis. Finally, a capital operation risk prediction and analysis platform is built by combining the above processes. In this paper, the effectiveness of the proposed platform is verified, and the practical results show that the accuracy of the proposed platform for risk prediction discovery is as high as 97%, and the time spent for risk discovery is controlled within 30 minutes. The relevant data results verify that big data technology improves the accuracy of enterprise capital operation risk prediction and analysis while accelerating the speed of risk discovery.