Operational Risk Management Research Articles

Ground Deformation and Damage Assessment using SAR Observations: A Case Study of Hinatuan, Philippines in the 2023 Surigao Del Sur Earthquake

Abstract. Earthquakes are among the major hazards that lead to economic loss every year. Rapid damage assessment is essential for a more efficient disaster response. The 2023 Surigao del Sur earthquake in the Philippines with moment magnitude (Mw) 7.4 occurred on December 2, 2023, with Hinatuan as the nearest municipality located 12 km south of the epicenter. Thus, this study examined the co-seismic impacts in Hinatuan using Synthetic Aperture Radar (SAR) observations. Using phase interferometry and displacement maps to estimate the ground surface deformation, results show that the phase interferograms, Line-of-sight (LOS) displacements, and vertical displacements were consistent, with most of Hinatuan experiencing an uplift of up to 7.2 cm. In contrast, subsidence as low as –9.0 cm was observed in some isolated areas. The damage assessment conducted through change detection analysis revealed 6.15 ha (6.4%) of built area out of the total 84 ha was significantly damaged. The damage mainly occurred in the uplifted regions between 0 to 5 cm. Building codes, land-use planning, and risk management and assessment can be improved and strengthened with these findings for a more earthquake-resilient community. The findings will be a basis for disaster risk reduction and management actions. These may, furthermore, serve as a reference for the development planning of local government units, especially for urban and built-up areas. These can also be used in developing Information, Education, and Communication (IEC) materials and advisory for residents in Hinatuan and the vulnerable adjacent regions.

Risk Management As A Determinant Of Indonesian Banking Financial Performance: A Systematic Literature Approach

This study aims to understand how risk management affects financial performance in the Indonesian banking sector. In a business environment full of uncertainty, especially in the banking sector, risk management is key to ensuring financial stability. Systematic Literature This review (SLR) analyzes the findings of articles published between 2016 and 2022, focusing on the main risks faced by banks: credit risk, market risk, liquidity risk, and operational risk. The selected articles were obtained from leading journal sources in the fields of economics and business. The literature selection process includes the stages of identification, screening, and thematic analysis to identify trends and correlations between risk management and financial performance indicators such as Return on Assets (ROA) and Return on Equity (ROE). The results of the study indicate that credit risk and operational risk have the most significant impact on financial performance, while market and liquidity risks show varying effects depending on the market situation and internal conditions of the bank. These findings underline the importance of a proactive approach to risk management, including the implementation of integrated risk mitigation policies and the use of effective internal controls. Thus, risk management not only serves as a safeguard against potential losses but also as a support for business sustainability. This study recommends further research to explore new risks such as cyber threats and regulatory changes, which are increasingly relevant in the context of the modern banking industry. These results are expected to provide insights for financial practitioners and banking leaders in improving the resilience and financial performance of their companies.

Risk Management Strategies and Performance of Selected Insurance Companies in Nairobi City County, Kenya

The insurance industry plays a vital role in the management of risk and therefore helps to support and facilitate business activities. The performance of insurance companies is impacted by various challenges related to their risk management strategies. These challenges can arise from both internal and external factors, and they can have significant implications for the financial stability and profitability of insurance companies. Changes in regulatory requirements can impact the risk management strategies of insurance companies, requiring them to adapt their practices and systems to remain compliant. Therefore, this study seeks to investigate the influence of risk management strategies on the performance of selected insurance companies in Nairobi City County, Kenya. The study was guided by the balanced scorecard model, agency theory, portfolio theory, risk aversion theory, and prospect theory. A descriptive research design was employed. The study targeted 95 respondents, comprising 10 senior-level managers, 30 middle-level managers, and 55 departmental heads from the insurance companies operating in Kenya. A census of 95 respondents was conducted. The study used a structured questionnaire. A pilot group of 9 individuals was selected from the target population. Content validity was applied to the study. Cronbach’s Alpha coefficient was computed for all components of the questionnaire, and their assessment was provided. Descriptive analysis was computed using mean, frequencies, and percentages. Regression analysis tested the relationship between the study variables. The regression model assessed the relationship between the independent variables and the dependent variable. The findings were presented using tables and figures. Through regression analysis with a linear model result showed a strong relationship between risk management strategies and performance. The resulting value of regression coefficient at .000 (p<0.05) indicated existence of relationships that were relatively strong. The study thus concluded that performance of insurance companies is dependent on the careful choice or selection of risk management strategies. It is expected the results will benefit various stakeholders, including the government policy makers, Insurance sector players, and academia. Further studies exploring more strategies to manage risks in other entities including other sectors such as the finance sector could be undertaken by scholars.

Handbook of flood risk management and community action: an international perspective

Handbook of flood risk management and community action: an international perspective

Applying FMEA for Operational Risk Management: Lessons from Minestar Implementation at PT. Borneo Indobara

PT Borneo Indobara (BIB) is planning to implement Minestar, an integrated mining management system, in 2025 to enhance operational efficiency and safety. However, the implementation of this system poses several operational risks that require careful management to ensure success. The aim of this research is to develop a comprehensive risk matrix and propose effective mitigation strategies for the Minestar implementation at BIB, using the SNI ISO 31000:2018 risk management framework. The research employs a mixed-method approach, combining qualitative techniques such as semi-structured interviews and focus group discussions (FGD) with quantitative analysis using Failure Mode and Effect Analysis (FMEA). Data was collected from key stakeholders directly involved in the Minestar project to assess the severity, occurrence, and detection of each identified risk, which were then used to develop a risk matrix. The results of the study identified and prioritized several critical operational risks, with a three-dimensional risk matrix providing a clear visualization of their severity, occurrence, and detection levels. This structured approach allows BIB's management to prioritize risks and allocate resources effectively for risk mitigation. The findings of this research contribute to operational risk management in the mining industry, particularly for the implementation of advanced technologies like Minestar. The practical insights provided can serve as a reference for similar projects in the industry, helping organizations to address operational challenges proactively.

The Attitudes of Households for Disaster Risk Management in Fogera, Estie and Ebenat Woredas

The underlining disaster risk management practice translates the combination of knowledge, attitude, and action to maximize the effectiveness of responses against disasters. While knowledge and disaster risk management activities move along simultaneously, attitudes are inherent to individuals posing challenges to easily identify issues and then taking extended time to change. Lack of scientific wisdom on the perception of individuals towards disaster management, and the limited understanding of different factors that influence attitudes, complicates the endeavor in response to the increasingly uncertain future. This study assesses the attitudes of households for disaster risk management in the nine kebeles, the lowest administrative unit in Ethiopia, and 32 villages in Fogera, Ebenat and Estie districts (Woredas, the main administrative unit similar to county). Cross-sectional quantitative method was employed, and attitudinal survey was conducted among 412 households selected through probability simple random sampling. Purposive nonprobability sampling technique was used to identify research kebeles based on disaster prevalence, and to collect supplementary attitudinal data from 64 participants representing academia and local stakeholders. Descriptive statistics and parametric test of variance and covariance have been conducted to determine the attitude levels and to assess major factors influencing households’ attitude for disaster risk management. Results indicated that most of the households (53%) have a fairly positive attitude. Households with negative (27%) and extremely negative (20%) perception are concentrated in rural kebeles that are highly affected by recurrent disasters. Therefore, households in disaster affected areas have negative and unconstructive perception for disaster risk management. This is mainly associated with lack of active community participation and ineffective risk management activities. Households’ attitude is also significantly affected by age (p = 0.0001), and within different age groups (p = 0.001), location by kebeles (p = 0.0237), education levels (p = 0.0016), education status (p = 0.004) and experience in indigenous risk management practices (p = 0.00001). In addition, this study revealed a linear relationship within all the identified factors and households’ attitude levels. Considering the situation in Ethiopia where individual perceptions are deeply rooted, coupled with the results of this study that revealed highly negative attitude among disaster affected households, it is recommended to consolidate efforts and influence attitude through maximizing community participation and enhancing the effectiveness of disaster management.

Strategic Transformation and Sustainability: Unveiling the EFQM Model 2025

The EFQM Model (European Foundation for Quality Management), established in 1991, serves as a framework for organizational excellence, helping achieve sustainable success through an integrated management system. The Model’s evolution is driven by the need to adapt to global trends, threats, and technological innovations such as digital transformation, employee engagement and well-being, remote work, agile performance management, diversity, equity and inclusion (DEI), sustainability, AI (Artificial Intelligence), and big data. The new EFQM Model 2025, presented in Istanbul in June 2024, introduces significant changes, emphasizing sustainability, innovation, and technology. These changes are analyzed based on the logic of three questions: Why, How, and What. Why: There is a necessity for better alignment of organizations with contemporary challenges through flexibility, risk resilience, and innovation capabilities in a dynamic business environment, including alignment with the Unated Nations Sustainable Development Goals (SDGs). How: The Model introduces an integrated approach to performance management and transformation, incorporating advanced technologies such as AI and data analytics. What: Implementing the EFQM Model 2025 enhances organizational adaptability, innovation, and flexibility, improving financial, operational, and strategic outcomes. Better alignment with sustainability goals leads to long-term value and social responsibility. Improved stakeholder engagement methods enhance understanding and satisfaction. The use of advanced technologies supports innovation and operational efficiency, while better strategic and operational performance and risk management ensure greater stability and the ability to anticipate future challenges.

Prediction of aviation safety incident risk level based on ECSDNN

Prediction of aviation safety incident risk level is an important means of active risk management. Considering the high-dimensional complexity and class imbalance of massive aviation safety incident data, a prediction method for aviation safety incident risk level based on integrated cost-sensitive deep neural network (ECSDNN) is proposed. The feature representation of aviation safety incident data is realized by using the method of embedded coding of categorical attributes and splicing of numerical attributes; the cost-sensitive matrix and cost-sensitive loss function are designed by comprehensively considering the misclassification ratio and fixed cost, and the base classifier model based on cost-sensitive deep neural network (CSDNN) is constructed; the hard voting method is used to integrate multiple base classifiers with different parameters and performances to construct the integrated prediction model ECSDNN for aviation safety incident risk level. The experimental results on the Aviation Safety Incident Reporting System (ASRS) dataset show that compared with the optimal prediction ability of the baseline algorithm, the prediction accuracy of the ECSDNN model is improved 4.51%; compared with the single CSDNN base classifier, the prediction accuracy is improved 3.17%.

Registered sex offenders’ experiences of home visits in England & Wales: are the police expected to integrate “risk” with “desistance”

Purpose In England and Wales, adult male registered sex offenders (RSOs) are risk assessed and managed using a tool known as the Active Risk Management System; a risk assessment designed specifically for police management of RSOs and carried out by a specialist group of police officers known as Management of Violent or Sexual Offenders (MOSOVO) at the RSO’s home, known as “the home visit”. The purpose of this paper is to explore RSOs views of the home visit and risk assessment and to make recommendations to MOSOVO to improve future home visit & risk assessment practice. Design/methodology/approach This study aimed to examine a sample of adult male RSOs’ views of the risk assessment and home visit process. Three police forces in England and Wales agreed to facilitate the sampling of 10 RSOs who varied in their level of risk, namely, low, medium, high and very high. Findings Three themes were developed from the analysis: anxiety and shame; perceptions of the first home visit; and the property search and observations. This paper discusses these experiences in light of the growing call for MOSOVOs to both manage risk and assist desistance and present recommendations for improving both the home visit and risk assessment practice. Originality/value To the best of the authors’ knowledge, this is the first study to understand and explore RSOs views of the home visit and risk assessment process.

Evaluation Of Graha Nusantara’s Operational Risk Management Process Using ISO 31000:2018

Graha Nusantara is one of the business units of cooperative x which is engaged in building rental. Since the pandemic in 2020, Graha Nusantara has experienced a decrease in demand for building rentals which has led to a decrease in revenue. In addition, Graha Nusantara has also experienced problems related to its business operations such as canceling events by consumers for various reasons, building maintenance and management, employee management to those related to vendor partners. This causes Graha Nusantara to continue to lose money due to ineffective building operations which can actually be prevented by streamlining Graha Nusantara's operations. This study aims to evaluate operational risk management in the Graha Nusantara business unit, which is a building leasing business, with reference to risk management standards based on ISO 31000. The method used in this research is descriptive qualitative analysis with a case study approach, through interview and documentation data collection techniques. The results showed that risk management has not determined the scope, context and criteria process according to ISO 31000 and nineteen risks with various levels of risk were identified. Therefore, this study recommends handling each risk and it is expected that management establishes a risk management policy, especially operational risk

Risk management and corporate ESG performance: The mediating effect of financial performance

This study utilizes a sample of A-share manufacturing companies listed in China from 2012 to 2022 to explore the intricate interplay between systemic risk, financial performance, and ESG (Environmental, Social, and Governance) performance. The findings reveal that a decrease in systemic risk positively influences corporate ESG performance with a notable lag of 1–2 periods, with financial performance serving as a pivotal mediator in this dynamic. However, within the heavy pollution industry, the enhancement of ESG performance through systemic risk reduction is observed to be comparatively muted.

Modeling and scenario building for climate change adaptation planning: The case of large mining in Chile

The mining sector in Chile is a strategic industrial sector for the country. Existing evidence shows that it faces several serious climate change threats; precipitation and flooding, droughts, heatwaves, among others. This scene put pressure on the government and the industry to develop efficient adaptation plans. To date, adaptation plans are designed under the rather linear paradigm of predict-then-act or the impact-lea approach as they are characterized in the IPCC Assessment Report 5 (AR5). Literature and the IPCC reports have identified the limits of those planning paradigms showing the relevance of adaptation barriers or enabling conditions, which should be considered as intrinsic part of the planning problem.In methodological terms, planning for climate change risks implies an enriched adaptation plan problem, previously characterized only by an operative climate risk management, that must be described at the beginning of the decision-making process. In this study, our objective is to contribute to the climate change adaptation planning of large-scale mining in Chile. The study is based on a climate change adaptation planning approach that overcomes the limitations of the current paradigm. In doing so, we start from the understanding that what emerges as an object of analysis from adding to the climate risks their enabling managing conditions is a social system. The social system whose function is that social climate risk management takes place. Therefore, we call it the Social Management System for Adaptation to Climate Change (SMSACC). As such the SMSACC should be the adaptation planning key object.In the first place we modeled that system applying a qualitative system methodology and then we developed it into a mathematical model based on graph theory, in particular the signed digraphs. This allows us to simulate two types of intervention on the enlarged object of analysis of the large mining adaptation plan. On the one hand, we carried out a future scenario analysis based on prospective tools which enables us to understand the system's answer to different future behavior of its environment, including climate change. On the other hand, we simulate different strategic interventions options on the system, which facilitates understanding the system's reaction under different public policy approaches.The modeling and simulation results provided an insightful understanding of the dilemma of social adaptation management of large mining in Chile, and as such they are useful input for the planning process.

Climate change influence on the trends of BFRs in the environment and food.

Climate change poses new challenges for environmental protection and food safety. With reported consequences including warmer temperatures, melting of Alpine glaciers, higher sea levels, droughts, extreme rainfall events and increased surface UV radiation, concerns about the impact on food contaminants have been raised. While the effects of climate change on POPs were initially expected to have the biggest impact in the arctic region, given the intensity, frequency and spread of extreme weather events, global influence on environmental pollution and food safety is currently anticipated. Warmer temperatures are expected to enhance the volatilization of POPs and influence their partitioning between soil, sediment, water and atmosphere, enhancing their mobility and their potential for long-range atmospheric transport. Floods and strong winds can cause dilution but also spread of pollutants to wider areas. Limited data are available for the impact of climate change on BFRs levels, trends and toxicity. BFRs are widely used to protect people from fire hazards. Numerous BFR containing products are disposed in landfills where climate change could possibly induce increased leaching and resulting impacts on the food chain. Heat and UV exposure can lead to degradation of novel polymeric BFRs with adverse environmental effects. Long-term monitoring data are needed for feed, food and environmental compartments in order to evaluate climate change influence, which will also enable the development of prediction models specific for legacy and novel BFRs, for various climate change scenarios. Furthermore, there is a need to promote further discussion in the scientific community for the design of risk management and remediation activities for contaminated areas, in response to potential future conditions as the climate continues to change.

Analisis Efisiensi Operasional, Manajemen Risiko, dan Pengelolaan Sumber Daya terhadap Keberlanjutan Kinerja Keuangan Perusahaan di Indonesia

This study investigates the effects of Operational Efficiency, Risk Management, and Resource Management on the sustainability of corporate financial performance in Indonesian companies. A quantitative research approach was employed, using data from 170 companies across various industries. The data was analyzed using Structural Equation Modeling-Partial Least Squares (SEM-PLS). The findings reveal that all three variables have a significant positive impact on financial sustainability. Operational Efficiency emerged as the most influential factor, followed by Risk Management and Resource Management. These results highlight the importance of an integrated approach to corporate strategy, focusing on improving operational processes, mitigating risks, and optimizing resource allocation to achieve long-term financial stability. The study offers practical insights for managers and policymakers on how to enhance corporate financial sustainability in Indonesia.

Enhancing Organizational Resilience through Digital Innovation in Manufacturing

This study explores the role of digital innovation in strengthening organizational resilience within the manufacturing sector. By analyzing the integration of advanced technologies such as AI, IoT, and automation, the research investigates how these innovations improve operational flexibility, risk management, and adaptability to disruptions. A qualitative approach, including interviews with industry leaders, is employed to assess the impact. Findings demonstrate that digital innovation significantly enhances resilience, allowing manufacturers to respond efficiently to market volatility and operational challenges. The study concludes with recommendations for strategic implementation of digital tools.

Evaluating the impact of AI and blockchain on credit risk mitigation: A predictive analytic approach using machine learning

In recent years, the integration of artificial intelligence (AI), blockchain technology, and machine learning has transformed credit risk mitigation strategies in the financial industry. This paper explores the practical applications of these technologies in identifying, assessing, and managing credit risk, with a specific focus on predictive analytics and decentralized frameworks. Through a comprehensive literature review and case studies, the research demonstrates how AI-driven algorithms, blockchain's transparent and immutable ledger systems, and machine learning models have enhanced the precision and efficiency of credit risk evaluations. Additionally, the study investigates how these innovations are being adopted by financial institutions to create more accurate credit scoring systems, reduce fraud, and optimize operational risk management. While these technologies hold great promise, challenges such as data privacy, regulatory compliance, and implementation costs remain significant barriers. The paper concludes with recommendations for overcoming these challenges and maximizing the potential of AI, blockchain, and machine learning in credit risk mitigation.

디지털 무역환경에서 우리나라 중소수출기업의 대금결제 위험관리가 결제위험 관리성과에 미치는 영향: 거래 파트너십 구축지향의 조절효과

Purpose: The purpose of this study is to analyze the relationship between payment risk management and the performance of SME exporters in the digital trade environment. Research design, data, and methodology: In total, 1500 questionnaires were distributed, 200 questionnaires were returned, and 191 were utilized after excluding questionnaires with dishonest or inappropriate responses. Empirical analysis to derive the research results was conducted using the Smart PLS ver. 4.1 statistical package for structural equation modeling. Results: First, credit risk management, B2B trade receivables management, and strategic foreign exchange risk management were found to have a significant impact on payment risk management performance. Second, orientation toward building trade partnerships was found to positively moderate the relationship between payment risk management and payment risk management performance. Conclusions: This study provides guidance on the factors that small and medium-sized enterprise exporters should adopt for managing payment risks, and it is expected to contribute to strengthening export competitiveness by providing practical measures.

Analysis of TEF Operational Risk Management for Trains and Underground Stations of MRT Jakarta

Analysis of TEF Operational Risk Management for Trains and Underground Stations of MRT Jakarta

Integrated risk management and maintenance planning in Oil and Gas Supply Chain operations under market uncertainty

The Oil and Gas Supply Chain (OGSC) is a multifaceted network comprising diverse activities and echelons. Instability or interruptions can cause economic fluctuations, impacting industries, markets, and consumers. Maintenance activities, which pause production but extend facilities' life, are recommended during non-peak demand periods to avoid production losses and meet customer demand. To mitigate these effects, decisions on operations planning, maintenance scheduling, and maintenance team assignments should be optimized in a risk management framework. The proposed model adopts a mixed-integer linear programming (MILP) framework and is solved via a sequential approach that incorporates the relax-and-fix (RF) heuristic in order to find a solution that is close to optimal. Subsequently, the solution serves as an initial solution for the CPLEX solver, which employs a branch-and-cut algorithm to attain the exact optimal solution. The practicality of this model has been showcased through its application to the supply chain in Saudi Arabia. The model efficiently schedules maintenance activities evenly and consistently across the OGSC plants over the planning period to reduce lost sales by keeping plants operational during high-demand periods. Furthermore, a sensitivity analysis was conducted to investigate the influence of the decision-maker's risk attitude on the outcomes that were obtained.

Configurational risks and innovation performance of complex product systems development: A fsQCA lens

Complex products and systems (CoPS) development demands effective risk management, which is frequently impeded by a lack of clarity regarding the impact of risks on performance. This study aims to investigate how multiple risks jointly affect innovation performance in CoPS projects. Based on the configurational theory and WSR framework, we use fuzzy set qualitative comparative analysis (fsQCA) with data from 97 CoPS projects and examine the combined effects of risks on innovation performance. We identify two types leading to high innovation performance and four patterns causing low innovation performance. The results verify the asymmetrical causality of the influence of risks on innovation performance in CoPS projects. The findings contribute to broadening the relationship studies of risk and innovation performance by adopting an empirical method in the context of CoPS. Moreover, our study can help managers implement flexible risk management activities within CoPS projects, by addressing several equivalent and distinctive paths.