Risk Management Research Articles

FROM CALENDAR TIME TO BUSINESS TIME: THE CASE OF COMMODITY MARKETS

We address the problem of modeling commodity forward curves, while preserving empirical features observed in commodity markets. By letting a commodity market to “ live” in the tempo of a business rather than calendar clock, we create a model with a rich but realistic set of features, such as stochastic volatility, stochastic rate of mean reversion and various shapes of forward curves such as backwardation and contango. The model, when applied to extensive historical datasets of crude oil and natural gas forward curves, shows a remarkably good fit to the observed futures prices, also in periods of high volatility and negative prices. The model is developed in such a way that it can be used for a wide variety of applications, ranging from exotic derivatives pricing to risk management of commodity portfolios.

CARROT: Simultaneous prediction of anomalies from groups of correlated cryptocurrency trends

Cryptocurrencies are virtual currencies that exploit cryptography to perform secure financial transactions. They gained widespread popularity in recent years due to their decentralized nature, (pseudo-)anonymity, and ability to facilitate cross-border transactions without the need for intermediaries. However, their price on the market exhibits a huge volatility, that makes them prone to market anomalies. Therefore, predicting anomalies in cryptocurrency time series can be considered an important task for financial institutions, traders, and investors, to maximize their profit or minimize losses.In this paper, we propose a novel approach for predicting anomalies in cryptocurrency time series by exploiting temporal correlations among different cryptocurrencies. Our approach, called CARROT, is based on the idea that groups of cryptocurrencies exhibit similar trends, possibly due to common influencing factors. CARROT analyzes the temporal correlation between different cryptocurrencies, and identifies clusters showing similar patterns that can be useful for gaining insights into future anomalies. Subsequently, CARROT exploits multiple (i.e., one for each cluster) multi-target LSTM models to predict anomalies.Our experiments, performed on a dataset of 17 cryptocurrencies, proved that CARROT outperforms single-target LSTM models of up to 20%, as well as other approaches based on neural networks, i.e., MLP and CNN, in terms of macro F1-score. Therefore, the proposed approach can be considered as a promising tool for predicting anomalies in cryptocurrency time series data and can potentially be used to improve risk management and trading strategies in the cryptocurrency market.

Research on Time Management and Risk Management of Small and Medium-Sized Enterprises

This study aims to explore SME time management and risk management in R & D projects. First, we define project time management and project risk management, and introduce commonly used tools and models. Next, the definition of SMEs and the type of R & D projects are explained, and the problems faced in time management and risk management are analyzed. We also explored the relationship between project risk management and time management in SMEs. Finally, analysis and selection methods for SMEs when selecting project time management and risk management tools. The purpose of this study is to provide effective time management and risk management solutions for SMEs.

Effectiveness of Risk Management through Risk Maturity Measurement: A Study at PT Pelabuhan Indonesia

This research aims to evaluate the effectiveness of risk management at Pelindo post-merger and assess its risk management maturity level. Additionally, the study intends to offer relevant recommendations for the company in developing its risk management strategy and implementation. The research adopts a qualitative descriptive approach with a case study strategy, where the researcher analyzes an organization as a unit of analysis in a natural setting without manipulation. Data collection techniques include interviews with representatives from the Group Risk Management, Governance, and Compliance as the corporate-level risk managers. Document analysis includes textbooks, academic and professional journals, theses, articles, and company department reports. Data analysis follows the Miles and Huberman model. The research indicates that the maturity level of risk management at Pelindo post-merger has reached the good practice phase with a score of 2.94. This reflects a consistent application of risk management in accordance with industry standards, although its effectiveness varies. The organizational structure, framework, processes, and risk culture have begun to be implemented. Recommendations for improvement include strengthening the risk culture, enhancing the effectiveness of risk management functions, and aligning risk strategies with the ERM transformation plan for better effectiveness and compliance.

A Bibliometric Analysis of Risk Management in Road Construction Project

Risk management in road projects is a process of controlling construction work and development that significantly affects the success of road project work. This research aims to investigate the latest developments in the world, with a specific focus on those related to risk management in road construction. The study intends to shed light on emerging trends and innovations in the field by exploring global advancements. The primary goal is to contribute valuable insights that can enhance the understanding and implementation of risk management strategies in road construction projects. These publications were obtained by scrutinizing keywords such as road construction, risk management, and construction projects. Utilizing Publish or Perish facilitated the extraction of data relevant to our research topic. Subsequently, the acquired data was transformed into a new format using Microsoft Excel. This dataset encompasses citation counts, author names, and publication years. Leveraging this information and Microsoft Excel, we constructed a chart or figure to present a comparative analysis. Additionally, VOSViewer was employed to create a visual representation illustrating relationships between research keywords.

Interprofessional Management of (Risk of) Malnutrition and Sarcopenia: A Grounded Theory Study from the Perspective of Professionals.

As our global population ages, malnutrition and sarcopenia are increasingly prevalent. Given the multifactorial nature of these conditions, effective management of (risk of) malnutrition and sarcopenia necessitates interprofessional collaboration (IPC). This study aimed to understand primary and social care professionals' barriers, facilitators, preferences, and needs regarding interprofessional management of (risk of) malnutrition and sarcopenia in community-dwelling older adults. We conducted a qualitative, Straussian, grounded theory study. We collected data using online semi-structured focus group interviews. A grounded theory data analysis was performed using open, axial, and selective coding, followed by developing a conceptual model. We conducted five online focus groups with 28 professionals from the primary and social care setting. We identified five selective codes: 1) Information exchange between professionals must be smooth, 2) Regular consultation on the tasks, responsibilities, and extent of IPC is needed; 3) Thorough involvement of older adults in IPC is preferred; 4) Coordination of interprofessional care around the older adult is needed; and 5) IPC must move beyond healthcare systems. Our conceptual model illustrates three interconnected dimensions in interprofessional collaboration: professionals, infrastructure, and older adults. Based on insights from professionals, interprofessional collaboration requires synergy between professionals, infrastructure, and older adults. Professionals need both infrastructure elements and the engagement of older adults for successful interprofessional collaboration.

Key organisational barriers to effective knowledge risk management in South African public sector enterprises

Purpose: The aim of this study was to delve into the obstacles preventing the effective management of tacit knowledge risks in South African public sector enterprises (PSEs) from the perspectives of human resource management (HRM) and knowledge management (KM).A perusal of the literature reveals that most South African PSEs are grappling with significant challenges related to potential tacit knowledge loss risks.Design/methodology/approach: The research utilised a mixed methods exploratory sequential design, collecting qualitative data through interviews with 20 HR managers in 9 PSEs and survey data from 585 questionnaires. The reliability of the data was tested, and thematic analysis was performed using Atlas.ti software.Findings: The study identified key barriers to effective tacit knowledge loss risk management in PSEs, including a silo mentality, organisational red-tape, knowledge as a power source, lack of recognition and rewards, KM awareness, cultures and structures, employment equity, fixed-term contracts, competing priorities for leadership, knowledge hoarding, HRM practices, and inadequate KM technologies and systems. These pressing issues need to be addressed to improve knowledge risk management (KRM) efforts in PSEs.Research limitations/implications:The exploration of organisational barriers was only limited to the tacit knowledge loss risks category, induced by human resource turnover in country-specific PSEs. Future studies could explore the organisational barriers and factors affecting other types of knowledge risks in PSEs or similar knowledge-intensive business enterprises across the globe using different samples and populations. Other similar studies could include strategic sectors of the economy such as energy generation, civil aviation, defence, mining and rail. The study contributes to the knowledge-based view and knowledge stickiness theories, and proposes an interdisciplinarity approach using mixed methods for future research on tacit knowledge loss.Practical implications: The research findings conclusively indicate that PSEs face the aforementioned barriers that hinder the effective implementation of the KRM system. This study identifies that key organisational barriers were mainly due to a lack of knowledge-driven HRM strategies in KM. To address these barriers, HR managers and other stakeholders must collaborate to ensure effective knowledge management and mitigate the negative impact of knowledge loss risks on organisational performance.Social Implications: The study highlights the importance of removing key barriers for improved KRM in PSEs. The improved KRM can enhance public service delivery efficiency, transparency and the accountability of PSEs by addressing socio-economic developmental issues in developing economies.Originality/value: Using South African PSEs as a case to address this challenge, the paper sought to explore key organisational barriers to effective knowledge loss risk management in organisations with a view to shaping discourse, policies, research, theories and practices in KM and HRM. Organisational barriers affecting the management of such risks remain unexplored in the extant body of knowledge and practice.

Dear CRO: Behavioural risk management is the new thing for you

Behavioural risk management (BRM) helps to better prevent risk events that can hurt financial services firms, their customers, shareholders and society. Underpinned by methods and insights from across the behavioural sciences (such as organisational and social psychology, decision making and cognitive science, etc), this forward-looking risk management approach is increasingly encouraged by regulators and invested in by financial institutions globally. This paper provides a practical three-step approach to manage behavioural risk, illustrated with financial services case studies. Future developments are then discussed. The paper closes with common implicit beliefs that may hinder senior risk management professionals initiating BRM in their organisations and a manifesto for action to help get started.

An Integrated Management System (IMS) Approach to Sustainable Construction Development and Management

Construction is aiding to fuel the severe environmental crisis that it is grappling alongside. The sector uses over 3 billion tons of raw materials annually on projects, and 40% of world CO2 emissions derive from its activities. Traditional integrated strategies toward fragmented sustainability cannot offer total optimization. In this respect, the present research presents an integrated management system (IMS) containing a composite of metrics for sustainable construction management (SCM). This research was specifically geared to test the relationship between the elements of IMS and SCM from the perspective of the construction industry. A quantitative survey tested through 119 professionals was used for data collection. It is established through structural equation modeling (SEM) that the internal consistency of Cronbach's Alpha 0.72-0.95 and construct validity was strong. The Fornell-Larcker criterion was realized to affirm good discriminant validity. Crucial results identified the presence of significant impacts for quality management (QM) (β=0.643, p<0.001), risk management (RM) (β=0.53, p<0.001), and safety management (SM) (β=0.439, p<0.001). Therefore, this study further enhances the scalability of IMS so that it is practically applied to improve project quality and safety, along with risk management. Future research could also focus on studying the context of the integration of IMS with SCM and continue to work using objective performance measures to validate these findings.

Developing a healthcare transformational leadership competency framework for disaster resilience and risk management

Climate change-induced hazards increasingly threaten healthcare systems worldwide, amplifying the frequency and severity of disasters and their adverse health effects. This necessitates fortified healthcare leadership and resilient systems capable of delivering quality care amidst escalating environmental challenges and emphasises the need for standardised competency frameworks to enhance disaster readiness and response. As healthcare organisations face evolving challenges, cultivating transformational leadership competencies becomes essential for building adaptive, resilient, and effective disaster management strategies. Purposeof this study: This conceptual paper addresses the research question: "How can healthcare leaders' competencies be developed to support healthcare disaster resilience?". MethodsThe study, conducted in 2023, used a narrative literature review, comparative analysis, and synthesis. It reviewed frameworks on transformational leadership and disaster resilience, employing comparative analysis to examine relationships and leadership competencies. A synthesized framework was developed to clarify dimensions and relationships. ResultsEight ‘domains’ of competencies were identified, in addition to other ‘transferring skills.’ The domains were analysed regarding their component competencies and were broadly classified into knowledge, cognitive and interpersonal skills, and attitudes. This classification is proposed as a ‘Healthcare Transformational Leadership Competency Framework’ (HTLCF) for disaster resilience and risk management. ConclusionThe HTLCF supports leaders in navigating complexities, anticipating risks, and facilitating collaboration, communication, and accountability, leveraging their transformative agency. This study suggests the use of the Healthcare Transformational Leadership Competency Framework to develop a standardised disaster management curriculum and continuous, ongoing training. This would equip leaders to enhance resilience and ensure coordinated, effective disaster responses for healthcare systems.

Research on risk management of ship maintenance projects based on multi agent swarm model simulation method

In recent years, the role of naval ship power has become increasingly prominent in regional conflicts and military operations worldwide, and the powerful capabilities demonstrated by naval forces have also been valued by countries around the world. While naval forces are frequently deployed to carry out various tasks, the intensity of equipment wear and tear on ships is also significantly increasing, posing a huge challenge to the maintenance and support capabilities of ship equipment. In the actual process of ship equipment maintenance, a series of risk factors such as cost, schedule, and quality will have a significant impact on the entire ship maintenance project, and even affect the success or failure of the entire project. This article first decomposes the project process of ship maintenance projects, further analyzes the various risk factors of ship maintenance projects based on the project decomposition situation, and then distinguishes the overall project, project process, and project risk factors to establish an intelligent agent group model for simulation analysis. Through the above simulation analysis, we will conduct in-depth research on the specific impact of project risks on ship maintenance projects, and analyze and verify the positive role and practical significance of project risk management in project risk control and project efficiency improvement. In the process of the above research content, methods and measures for risk management of ship maintenance projects are proposed, providing scientific and efficient risk management suggestions for such projects, improving the scientific management efficiency of ship maintenance projects, and contributing to the improvement of the quality and efficiency of project management.

Model risk management in stress testing: The road up to here

This paper reviews the historical evolution of the quantitative models, model usage and model risk management (MRM) in large US banks since the 1980s. It comments on the most significant model-related events through this period. Some of these events were associated with contexts of great stress to the financial system. The paper identifies the main features of modelling in finance and economics that distinguish it from its application in the natural sciences. Then it presents the different types of models used in the large banks' stress testing programmes, the specific characteristics and risks of each type of model and the best practices for the implementation of sound model risk management, and it suggests a proper way to interpret the results of stress testing and capital assessment in the presence of model risks. The paper discusses the future evolution of MRM towards the implementation of a `fully fledged risk management framework` along the lines of other risk management disciplines, including risk identification, measurement, monitoring, reporting, limiting and capitalisation. It acknowledges the enhancements and opportunities offered by advances in the use of artificial intelligence and machine learning as well as increases in computational power. The paper concludes by noting that the model risk management framework that has been enforced by the Federal Reserve's stress testing and capital planning programmes has substantially strengthened the capital position, profitability and resilience of the large banks in the US.

Risk assessment and management strategies in older patients with acute pulmonary embolism

IntroductionManaging older patients with acute pulmonary embolism (PE) is challenging due to their underrepresentation in clinical trials, comorbidities and increased complication risk. This study evaluates risk assessment and management outcomes in older PE patients focussing on home and reperfusion treatment. MethodsA retrospective analysis was conducted on patients aged ≥70 years diagnosed with acute PE at an academic medical centre (2015-2022). Results242 patients with a mean age of 77 years were included. All 59 patients with negative Hestia criteria were discharged ≤24h, and in total 81 patients (35%) received home treatment. Among these 14-day mortality and recurrent venous-thromboembolism were 0% and major bleeding occurred in 1.3% (one patient, 95%CI 0.11-6.1). European Society of Cardiology (ESC) risk-classification showed 9 low-risk PE (3.9%), 199 intermediate-risk (87%), and 20 high-risk PE patients (8.8). In 5 of the 20 high-risk patients, hypotension was mainly caused by another condition, i.e. sepsis. Eight high-risk patients received reperfusion therapy. Fourteen-day mortality was 51% in high-risk patients (95%CI 27-71); 5 out of 8 patients receiving reperfusion treatment died within 5 days. Patients with an Acute Presenting Older Patient (APOP) score of ≥45% had higher 14-day mortality (28%; 95%CI 12-46) compared to <45% (3.2%; 95%CI 0.85-8.3; HR 10.2; 95%CI 2.6-39). ConclusionSelecting for home treatment using Hestia was safe for older PE patients in our cohort. Mortality in the high-risk group was high also when receiving reperfusion treatment. The ESC risk-classification and APOP score identified patients at higher mortality risk, suggesting their potential utility in clinical decision-making.

Crisis preparedness exercise on food and feed safety for IPA beneficiaries 2024.

The European Food Safety Authority (EFSA) within the framework of the Preparatory measures for the participation of IPA beneficiaries in the European Food Safety Authority 2023-2026 will organize a total of 3 crisis preparedness training events for the IPA countries (Albania, Bosnia and Herzegovina, Kosovo,* Montenegro, North Macedonia, Serbia, Türkiye). For 2024, EFSA requested to organise a simulation exercise focused on a multi-country incident related to biological risks in products of animal origin. The overall objectives of the training were: 1) to increase IPA countries' knowledge and understanding of crisis handling concepts and of EFSA's crisis handling procedures; 2) to improve preparedness and response planning for crisis situations in the domain of biological hazards; 3) to improve coherence, interoperability and coordination, to be prepared for communication and decision-making challenges in crisis situations. Working with the contractor Opera srl, EFSA organised a 2-day training on 26-27 June 2024 in Sarajevo (Bosnia and Herzegovina), attended by 24 participants (3 online) from 7 IPA countries, 2 representatives from EFSA and 1 representative from the hosting competent authority from Bosnia and Herzegovina. Participants were briefed on the IPA crisis preparedness training scheme, EFSA's crisis handling procedures, principles of crisis communication (remote mode), EFSA - ECDC Rapid Outbreak Assessment (remote mode), food safety risk assessment structures in Bosnia and Herzegovina and Serbia. Most of the workshop was dedicated to the simulation exercise, that was organized in a tabletop format, with injects describing an evolving food safety incident and a debriefing after each inject. During the exercise, 1 audio-conference meeting and a TV debate were simulated. The exercise was concluded with a brainstorming session between the tutors and participants. Three recommendations were done to improve the organization of future events. Six recommendations were given for the improvement of risk assessment, risk management and risk communication in IPA countries. The objectives were achieved, based on the results of the knowledge test and on the feedback provided by participants in the course evaluation questionnaire.

Leveraging AI and Machine Learning to Optimize SAP-Driven Financial Operations: A New Paradigm in Risk Management and Fraud Detection

As the global business landscape continues to evolve, organizations are increasingly relying on advanced technologies to enhance their financial operations. The integration of Artificial Intelligence (AI) and Machine Learning (ML) with SAP-driven financial systems represents a transformative shift in how companies manage risk and detect fraud. This article explores how AI and ML can optimize SAP systems for proactive risk management and real-time fraud detection. It highlights the benefits, challenges, and best practices for implementing these technologies within SAP environments, drawing on industry case studies and expert insights

Stock Volatility Modelling With Augmented Garch Model For Voltas Ltd

This research paper seeks to examine the efficiency of the augmented GARCH models in estimating the stock volatility. GARCH models that were introduced by Bollerslev (1986) became popular for the modelling of time varying volatility in the financial markets. However, due to the specificity of financial markets and variation of factors that define it, extra parameters may be required to improve the model. To investigate further, the study uses an extended GARCH model that integrates other features including leverage effects, exogenous variables and non-linearities. These components seek to establish features giving clearer volatility patterns of stock markets. In this paper, empirical comparison of the extended GARCH model with the basic forms of the models is done. The outcomes are expected to be of interest to financial investors, advisors and risk managers

Assessing the Holistic Value of Danhong Injection for Chronic Stable Angina: A Multi-Criteria Decision Analysis in China

IntroductionThis study aimed to assess the holistic value of Danhong injection (DHI) for treating chronic stable angina (CSA) and to identify the therapeutic characteristics of DHI. MethodThe holistic value of DHI was assessed using a well-established evaluation index system including 34 criteria for the post-marketing assessment of the value of Chinese patent medicine (CPM) based on the Multi-criteria decision analysis (MCDA) model. Each criterion was rated by seven experts based on an evidence matrix comprising a literature review on DHI for treating CSA. The overall value of DHI for the treatment of CSA was evaluated by aggregating these performance scores and predetermined weights. Additionally, the contributions of each domain and criterion to the overall value estimate were calculated. Uncertainty was explored using an online retest and intrarater correlation coefficient. ResultsWe found that the comprehensive value estimate of DHI for treating CSA was 80.18 points. The domain of “safety and risk management” was the strongest contributor to the final estimated value (30.37), followed by “effectiveness” (23.75). The criteria “size of population affected by disease” (3.79), “risk control of toxic medicinal materials” (4.38), “comparative non-medical costs” (1.14), “clarity of the mechanism of drug action” (0.6), “sustainability of medicinal materials resources” (1.91) and “patient compliance” (4.59) were found to be the most significant contributors to the overall value estimate across the 6 evaluation domains. The initial scores for DHI over the two rounds showed good consistency across panelists (ICC=0.886 (0.858-0.909)). ConclusionCompared with standard treatment alone, DHI was perceived as being at a “good level” intervention.

Blockchain Technology in Risk Management: Strengthening Cybersecurity and Financial Integrity

Blockchain Technology in Risk Management: Strengthening Cybersecurity and Financial Integrity

Solidarity is not a dirty word: exploring and locating solidarity as a theory and model for a radical community social work practice

Within this article we highlight that social work is both a political as well as a professional practice. Despite years of technical specialisation and a policy context that has focused social work on risk management and resource allocation, there remains a deep commitment to care, compassion, and solidarity within contemporary social work practice. The article and its analysis make the case for a more politically informed social work practice, one that is based on solidarity; in opposition to a system that isolates individuals and internalises complex social problems. We posit that the application of solidarity within social work delivers a practice that promotes social inclusion and is based on the provision of practical social support. It is from this perspective that we will present evidence from ethnographic research, drawn from community social work practice, to highlight the importance of social solidarity and provide an insight into different ways of working.

Operational resilience implementation: Challenges and opportunities for UK building societies

Operational resilience is the preparedness and existence of resilient IT systems, processes and resources to provide services continuously during a disruption. This study examines the operational resilience implementation challenges and opportunities for UK building societies and wider financial institutions. The key challenges are resource constraints, understanding regulatory requirements, supplier concerns, domain knowledge, legacy systems and manual-driven processes. Some challenges are being addressed with awareness and training, improved governance and risk management, recruitment and industry support networks. The opportunities include realising the actual state of IT systems, adopting cloud solutions, resources and capabilities, as well as improved domain knowledge and a better understanding of services and markets. Regulators need to be more explicit about their expectations and requirements, while the industry needs to collaborate on setting up common frames of reference for operational resilience frameworks. Lastly, the study provides a holistic view of operational resilience, including its implementation and management challenges, control measures and emerging opportunities.