Risk management in translation

As risk analysis and risk management get increasingly caught up in political debates, a new way of looking at and defining the risks of modern technologies becomes necessary

New Risks: Issues and Management

This article is the first of two written to focus attention on risk and behavior management in therapeutic schools as an ongoing process with key components and steps. The professional literature for public schools contains a large number of articles addressing risk and behavior management, but most possess limited application to therapeutic schools. These papers attempt to bridge this gap by outlining the characteristics of therapeutic schools and comparing risk management principles with other types of therapeutic programs. Demographics of the population served by therapeutic schools are described. The importance of experiential education in the therapeutic school is explored along with the role of risk and challenge in the learning process. Risk management and other useful terms are defined. An integrated risk management model is presented discussing risk assessment and analysis. Examples from the Mission Mountain School’s approach to integrated risk and behavior management is presented as an illustration of how the principles identified in the literature can be used to create an applied model of integrated risk and behavior management. Citations are referenced both as a resource and to stimulate thought and discussion. This paper is directed toward school administrators, clinical directors, and program directors seeking to understand the important concepts and theory of risk management. The integrated risk management model and concepts introduced in this paper may also help the referring professional or parents to better evaluate an individual program’s risk management approach and its suitability for different student profiles.

Many previously conducted empirical studies have displayed mixed findings about the influence of internal factors within an organization on the management of risk among construction companies. Hence, there is a need for introducing a moderating variable to this field of study. The aim of this research was to confirm whether coercive pressure plays a significant role in the relationship between the management of risk in construction and factors within the organization. Therefore, this study examined the influence that internal organizational factors and coercive pressure have on the management of construction risk through the lens of discouragement and organizational control theory, and institutional theory. Data were collected through the distribution of questionnaires involving 165 workers working in the Malaysian Peninsular construction companies, and the analysis was performed by means of partial least squares structural equation modelling. Results revealed a positively significant connection between internal organizational factors and the management of construction risk. Also, coercive pressure and the management of construction risk has a positively significant relationship. Coercive pressure mediated the connection that organizational internal factors had with the management of construction risk. A discussion of the research implications was done from the point of view of Malaysia. In conclusion, the reduction of risk incidents in the process of carrying out construction activities is being facilitated by active leadership and organizational culture. In addition, the rate and period at which accidents occur during and after the completion of construction activities are reduced by coercive pressure. In the same way, some influential internal factors of organizations as well as the introduced coercive pressure in the process of managing construction risk have established that many construction companies that apply the necessary internal factors as well as the coercive pressure introduced by the government are able to make delivery of their construction task at the specified cost, time, and qualities, thus establishing them as the correct standard for measuring a well-constructed project.

Ownership Structure across Lines of Property-Casualty Insurance

PurposeThe purpose of this paper is first to determine the competencies required of risk managers and second to consider the implications of such competencies in determining modules for inclusion in the curriculum framework of an undergraduate qualification in risk management.Design/methodology/approachA qualitative research approach was followed, involving risk management professionals in a focus group and making use of interactive qualitative analysis (IQA).FindingsThe competencies identified are managerial and risk management knowledge, attributes such as assertiveness and steadfastness and ethical values, as well as people and technical skills. These are explained in greater detail in this paper.Research limitations/implicationsThe unique contribution of the current research was the innovative use of IQA for data collection, the removal of subjectivity and the rigour in analysing and presenting the results. The results provide a starting point for designing a curriculum that will both meet the requirements of the professional body and will equip graduates with the best possible combination of knowledge, attributes, values and skills needed by the risk management profession. The implications for further research include that a comparative IQA study of the competencies of risk managers using academics from the field could be undertaken, as well as a study of the design, benchmarking and validation of a proposed curriculum for an undergraduate degree in risk management. The purpose of this study was not to compile a curriculum for a new BCom (risk management). However, this was beyond the scope of the current study. IQA uses rigour and eliminates the bias of the researcher, and the one limitation of this research lies in the use of a focus group, which resulted in the findings not being generalizable as the case would have been with a representative sample used in the positivist paradigm and using appropriate statistical analysis. However, this study was exploratory and could serve as a valuable starting point for further research in this area to perform a comprehensive curriculum development.Practical implicationsThis study found that constituents of the focus group perceived that the following competencies are required of risk managers, namely, knowledge, skills, attributes and values. These competencies correspond closely with the competencies indicated in the Risk and Insurance Management Society (RIMS) Professional Core Competency Model, except that RIMS subdivides knowledge into three categories, namely, business, organisational and risk management knowledge. Similarly, RIMS distinguishes between management skills and technical skills. The attributes identified by the focus group of this study were similar to those identified by RIMS. However, the focus group emphasised values such as integrity, ethical conduct, respect and accountability. However, unlike RIMS, these were not perceived as one of the five core competencies, but rather as a stand-alone competency in its own right, which risk managers need to be successful. RIMS could consider reviewing its core competencies by allocating three closely related aspects, namely communication, collaboration and consultation to technical skills. Core competencies may be replaced by core values, which are literally at the centre of all the competencies required. Such core values are enhanced by the RIMS Code of Ethics (2019) and significantly contribute to the professionalization of risk management. RIMS could also consider providing guidelines to universities for those competencies that could be taught or learnt, to be included in their curricula and to accredit universities who meet such requirements.Social implicationsThe findings of this study also serve as a starting point for the reintroduction of a BCom (risk management) degree by Unisa. Despite the requirements of the South African Qualifications Authority (SAQA) and the Council for Higher Education (CHE), this study demonstrated that a specialised degree in risk management needs to be offered to meet the need expressed by IRMSA for professional risk managers in Southern Africa, and such a degree should ideally be curriculated based on the competencies identified in this article. The implication for public policy is that SAQA and the CHE need to reconsider their rigid stance about the composition of specialised qualifications, and rather set a range of 33-50% for subjects from the field of specialisation that must be included in the curricula of specialised degrees. As indicated by this research, a combination of subjects from different disciplines is required to enhance the competencies and employability of risk management graduates.Originality/valueThe use of IQA is a novel way of ensuring rigour and objectivity in arriving at the required knowledge, attributes, values and skills of risk managers, and aids in the compilation of a new curriculum for an undergraduate qualification in risk management, thus ensuring the qualification will provide a competency-based qualification that will meet the needs of the profession.

Our concept of nine risk evaluation criteria, six risk classes, a decision tree, and three management categories was developed to improve the effectiveness, efficiency, and political feasibility of risk management procedures. The main task of risk evaluation and management is to develop adequate tools for dealing with the problems of complexity, uncertainty. and ambiguity. Based on the characteristics of different risk types and these three major problems, we distinguished three types of management--risk-based, precaution-based, and discourse-based strategies. The risk-based strategy--is the common solution to risk problems. Once the probabilities and their corresponding damage potentials are calculated, risk managers are required to set priorities according to the severity of the risk, which may be operationalized as a linear combination of damage and probability or as a weighted combination thereof. Within our new risk classification, the two central components have been augmented with other physical and social criteria that still demand risk-based strategies as long as uncertainty is low and ambiguity absent. Risk-based strategies are best solutions to problems of complexity and some components of uncertainty, for example, variation among individuals. If the two most important risk criteria, probability of occurrence and extent of damage, are relatively well known and little uncertainty is left, the traditional risk-based approach seems reasonable. If uncertainty plays a large role, in particular, indeterminacy or lack of knowledge, the risk-based approach becomes counterproductive. Judging the relative severity of risks on the basis of uncertain parameters does not make much sense. Under these circumstances, management strategies belonging to the precautionary management style are required. The precautionary approach has been the basis for much of the European environmental and health protection legislation and regulation. Our own approach to risk management has been guided by the proposition that any conceptualization of the precautionary principle should be (1) in line with established methods of scientific risk assessments, (2) consistent and discriminatory (avoiding arbitrary results) when it comes to prioritization, and (3) at the same time, specific with respect to precautionary measures, such as ALARA or BACT, or the strategy of containing risks in time and space. This suggestion does, however, entail a major problem: looking only to the uncertainties does not provide risk managers with a clue about where to set priorities for risk reduction. Risks vary in their degree of remaining uncertainties. How can one judge the severity of a situation when the potential damage and its probability are unknown or contested? In this dilemma, we advise risk managers to use additional criteria of hazardousness, such as "ubiquity versibility," and "pervasiveness over time," as proxies for judging severity. Our approach also distinguishes clearly between uncertainty and ambiguity. Uncertainty refers to a situation of being unclear about factual statements; ambiguity to a situation of contested views about the desirability or severity of a given hazard. Uncertainty can be resolved in principle by more cognitive advances (with the exception of indeterminacy). ambiguity only by discourse. Discursive procedures include legal deliberations as well as novel participatory approaches. In addition, discursive methods of planning and conflict resolution can be used. If ambiguities are associated with a risk problem, it is not enough to demonstrate that risk regulators are open to public concerns and address the issues that many people wish them to take care ot The process of risk evaluation itself needs to be open to public input and new forms of deliberation. We have recommended a tested set of deliberative processes that are, at least in principle, capable of resolving ambiguities in risk debates (for a review, see Renn, Webler, & Wiedemaun. 1995). Deliberative processes are needed, however, for ail three types of management. Risk-based management relies on epistemiological, uncertainty-based management on reflective, and discourse-based management on participatory discourse forms. These three types of discourse could be labeled as an analytic-deliberative procedure for risk evaluation and management. We see the advantage of a deliberative style of regulation and management in a dynamic balance between procedure and outcome. Procedure should not have priority over the outcome; outcome should not have priority over the procedure. An intelligent combination of both can elaborate the required prerequisites of democratic deliberation and its substantial outcomes to enhance the legitimacy of political decisions (Guttman & Thompson, 1996; Bohman, 1997. 1998).

Background This study examines the impact of integrating risk management (RM) into corporate social responsibility (CSR) practices within Moroccan companies certified with the CGEM CSR label. Although previous research has established a theoretical link between RM and CSR, there remains a lack of empirical evidence regarding how RM integration affects organizational resilience and social efficiency, particularly in emerging economies. Methods A quantitative empirical approach was employed, using a structured questionnaire administered to employees from a diverse range of Moroccan companies holding the CGEM CSR label. The survey gathered data on the extent of RM integration and its perceived effects on CSR outcomes. Statistical analyses, including regression and correlation tests, were conducted to assess the relationships among RM practices, organizational resilience, and social efficiency. Results The findings reveal that integrating RM into CSR initiatives significantly enhances both organizational resilience and social effectiveness. Companies that systematically incorporate RM into their CSR strategies demonstrate greater adaptability to external shocks and improved stakeholder satisfaction. These results highlight the importance of including a "Risk and Opportunity Management in Social Responsibility" chapter, as previously proposed for ISO 26000. Conclusions Embedding RM within CSR frameworks positively reinforces the effectiveness of CSR in Moroccan companies certified by the CGEM. The results suggest that the formal integration of a risk and opportunity management component into international CSR standards, such as ISO 26000, would address an existing methodological gap and further strengthen the credibility and impact of corporate social commitments. Future research could expand this analysis to other contexts and investigate the long-term benefits of such integration for organizational sustainability.

This study aims to explore the integration of innovative quantitative models, behavioral finance insights, and advanced analytics techniques in contemporary risk management practices to bolster organizations' resilience and informed decision-making within dynamic financial landscapes. Through a systematic literature review spanning disciplines such as finance, psychology, and technology, this research synthesizes diverse insights to comprehensively understand the evolving nature of risk management strategies. The findings elucidate that incorporating advanced quantitative models like Value at Risk (VaR) and Conditional Value at Risk (CVaR) empowers organizations to meticulously assess and quantify financial risks, thereby enhancing risk management accuracy and granularity. Furthermore, the assimilation of behavioral finance insights illuminates the psychological determinants shaping risk perception and decision-making behaviors, leading to the development of more robust risk management frameworks that accommodate both rational and irrational factors. Moreover, leveraging advanced analytics techniques, notably natural language processing (NLP) algorithms, enables proactive risk management by analyzing textual data and market sentiments with heightened precision. This study underscores the imperative of perpetual innovation and adaptability in risk management practices to adeptly navigate the intricacies of modern financial landscapes. By harnessing emerging technologies, behavioral insights, and interdisciplinary methodologies, organizations can fortify their risk management capabilities, mitigate threats, and seize opportunities in today's globally interconnected economy. Addressing the challenges associated with implementing innovative risk management practices necessitates proactive leadership, resource allocation, and organizational culture transformation. Ultimately, this research contributes to advancing the understanding and application of innovative risk measurement and management approaches, fostering sustainable growth and success for organizations.

Since the early eighties volatility of GDP and inflation has been declining steadily in many countries. Financial innovation has been identified as one of the key factors driving this ‘Great Moderation’. Financial innovation was considered to have improved significantly the allocation and sharing of financial risks, both from a macro and micro perspective. In particular, the prevailing opinion was that great progress has been made in developing models and other quantitative methods for measuring and managing risk. However, the global financial crisis that started in the summer of 2007 revealed important failures in risk management by financial institutions. Over-optimism prevailed and risks were underpriced, caused by problems of both a conceptual and technical nature. This paper analyses these two angles from the viewpoint of financial institutions. Conceptually, we will show that risk management degenerated into a ‘pseudo’ quantitative science. This in turn gave a false sense of security to financial institutions and their supervisors. Prior to the crisis, supervisory and regulatory regimes assumed that for the financial sector as a whole, risk management had been improved and that, as a result, financial stability was enhanced. The fact that many financial activities were carried out in a rapidly changing landscape – i.e. key decisions had to be taken in situations with uncertainty - was largely ignored. At a very fundamental level it was mistakenly assumed that all uncertainty can be measured in a reliable fashion using a probability distribution – i.e. all uncertainty can be treated as ‘risk’. This attitude had also adverse consequences for the way risk management and decision making were organised in financial institutions. There was too much focus on quantitative models and measurement and too little on the qualitative dimension of risk management, involving such issues as information flows, people and their motives and incentives. In addition, even from a narrow, technical perspective risk management techniques proved to be insufficiently sophisticated. The second part of the paper focuses on the lessons to be learned from the past episode of inadequate risk management at the level of financial institutions. Apart from technical improvements there is a need for a greater emphasis on handling fundamental uncertainty. More specifically, it will be shown that qualitative risk management is particularly important to deal with the latter uncertainty. However, even with better risk management the future remains uncertain and human nature will remain largely unchanged. Finding better ways of dealing with fundamental uncertainty remains therefore a continuous challenge.

Project risk management provides a guideline for decision making in new product development (NPD) projects, reducing uncertainty and increasing success rate. However, the acceptance of formal risk management applications in industry, especially for NPD projects is still in question. A study of a food conglomerate in Thailand found that only 9% of NPD projects used a systematic approach for managing risk. 61% of the projects realised the importance of risk management, while the remaining 30% did not involve risk management at all. This study aims to develop a risk management model for NPD projects in the food industry. The first section of this paper reviews the literature on risk management theory, including international standards for risk and project management (ISO31000 and ISO21500), publications for the Project Management Body of Knowledge (PMBOK), by a professional organisation the Project Management Institute (PMI), and also academic research. 182 academic papers, published between January 2002 and August 2012 were selected. The second part interviews conducted with eight NPD experts from five of the major food manufacturers in Thailand to examine their risk management practices and problems. Conclusions are made on five topics : classification of research method, project type and industrial segment, distribution of articles by region, tools & techniques for risk management and risk factors in projects. Specific requirements of risk management for NPD projects in the food industry are identified. A risk management model and the concept of risk management applications for the food industry are proposed.

Risk management in translation service companies is an effective, integrative, proactive way to handle risk. Such companies must integrate defined long-term risk management into their strategies, decision-making, and daily processes; top-management must fully support the risk management system; risk factors, management benefits, and processes require articulation amongst employees; job roles, responsibilities, performance evaluation, and motivation systems must incorporate risk management practices. Risk management in project-based companies might also account for changing clients’ requirements, tight deadlines and budgets, different participants, and high IT use. However, this requires identifying the critical success factors. The research method builds upon the analysis and systemization of the scientific literature – from risk management, emphasizing the underlying strategic approach and effective management, to deriving the focal-points of effective risk management of translation projects. This work unifies the gathered knowledge and results in a conceptual model that integrates the specific assessment criteria for project risk management in translation companies – process definiteness and versatility, responsibility definiteness, top-management involvement, and risk management communication. The operationalisation of the model may lead to the companies’ critical success performance. To the best of our knowledge, this work is one of the first contributions addressing risk management assessment criteria in this industry.

Foreword. Preface. Introduction. Notes on Contributors. List of Acronyms. PART I INTRODUCTION TO OPERATIONAL RISK MANAGEMENT. 1 Risk management: a general view (Ron S. Kenett, Richard Pike and Yossi Raanan). 1.1 Introduction. 1.2 Definitions of risk. 1.3 Impact of risk. 1.4 Types of risk. 1.5 Enterprise risk management. 1.6 State of the art in enterprise risk management. 1.7 Summary. References. 2 Operational risk management: an overview (Yossi Raanan, Ron S. Kenett and Richard Pike). 2.1 Introduction. 2.2 Definitions of operational risk management. 2.3 Operational risk management techniques. 2.4 Operational risk statistical models. 2.5 Operational risk measurement techniques. 2.6 Summary. References. PART II DATA FOR OPERATIONAL RISK MANAGEMENT AND ITS HANDLING. 3 Ontology-based modelling and reasoning in operational risks (Christian Leibold, Hans-Ulrich Krieger and Marcus Spies). 3.1 Introduction. 3.2 Generic and axiomatic ontologies. 3.3 Domain-independent ontologies. 3.4 Standard reference ontologies. 3.5 Operational risk management. 3.6 Summary. References. 4 Semantic analysis of textual input (Horacio Saggion, Thierry Declerck and Kalina Bontcheva). 4.1 Introduction. 4.2 Information extraction. 4.3 The general architecture for text engineering. 4.4 Text analysis components. 4.5 Ontology support. 4.6 Ontology-based information extraction. 4.7 Evaluation. 4.8 Summary. References. 5 A case study of ETL for operational risks (Valerio Grossi and Andrea Romei). 5.1 Introduction. 5.2 ETL (Extract, Transform and Load). 5.3 Case study specification. 5.4 The ETL-based solution. 5.5 Summary. References. 6 Risk-based testing of web services (Xiaoying Bai and Ron S. Kenett). 6.1 Introduction. 6.2 Background. 6.3 Problem statement. 6.4 Risk assessment. 6.5 Risk-based adaptive group testing. 6.6 Evaluation. 6.7 Summary. References. PART III OPERATIONAL RISK ANALYTICS. 7 Scoring models for operational risks (Paolo Giudici). 7.1 Background. 7.2 Actuarial methods. 7.3 Scorecard models. 7.4 Integrated scorecard models. 7.5 Summary. References. 8 Bayesian merging and calibration for operational risks (Silvia Figini). 8.1 Introduction. 8.2 Methodological proposal. 8.3 Application. 8.4 Summary. References. 9 Measures of association applied to operational risks (Ron S. Kenett and Silvia Salini). 9.1 Introduction. 9.2 The arules R script library. 9.3 Some examples. 9.4 Summary. References. PART IV OPERATIONAL RISK APPLICATIONS AND INTEGRATION WITH OTHER DISCIPLINES. 10 Operational risk management beyond AMA: new ways to quantify non-recorded losses (Giorgio Aprile, Antonio Pippi and Stefano Visinoni). 10.1 Introduction. 10.2 Non-recorded losses in a banking context. 10.3 Methodology. 10.4 Performing the analysis: a case study. 10.5 Summary. References. 11 Combining operational risks in financial risk assessment scores (Michael Munsch, Silvia Rohe and Monika Jungemann-Dorner). 11.1 Interrelations between financial risk management and operational risk management. 11.2 Financial rating systems and scoring systems. 11.3 Data management for rating and scoring. 11.4 Use case: business retail ratings for assessment of probabilities of default. 11.5 Use case: quantitative financial ratings and prediction of fraud. 11.6 Use case: money laundering and identification of the beneficial owner. 11.7 Summary. References. 12 Intelligent regulatory compliance (Marcus Spies, Rolf Gubser and Markus Schacher). 12.1 Introduction to standards and specifications for business governance. 12.2 Specifications for implementing a framework for business governance. 12.3 Operational risk from a BMM/SBVR perspective. 12.4 Intelligent regulatory compliance based on BMM and SBVR. 12.5 Generalization: capturing essential concepts of operational risk in UML and BMM. 12.6 Summary. References. 13 Democratisation of enterprise risk management (Paolo Lombardi, Salvatore Piscuoglio, Ron S. Kenett, Yossi Raanan and Markus Lankinen). 13.1 Democratisation of advanced risk management services. 13.2 Semantic-based technologies and enterprise-wide risk management. 13.3 An enterprise-wide risk management vision. 13.4 Integrated risk self-assessment: a service to attract customers. 13.5 A real-life example in the telecommunications industry. 13.6 Summary. References. 14 Operational risks, quality, accidents and incidents (Ron S. Kenett and Yossi Raanan). 14.1 The convergence of risk and quality management. 14.2 Risks and the Taleb quadrants. 14.3 The quality ladder. 14.4 Risks, accidents and incidents. 14.5 Operational risks in the oil and gas industry. 14.6 Operational risks: data management, modelling and decision making. 14.7 Summary. References. Index.

Managing the Risks in Information Systems and Technology

Breast cancer risk assessment continues to evolve as emerging knowledge of breast cancer risk drivers and modifiers enables better identification of high-risk women who may benefit from increased screening or targeted risk-reduction protocols. The ongoing development of breast cancer Risk Assessment and Management Programs (RAMPs) presents an opportunity to decrease breast cancer disease incidence with evidence-based interventions. The goal of this review was to provide a practical guide for providers seeking to establish or update a breast cancer risk assessment and management program. We outline genetic/familial, personal, reproductive, and lifestyle-related factors while discussing the incorporation of risk modeling for precise risk estimate personalization. We further describe the process for determining a risk management plan: information gathering, generation of a risk profile, and articulation and implementation of risk reduction. We also include an overview of clinical workflows in breast cancer management programs and underlines the logistics of establishing a program as well as general principles for guiding the formulation of an individualized risk management plan. We discuss practical considerations, such as clinic structure and operation, allocation of resources, and patient education. Other critical aspects of program design, including identification of the target population, delineation of the core components of the clinical experience, definition of provider roles, description of referral mechanisms, and the launching of a marketing plan are also addressed. The process of risk assessment is both anxiety-provoking and empowering for women at increased risk. New knowledge has enabled strategies to both understand the risk and control it through evidence-based risk management. These benefits can now be realized by an increasing number of unaffected, high-risk patients collaborating with risk management practitioners. Continuation of these efforts will lead to further progress in both risk stratification and risk management of women at elevated breast cancer risk in the near future.