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The paper aims to explore a risk‐finance context in which less information may be preferable to more information.

Insurance companies collect a variety of information on potential policyholders to support two fundamental components of risk classification: underwriting (the determination of whether or not to offer an insurance contract to a particular individual or firm) and rating (the calculation of a policyholder's premium level once a contract has been offered). Although risk classification is necessary in voluntary markets to ensure that most individuals or firms will be able to purchase insurance, it is not necessary when the purchase of insurance is required by government. The paper explores the usefulness of risk‐classification‐related information in the context of government‐mandated insurance.

In the case of government‐mandated insurance, it is shown that risk classification may be more or less useful, depending upon the degree to which policyholders are able to obtain substantial premium reductions for risk control efforts. When such reductions are not available, then risk classification is not only “less useful,” but in fact particularly unjust to certain policyholders.

The paper describes an insurance context in which less information is preferable to more information.

The purpose of this paper is to develop a supplier risk framework. The framework provides the information about the risk level in which a supplier is classified. This study is part of the company’s one- department-one-improvement policy. This policy encourages all departments to look for way to improve process management. For this study, the Purchasing Department attempts to extend its supplier management practices by integrating the risk consideration.

This work is considered as a case study. The study integrates the benchmarking and classification concepts for this extension. The involvement from the company’s purchasing department is critical. There are several steps that have been undertaken. Included are the selection of the supplies to be considered (i.e. packaging), the analysis of the formal complaints by the ratio-format indicator, the four criteria used for the classification, the risk level identification, and the next steps for improving supplier management. The results are verified by the use of cluster analysis. The data are from departmental staffs and manager.

Based on the results, with the four agreed criteria (e.g. regional location, ownership type, joint venture, and registered capital and size), there are altogether four risk levels which are high, medium, low, and minimal.. For the packaging materials, most suppliers belong to the low and minimal risk levels (or 19 out of 27 suppliers). Future activities are then developed and added into the company’s ISO 9001: 2008 manual.

The suppliers’ risk levels with corresponding future actions represent positive contributions to the purchasing department. Integrating supplier risk is based on the applications of benchmarking (i.e. the use of the ratio-format indicators) and classification (i.e. the need to understand the nature of the risk level) frameworks. Future actions to mitigate the risk are also proposed and incorporated into the purchasing department’s procedure.

The project underlines the roles and importance of benchmarking in strengthening the supplier management processes. It also highlights the practicality and benefits of benchmarking when linking with the classification concept for addressing today business problems.

This paper aims to reviews Sukuk risk classification schemes based on extending and adapting the risk classification schemes of conventional finance. It is then argued that risk classification schemes based on Sukuk structure provide significant insights into Sukuk risk not obtainable from conventional schemes. This is because Sukuk structure risk classification schemes link Sukuk risk more directly to the fundamental causal factors creating those risks. These links are less evident in conventional risk classification schemes. It is hypothesised that Sukuk structure risk factors will prove to be highly significant in multifactor expected return regressions.

The paper argues that, given the paucity of the empirical data currently available to researchers in Islamic finance, greater care needs to be taken in hypothesis development than is necessary for conventional finance. The limited data available should be used for testing hypotheses and not “wasted” in hypothesis formation. Through a meta-analysis of the existing literature on Sukuk risk, it is hypothesised that Sukuk structure risks will be highly significant in explaining Sukuk returns and returns volatilities in empirical tests.

The main Sukuk structures, debt based, equity based, assets based, agency based and hybrid structures, arise directly from the requirement of Sukuk to conform to the Shariah and to the fundamental ethical principles of Islamic finance and business. Further, Sukuk risk profiles are directly related to Sukuk structures. Thus, Sukuk structure risks are essentially Shariah risks. The paper presents a Sukuk risk classification matrix based on an evaluation of Sukuk structure risks.

The findings on the relation of Sukuk risks to Sukuk structures require corroboration by rigorous empirical tests.

The paper contributes to work on the creation of evidence-based risk management techniques in Islamic finance and to the expansion of ethical financial management.

The paper is one of the early detailed academic studies on the evaluation of risks arising from Sukuk structures.

The purpose of this research is to investigate whether inclusion of risk assessment variables in the multiple discriminant analysis (MDA) model improved the banks ability in making correct customer classification, predict firm's performance and credit risk assessment.

The paper reviews literature on the application of financial distress and credit scoring methods, and the use of risk assessment variables in classification models. The study used a sample of 56 performing and non‐performing assets (NPA) of a privatized commercial bank in Tanzania. Financial ratios were used as independent variables for building the MDA model with a variation of five MDA models. Different statistical tests for normality, equality of covariance, goodness of fit and multi‐colinearity were performed. Using the estimation and validation samples, test results showed that the MDA base model had a higher level of predictability hence classifying correctly the performing and NPA with a correctness of 92.9 and 96.4 percent, respectively. Lagging the classification two years, the results showed that the model could predict correctly two years in advance. When MDA was used as a risk assessment model, it showed improved correct customer classification and credit risk assessment.

The findings confirmed financial ratios as good classification and predictor variables of firm's performance. If the bank had used the MDA for classifying and evaluating its customers, the probability of failure could have been known two years before actual failure, and the misclassification costs could have been calculated objectively. In this way, the bank could have reduced its non‐performing loans and its credit risk exposure.

The valiadation sample used in the study was smaller compared to the estimation sample. MDA works better as a credit scoring method in the banking environment two years before and after failure. The study was done on the current financial crisis of 2009.

Use of MDA helps banks to determine objectively the misclassification costs and its expected misclassification errors plus determining the provisions for bad debts. Banks could have reduced the non‐performing loans and their credit risks exposure if they had used the MDA method in the loan‐evaluation and classification process. The study has proved that quantitative credit scoring models improve management decision making as compared to subjective assessment methods. For improved credit and risk assessment, a combination of both qualitative and quantitave methods should be considered.

The findings have shown that using the MDA, commercial banks could have improved their objective decision making by correctly classifying the credit worthiness of a customer, predicting firm's future performance as well as assessing their credit risk. It has also shown that other than financial variables, inclusion of stability measures improves management decision making and objective provisioning of bad debts. The recent financial crisis emphasizes the need for developing objective credit scoring methods and instituting prudent risk assessment culture to limit the extent and potential of failure.

The classification of criminal acts as violent or nonviolent should be a keystone of actuarial predictors of violent recidivism, as it affects their outcome measure and scoring of criminal history, thus influencing many decisions about sentencing, release and treatment allocation. Examination of existing actuarial and clinical violence risk assessment tools and research studies reveals considerable variation in the classifications used. This paper aims to use large samples to develop an alternative, empirically grounded classification that can be used to improve actuarial predictive scores within the offender assessment system (OASys), the tool used by the National Offender Management Service of England and Wales to assess static and dynamic risk.

Two analytical steps are implemented. First, to identify offences that frequently involve violent acts, 230,334 OASys cases are analyzed for indicators of violent content. Second, the ability of dynamic and static risk factors to predict reoffending for various offence types is investigated, analyzing 26,619 OASys cases that have official recidivism data.

The resulting empirical classification of violent offences adds public order, criminal damage, threats/harassment, robbery/aggravated burglary and weapon possession offences to the central group of homicide and assault offences. The need to assess risk of sexual recidivism separately is discussed.

This study has successfully produced an offence classification for use in a new predictor of violent recidivism. The use of empirical methods to select these offences helps to maximise predictive validity.

Studies addressing barriers to implement lean production (LP) from the perspective of risk management (RM) have not been so usual in the literature. Re-interpreting barriers to lean as potential risks that should be avoided or mitigated, this paper aims to identify and categorise risks in the implementation of LP to propose a framework, which provides an overview of risks that negatively influence this process.

Through a systematic literature review exploring papers in the Web of Knowledge database, 69 papers were selected. A descriptive analysis was first carried out to identify the evolution in the number of papers, usual terminologies, research methods, analytic tools and the RM phases approached by each paper. After that, an in-depth study of the paper sample was conducted to find risk factors and categories.

The authors found a list of 61 risk factors. Then, considering the sources of the identified risk factors, six broad categories of risks were defined, namely, top management risks, human resources risks, lean knowledge risks, technical risks, supply chain risks and cultural risks. The authors also defined 34 subcategories, resulting in a risk classification framework.

Based on the review, the authors identified literature gaps and provided a research agenda. A noteworthy research limitation is that the authors only selected papers about LP, so the authors might have missed some potential risks in lean implementation that may arise from other-related areas. Thus, the exploration of lean risks adopting other perspectives may constitute a promising pathway for further research.

The classification framework may help practitioners and researchers in risk identification, evaluation and mitigation. It can also enable the creation of response plans to risks in lean production implementation, as it indicates the potential risks that may be faced along with this process.

This study contributed to add the perspective of RM to the literature on lean implementation. The introduction of RM concepts and tools may generate more robust models of lean implementation. Therefore, the classification framework may represent a starting point to produce new knowledge about this research topic.

The purpose of this paper is to present a critical review of a criterion of risk, created to assess the flood risk of the international heritage building. In order to evaluate this criterion, it was applied to a sample of Portuguese building heritage.

This effort will start with the definition of the most important historical buildings in Portugal, its location and a full study about its constitution considering not only the materials they are made to but also the layers and the influence of the porosity/porometry for the drying process. Then it will also crucial the classification of the flood risk occurrence having in mind the previous information. A mapping will be made with the classification here developed.

This work presents a critical review of the main information related with the Portuguese monuments classified as “National Monuments”. A new empirical model was proposed takes into account all of the factors defined as the most influent in flood risk determination. A risk map was created on the basis classification developed. It will be possible to observe that a significant amount of Portuguese monuments are classified as medium to high risk of flooding.

This paper presents a new methodology to analyse the flood risk of international heritage building. The main benefit of the work is that it discusses the importance architectural heritage and justifies the need to safeguard it from extreme climatic phenomena such as floods.

The purpose of this paper is twofold: to classify the risks that affect the lean production implementation (LPI) process, and to demonstrate how that classification can help to identify the relationships between the risks.

Initially, a survey was conducted to identify the probability and impact of 14 risks in LPI, which had been identified based on a literature review. The sample comprised 57 respondents, from companies in the south of Brazil. An exploratory factor analysis was carried out to analyze the results of the survey, allowing the identification of three groups of risks in LPI. Then, a case study was conducted in one of the companies represented in the survey, in order to identify examples of relationships between the risks. Multiple sources of evidence were used in the case study, such as interviews, observations and documents analysis.

The risks that affect LPI were grouped into three categories: management of the process of LPI, top and middle management support and shop floor involvement. A number of examples of relationships between the risks were identified.

The survey was limited to companies from the south of Brazil and therefore its results cannot be completelly generalized to other companies. Moreover, the results of the survey were not subjected to a confirmatory factor analysis.

This study helps to improve the understanding of LPI, as: it re-interprets the factors, barriers and difficulties for LPI from the perspective of risk management, which had not been used for that purpose so far; it presents a classification of the risks that affect LPI, which can support the understanding of the relationships between the risks and, as a result, it can support the development of more effective methods for LPI.

The purpose of this paper is to examine the role of the International Union for the Conservation of Nature (IUCN) Red List of Threatened Species in achieving biodiversity conservation and preventing the extinction of species. The Red List is a calculative device that classifies species in terms of their exposure to the risk of extinction.

The paper draws on theorising in the Social Studies of Finance literature to analyse the Red List in terms of how it frames a space of calculability for species extinction. The analysis then traces the ways that this framing has overflowed, creating conditions for calculative innovations, such that assemblages of humans and calculative devices (i.e. agencements) are constructed with collective capabilities to act to conserve biodiversity and prevent species extinctions.

This paper has traced three ways that the Red List frame has overflowed, leading to calculative innovations and the construction of new agencements. The overflow of relations between the quality of “extinction risk”, produced by the Red List, and other qualities, such as location, has created opportunities for conservationists to develop agencements capable of formulating conservation strategies. The overflow of relations between the identity of the “threatened species”, produced by the Red List, and other features of evaluated species, has created opportunities for conservationists to develop agencements capable of impelling participation in conservation efforts. The overflow of ecological relations between species, discarded by the Red List’s hierarchical metrology of extinction risk classifications, has created opportunities for conservationists to develop agencements capable of confronting society with the reality of an extinction crisis.

The paper contributes to the accounting for biodiversity literature by addressing its fundamental challenge: explaining how accounting can create conditions within society in which biodiversity conservation is made possible.

This study aims to identify problems connected to information classification in theory and to put those problems into the context of experiences from practice.

Five themes describing problems are discussed in an empirical study, having informants represented from both a public and a private sector organization.

The reasons for problems to occur in information classification are exemplified by the informants’ experiences. The study concludes with directions for future research.

Information classification sustains the basics of security measures. The human–organizational challenges are evident in the activities but have received little attention in research.