Purpose: this study wants to find any relationship between the numbers of purchase and the income the customer brings to the company. The attempt is to find those customers who buy more than one life insurance policy and represent the signs of good payments at the same time by the help of data mining tools. Design/ methodology/ approach: the approach of this research is to use data mining tools based on CRISP-DM methodology. The classification is based on the K-means algorithm and prediction is applied by a proposed formula by the researcher in Excel worksheet. Findings: By selecting the customers who bought more than one policy, and filtering the Income bringer customers, the researcher could extract some simple rules to predict which customer belongs to which cluster. Based on the prediction, the company can change its strategies in relation to different customers. Originality/value: Utilizing data mining approach to classify different customers in life insurance and prediction based on the classification is a new approach amongIran insurance companies. There is not enough research and implementation in relation to the CRM and data mining in the insurance industry. Especially CRISP-DM methodology was used very hardly before in a life insurance investigation. تفاصيل المقالة

This paper provides a Fuzzy based decision support system (DSS) for risk analysis in E-tourism ( Electronic Tourism ) investment. In general term, E-tourism is the use of information and communication technology (ICT) in tourism which may allow operating tourism in least variable cost, least time and increased work efficiency. It is worth noting that there are many factors that affect the development of E-tourism. To demonstrate the effectiveness of the system, four factors of investment, human IT skill, E-tourism infrastructure and stability of the regions are considered in the present study. These parameters are fuzzified and a fuzzy rule-base has been developed for calculating risk factor for the E-tourism investment. The researchers used MATLAB software for fuzzifying the factors and gain the final risk. Case studies have been presented using the developed model. It shows that the investment possibility in developed region is high with low risk to invest. تفاصيل المقالة

This paper describes the development of a fuzzy decision support system (FDSS) for the assessment of risk in E-commerce (EC) development. A Web-based prototype FDSS is suggested to assist EC project managers in identifying potential EC risk factors and the corresponding project risks. A risk analysis model for EC development using a fuzzy set approach is proposed and incorporated into the FDSS. For running the fuzzy set approach, the researchers use MATLAB software. The research methodology includes these stages: At first, identifying the factors effect on the development of the E-commerce with the help of experts; secondly, defining the suitable membership function for each factor. There are three layers in the fuzzy system that every layers output is input for next layer. Then, the system calculates the final risk through SUGENO inference engine for E-commerce. Indeed the suggested architecture for the model with the help of experts is presented in this paper. تفاصيل المقالة

The main challenge for any insurer/reinsurer has proved to be underwriting major refinery/Petrochemical risk. Insurers have already considered process risk management measures while accepting and evaluating the risks all over the world. Erstwhile petrochemical tariff was adopting experiencing methodology as basis for premium calculation in Iran. In the present de-tariff scenario decisions will be crucial for underwriters on accepting the risk and deciding the terms and conditions. On the other hand the insured will be looking for merit based rating instead of general market driven premium calculations. Generalizing the risks based on the type of occupancy or the past experience also won’t do well either to the insured or to the insurer. Chemical process quantitative risk analysis (CPQRA) is a methodology designed to provide management with a tool to help evaluate overall process safety in the chemical process industry (CPI). Management systems such as engineering codes, checklists and process safety management (PSM) provide layers of protection against accidents. However, the potential for serious incidents cannot be totally eliminated. CPQRA provides a quantitative method to evaluate risk and to identify areas of cost-effective risk reduction. This method can be used as an effective tool in the entire gamut of underwriting of petrochemical risks in case of property insurance. One of the most important issues in insurance companies, is the making the wise decision on insurance risk. Insurers to cover risks in the process of motivation and a desire to identify and eliminate conditions that risk. Premiums payable by the insurer that the insurance will be commensurate with risk. Insurers attempt to identify and reduce risk plays an important role in increasing safety in the community. One major concern to insurers or reinsurers is whether to accept the risk of petrochemical refineries, and the tariffs and conditions commensurate with the identified risks . Insurers always seek ways to reduce risk insured. The present paper introduces the effective process of risk analysis that can be applied by the Insurance companies in order to identify and predict this kind risks. تفاصيل المقالة