Made available in DSpace on 2015-04-09T12:28:27Z (GMT). No. of bitstreams: 0 Previous issue date: 2014-11-10Bitstream added on 2015-04-09T12:47:32Z : No. of bitstreams: 1 000814919.pdf: 1106420 bytes, checksum: 6bbc007e3e1451a2648cbfdb3aeef795 (MD5) / The insurer that has an effective control of the risks involved by the insureds can avoid issues such as bankruptcy and loss of profitability. The purpose of the research was to identify the varieties that define the risk associated with future buyers, enabling classify them into one of two groups, the claimed and the unclaimed, based in probabilities defined by a multivariate model. Therefore, were questions considered (variables) existing on the risk evaluation of the insurers questionnaire and others nominated by the expert brokers of the insurers. To achieve the objective, was used in the analyses, the multivariate statistical technique, known as Discriminant Analysis, in order to segregate the individual into one of two groups. A discriminant function was constructed from the independent variables, associated to the risks, and from the dependent variable, which covers the two groups. Other results as estimation of the classification rule, evaluation of the quality of the discrimination rule settings, estimation of the overall probability of correct answers and tests related to the assumptions of discriminant analysis were presented. The studied sample was consisted of 2,000 insured served by the broker, divided into two groups: the first composed of individuals without claims; and the second with those who has one or more claims. The model enabled to classify individuals by the two groups, wherein in the development sample and test the classification represented 69% accuracy. The separation was carried out by variables with higher importance degrees. Where elected: car power, time of insurance, bonus, parking lot use, and professional activities defined by the insured occupation. Such variables can be considered highly discriminating, based on the contribution coefficient for the discrimination. This work has presented results that contradict the common sense in the insurance market, in which technicians say that sex and age determine whether / The insurer that has an effective control of the risks involved by the insureds can avoid issues such as bankruptcy and loss of profitability. The purpose of the research was to identify the varieties that define the risk assciated with future buyers, enabling classify them into one two groups, the claimed and the unclaimed, based in probabilities defined by a multivariate model. Therefore, were questions considered (variables) existing on the risk evaluation of the insurers questionnarie and others nominated by the expert brokers of the insurers. To achieve the objective, was used in the analysis, the multivariate statistical technique, known as Discriminant Analylsis, in order to segregate the individual into one of two groups. A discriminant function was constructed from the independent variables, associated to the risks, and the dependent variable, which covers the two groups. Other results as estimation of the classification rule, evaluation of the quality of the discrimination rule settings, estimation of the overall probability of correct answers and tests related to the assumptions of discrimination analysis were presented. The studied sample was consisted of 2,000 insured served by the broker, divided into two groups: the first composed of individuals without claims; and the second with those who has one or more claims. The model enabled to classify individuals by the two groups, wherein in the development sample and test the classification represented 69% accuracy. The separation was carried out by variables with higher importance degrees. Were elected: car power, time of insurance, bonus, parking lot use, and professional activities defined by the insured occupation. Such variables can be considered hihgly discriminating, based on the contribution coefficient for the discrimination. This work has presented results that contradict the common sense in the insurance market, in which technicians say that sex and age determine...

Orientador: Manoel Henrique Salgado / Banca: Gladys Dorotea Cacsire Barriga / Banca: João Pedro Albino / Resumo: The insurer that has an effective control of the risks involved by the insureds can avoid issues such as bankruptcy and loss of profitability. The purpose of the research was to identify the varieties that define the risk associated with future buyers, enabling classify them into one of two groups, the claimed and the unclaimed, based in probabilities defined by a multivariate model. Therefore, were questions considered (variables) existing on the risk evaluation of the insurers questionnaire and others nominated by the expert brokers of the insurers. To achieve the objective, was used in the analyses, the multivariate statistical technique, known as Discriminant Analysis, in order to segregate the individual into one of two groups. A discriminant function was constructed from the independent variables, associated to the risks, and from the dependent variable, which covers the two groups. Other results as estimation of the classification rule, evaluation of the quality of the discrimination rule settings, estimation of the overall probability of correct answers and tests related to the assumptions of discriminant analysis were presented. The studied sample was consisted of 2,000 insured served by the broker, divided into two groups: the first composed of individuals without claims; and the second with those who has one or more claims. The model enabled to classify individuals by the two groups, wherein in the development sample and test the classification represented 69% accuracy. The separation was carried out by variables with higher importance degrees. Where elected: car power, time of insurance, bonus, parking lot use, and professional activities defined by the insured occupation. Such variables can be considered highly discriminating, based on the contribution coefficient for the discrimination. This work has presented results that contradict the common sense in the insurance market, in which technicians say that sex and age determine whether / Abstract: The insurer that has an effective control of the risks involved by the insureds can avoid issues such as bankruptcy and loss of profitability. The purpose of the research was to identify the varieties that define the risk assciated with future buyers, enabling classify them into one two groups, the claimed and the unclaimed, based in probabilities defined by a multivariate model. Therefore, were questions considered (variables) existing on the risk evaluation of the insurers questionnarie and others nominated by the expert brokers of the insurers. To achieve the objective, was used in the analysis, the multivariate statistical technique, known as Discriminant Analylsis, in order to segregate the individual into one of two groups. A discriminant function was constructed from the independent variables, associated to the risks, and the dependent variable, which covers the two groups. Other results as estimation of the classification rule, evaluation of the quality of the discrimination rule settings, estimation of the overall probability of correct answers and tests related to the assumptions of discrimination analysis were presented. The studied sample was consisted of 2,000 insured served by the broker, divided into two groups: the first composed of individuals without claims; and the second with those who has one or more claims. The model enabled to classify individuals by the two groups, wherein in the development sample and test the classification represented 69% accuracy. The separation was carried out by variables with higher importance degrees. Were elected: car power, time of insurance, bonus, parking lot use, and professional activities defined by the insured occupation. Such variables can be considered hihgly discriminating, based on the contribution coefficient for the discrimination. This work has presented results that contradict the common sense in the insurance market, in which technicians say that sex and age determine... / Mestre