Computerized Protection System and Method for Automatically Identifying and/or Characterizing Risk Parameters

Abstract

The invention concerns a computerized protection system and method for automatically identifying and/or characterizing risk parameters. The invention is characterized in that it comprises a look up table ( 4 ) containing risk parameters, produced based on data records of products and/or populations, accessibly stored, in databanks ( 2 ), and classes of risk are produced, in combination with the records of products and/or populations, by means of a filtering module ( 3 ), based on risk parameters of the look up table ( 4 ); an analyzing module ( 1 ) is used for producing for each class of risk, at least one commuted value of the probability of occurrence of a definable event, and a normalizing module ( 5 ) is used for normalizing the commuted value of the respective class of risk, based on the average input speed of the event for the data files of products and/or populations, with respect to a relative input parameter; and the analyzing module ( 1 ) produces a risk characterizing value for the respective class of risk, based on the comparison between the relative input parameters.

1 . A computer-aided method for automated risk parameter identification and/or characterization, where relative risk values for a multiplicity of products and/or populations are determined, characterized
 in that product and/or population data records stored accessibly in databases ( 2 ) are taken as a basis for generating a lookup table ( 4 ) containing risk parameters,   in that a filter module ( 3 ) is used to store risk classes in association with the product and/or population data records on the basis of the risk parameters from the lookup table ( 4 ),   in that an analysis module ( 1 ) is used to generate at least one expected value for a probability of occurrence of a definable risk event for each risk class and to store it in association with the risk event,   in that a normalization module ( 5 ) is used to normalize the expected value for the respective risk class on the basis of an average rate of occurrence of the event for the product and/or population data records to produce a relative occurrence parameter, and   in that the analysis module ( 1 ) is used to produce a risk characterization value for the respective risk class on the basis of the comparison of the relative occurrence parameters, with the risk characterization value determining the probability of occurrence of the risk event.   
     
     
         2 . The method as claimed in  claim 1 , characterized in that, for a specific combination of risk classes, a risk characterization value is determined using the analysis module ( 1 ) and is compared with available empirical data records for the purpose of characterizing the product and/or the population, where only typical risk characterizations situated within a definable threshold value are associated with the risk class. 
     
     
         3 . The method as claimed in either of  claims 1  and  2 , characterized in that one or more of the risk classes have an associated multiplicity of risk parameters, where the method is repeated with the risk parameters modified and the deviations from the expected values are stored in association with the risk classes. 
     
     
         4 . The method as claimed in one of  claims 1  to  3 , characterized in that the analysis module ( 1 ) is used to determine correlation factors between the risk parameters on the basis of the population data files divided into risk classes and to store them in association with the relevant risk parameters. 
     
     
         5 . The method as claimed in one of  claims 1  to  4 , characterized in that one or more threshold values are used to allocate each risk parameter a relevance flag for a particular population and/or product. 
     
     
         6 . The method as claimed in one of  claims 1  to  5 , characterized in that the lookup table ( 4 ) containing risk parameters is generated at least partly dynamically on the basis of product and/or population data records stored accessibly in databases ( 2 ). 
     
     
         7 . The method as claimed in one of  claims 1  to  6 , characterized in that for secondary risk groups at least one separate relative occurrence parameter is generated. 
     
     
         8 . The method as claimed in one of  claims 1  to  7 , characterized in that when the data are compared with the empirical data stored in relevant memory units ( 6 ) the data, if situated outside of a determinable fluctuation tolerance, are aligned with the empirical data. 
     
     
         9 . The method as claimed in one of  claims 1  to  8 , characterized in that the risk parameters comprise at least the relative mortality risks. 
     
     
         10 . The method as claimed in one of  claims 1  to  9 , characterized in that new risk classes are produced dynamically on the basis of at least parts of the relative occurrence parameters. 
     
     
         11 . The method as claimed in one of  claims 7  to  10 , characterized in that the secondary risk groups comprise at least sex and/or age of occurrence and/or smoker/non-smoker and/or policy duration. 
     
     
         12 . A computer-aided system for automated determination of relative risks which are linked to a multiplicity of financial products, comprising:
 a) means for identifying one or more risk classes which are associated with the multiplicity of financial products;   b) means for determining an expected rate of occurrence for each risk class;   c) means for dividing the expected rates of occurrence by an average rate in order to determine a relative risk ratio for each risk class; and   d) means for comparing the relative risk ratios for the purpose of characterizing the relative risks linked to the multiplicity of products.   
     
     
         13 . The computer-aided system as claimed in  claim 12 , characterized in that said one or more risk classes are associated with one or more criteria, and which additionally has means for modifying one or more criteria and for recalculation of the relative risk ratio for determining an effect of said modification on the relative risks which are linked to the products. 
     
     
         14 . The computer-aided system as claimed in either of  claims 12  and  13 , characterized in that one or more of said risk classes are linked to different criteria, and in which said relative risk ratios are used for comparing said risk classes. 
     
     
         15 . The computer-aided system as claimed in one of  claims 12  to  14 , characterized in that it comprises means for applying the relative risk ratio to redefining one or more of said risk classes. 
     
     
         16 . The computer-aided system as claimed in one of  claims 12  to  15 , characterized in that it comprises means for determining a separate relative risk ratio for risk subgroups. 
     
     
         17 . The computer-aided system as claimed in one of  claims 12  to  16 , characterized in that for use in determining the relative risk ratios it comprises means for storing data which relate to the predominance of criteria which are linked to said risk classes. 
     
     
         18 . The computer-aided system as claimed in one of  claims 12  to  17 , characterized in that it comprises means for comparing the predominance data with empirical industrial data for particular combinations of criteria and means for aligning the stored data with the empirical data. 
     
     
         19 . The computer-aided system as claimed in one of  claims 12  to  18 , characterized in that it comprises means for storing data which relate to the expected rates of occurrence for the purpose of use when determining the relative risk ratios. 
     
     
         20 . The computer-aided system as claimed in one of  claims 12  to  19 , characterized in that it comprises means for comparing the stored data with empirical industrial data and means for aligning the stored data with the empirical data. 
     
     
         21 . The computer-aided system as claimed in one of  claims 12  to  20 , characterized in that the one or more risk classes are associated with at least one criterion, and also containing means for using the relative risk ratio to determine the effect which the inclusion in a risk class of one or more risks which do not meet one or more criteria linked to this risk class has on this risk class.