Abstract: A data science model score database may contain electronic records, each including a data science model identifier and a set of data science model scores. A data science model score server, coupled to the data science model score database, may receive (from a remote user device) an indication of a selected data science model. The server may then retrieve, from the data science score database, information about the selected data science model. Based on the retrieved information, the server may automatically calculate a maturity score for the selected data science model in accordance with a scalable score, a service-oriented score, a validated score, and a productized score. When the server receives from the remote user device an adjustment to at least one of the scalable score, the service-oriented score, the validated score, and the productized score, it may automatically re-calculate the maturity score for the selected data science model.

Abstract: A computer system for selection of data records for forwarding includes one or more data storage devices storing data records including structured and unstructured data, and an analysis hardware server configured to, in cycles, determine sets of data records for predictive model review, extract words and phrases from the unstructured data, apply the predictive model to determine current-cycle scores for the data records of the set, assign the data records to groups in accordance with the current-cycle score, determine a velocity of change in group, and select data records for forwarding to an operation system based at least in part on the determined velocity of change in group.

Abstract: Text input data may be aggregated and mapped to create composite text input data for electronic records. A semantic event may be automatically detected, triggered by a semantic rule and associated semantic tag. The detected semantic event may be flagged, and a text mining result database may be updated by adding an entry to the database. An indication associated with the event may be transmitted, and a back-end application computer server may establish a hierarchy for multiple elements of the electronic records. The computer server may determine a weight variable and response variable for each element in the hierarchy and apply a hierarchical credibility weighting methodology to the elements from level 1, representing the least granular level in the hierarchy, to level n, representing the most granular level in the hierarchy, calculated recursively from level n, to determine a final estimated credibility for the electronic records.

Abstract: In some embodiments, an input document is received at a tagging platform, via a communication device, and associates it with a tag request. The tagging platform automatically selects at least one electronic record associated with a first user from a user data store containing electronic records associated with users (each record including at least a user identifier and a user communication address). The input document and tag request are transmitted to the communication address associated with the first user, and a document tag is received from the first user. The tagging platform may then store the document tag in a document mining result database by adding an entry to the database identifying the received document tag and transmit an indication associated with the document mining result database to a plurality of risk applications.

Abstract: In some embodiments, an input document is received at a tagging platform, via a communication device, and associates it with a tag request. The tagging platform automatically selects at least one electronic record associated with a first user from a user data store containing electronic records associated with users (each record including at least a user identifier and a user communication address). The input document and tag request are transmitted to the communication address associated with the first user, and a document tag is received from the first user. The tagging platform may then store the document tag in a document mining result database by adding an entry to the database identifying the received document tag and transmit an indication associated with the document mining result database to a plurality of risk applications.

Abstract: A device and method are described for a universal analytical data mart and data structure for same. The analytical data mart (ADM) associated data structure is designed to allow data from disparate sources to be integrated, enabling streamlined business intelligence, reporting and ad hoc analysis. Conceptually, the ADM enables analytics and business intelligence from multiple frames of reference including people, such as parties and actors including individuals and organizations, places, such as addresses with geographic information at various levels of view, objects, such as insured properties, automobiles and machinery, and events, milestones which happen at points in time and provide analytical/business value.

Abstract: A device and method are described for a universal analytical data mart and data structure for same. The analytical data mart (ADM) associated data structure is designed to allow data from disparate sources to be integrated, enabling streamlined business intelligence, reporting and ad hoc analysis. Conceptually, the ADM enables analytics and business intelligence from multiple frames of reference including people, such as parties and actors including individuals and organizations, places, such as addresses with geographic information at various levels of view, objects, such as insured properties, automobiles and machinery, and events, milestones which happen at points in time and provide analytical/business value.

Abstract: A device and method is disclosed for automatically grouping data based on characteristics. The device and method include a communication interface for receiving data for component information, a storage medium for storing the received data, and a processor for performing an analysis on the received data to determine parameters included within the data and processing the data using correlations within the data to group or isolate data points. The correlations enable the processor to identify attributes associated with particular groups of the data.

Abstract: A computer system for selection of data records for forwarding includes one or more data storage devices storing data records including structured and unstructured data, and an analysis hardware server configured to, in cycles, determine sets of data records for predictive model review, extract words and phrases from the unstructured data, apply the predictive model to determine current-cycle scores for the data records of the set, assign the data records to groups in accordance with the current-cycle score, determine a velocity of change in group, and select data records for forwarding to an operation system based at least in part on the determined velocity of change in group.

Abstract: A device and method is disclosed for automatically grouping data based on characteristics. The device and method include a communication interface for receiving data for component information, a storage medium for storing the received data, and a processor for performing an analysis on the received data to determine parameters included within the data and processing the data using correlations within the data to group or isolate data points. The correlations enable the processor to identify attributes associated with particular groups of the data.

Abstract: Text input data may be aggregated and mapped to create composite text input data for electronic records. A semantic event may be automatically detected, triggered by a semantic rule and associated semantic tag. The detected semantic event may be flagged, and a text mining result database may be updated by adding an entry to the database. An indication associated with the event may be transmitted, and a back-end application computer server may establish a hierarchy for multiple elements of the electronic records. The computer server may determine a weight variable and response variable for each element in the hierarchy and apply a hierarchical credibility weighting methodology to the elements from level 1, representing the least granular level in the hierarchy, to level n, representing the most granular level in the hierarchy, calculated recursively from level n, to determine a final estimated credibility for the electronic records.

Abstract: A computer system for selection of data records for forwarding includes one or more data storage devices storing data records including structured and unstructured data, and an analysis hardware server configured to, in cycles, determine sets of data records for predictive model review, extract words and phrases from the unstructured data, apply the predictive model to determine current-cycle scores for the data records of the set, assign the data records to groups in accordance with the current-cycle score, determine a velocity of change in group, and select data records for forwarding to an operation system based at least in part on the determined velocity of change in group.

Abstract: In some embodiments, an input document is received at a tagging platform, via a communication device, and associates it with a tag request. The tagging platform automatically selects at least one electronic record associated with a first user from a user data store containing electronic records associated with users (each record including at least a user identifier and a user communication address). The input document and tag request are transmitted to the communication address associated with the first user, and a document tag is received from the first user. The tagging platform may then store the document tag in a document mining result database by adding an entry to the database identifying the received document tag and transmit an indication associated with the document mining result database to a plurality of risk applications.

Abstract: Text input data may be aggregated and mapped to create composite text input data for electronic records. A semantic event may be automatically detected, triggered by a semantic rule and associated semantic tag. The detected semantic event may be flagged, and a text mining result database may be updated by adding an entry to the database. An indication associated with the event may be transmitted, and a back-end application computer server may establish a hierarchy for multiple elements of the electronic records. The computer server may determine a weight variable and response variable for each element in the hierarchy and apply a hierarchical credibility weighting methodology to the elements from level 1, representing the least granular level in the hierarchy, to level n, representing the most granular level in the hierarchy, calculated recursively from level n, to determine a final estimated credibility for the electronic records.

Abstract: A device and method are described for a universal analytical data mart and data structure for same. The analytical data mart (ADM) associated data structure is designed to allow data from disparate sources to be integrated, enabling streamlined business intelligence, reporting and ad hoc analysis. Conceptually, the ADM enables analytics and business intelligence from multiple frames of reference including people, such as parties and actors including individuals and organizations, places, such as addresses with geographic information at various levels of view, objects, such as insured properties, automobiles and machinery, and events, milestones which happen at points in time and provide analytical/business value.

Abstract: A device and method are described for universally repositing repeatedly accessible information.

Abstract: A device and method are described for a universal analytical data mart and data structure for same. The analytical data mart (ADM) associated data structure is designed to allow data from disparate sources to be integrated, enabling streamlined business intelligence, reporting and ad hoc analysis. Conceptually, the ADM enables analytics and business intelligence from multiple frames of reference including people, such as parties and actors including individuals and organizations, places, such as addresses with geographic information at various levels of view, objects, such as insured properties, automobiles and machinery, and events, milestones which happen at points in time and provide analytical/business value.

Abstract: A system for evaluating text data to support multiple applications is disclosed. In some embodiments, text input data is received from multiple sources. The text input data may then be aggregated and mapped to create composite text input data. A semantic event in the composite text input data may be automatically detected, such as by being triggered by a semantic rule and associated semantic tag. A text mining result database may be updated by adding an entry to the database identifying the detected semantic event and the triggering semantic rule. An indication associated with the text mining result database may then be transmitted to a plurality of applications.

Abstract: A device and method are described for a universal analytical data mart and data structure for same. The analytical data mart (ADM) associated data structure is designed to allow data from disparate sources to be integrated, enabling streamlined business intelligence, reporting and ad hoc analysis. Conceptually, the ADM enables analytics and business intelligence from multiple frames of reference including people, such as parties and actors including individuals and organizations, places, such as addresses with geographic information at various levels of view, objects, such as insured properties, automobiles and machinery, and events, milestones which happen at points in time and provide analytical/business value.

Abstract: A computer system for selection of data records for forwarding includes one or more data storage devices storing data records including structured and unstructured data, and an analysis hardware server configured to, in cycles, determine sets of data records for predictive model review, extract words and phrases from the unstructured data, apply the predictive model to determine current-cycle scores for the data records of the set, assign the data records to groups in accordance with the current-cycle score, determine a velocity of change in group, and select data records for forwarding to an operation system based at least in part on the determined velocity of change in group.