Abstract: Monitoring transaction activity for system requests for a set of entities authorized to request services of a system is described. Entities with high feature values for respective features of the set of activity based features are identified to produce a set of outlier entities. The outlier entities are filtered from the set of entities. A set of clusters are created from the filtered set of entities based on the set of activity based features so that each entity in the filtered set of entities is assigned to a cluster. Values for the set of activity based features are established for each cluster. A risk is assigned for each cluster based on the values of one or more of the set of activity based features. Each of the filtered set of entities are monitored based on the risk assigned to the respective clusters to which the respective entities belong.

Abstract: Systems and methods are disclosed herein for identifying potential insurance prospects. The potential customers or prospects are identified by determining prospect underwriting affinity scores, prospect affinity scores, and prospect context scores with predictive models. The scores are then combined into a combined prospect score, which is used to adjust insurance underwriting, workflow, and premium determination processes for the prospects.

Abstract: A system includes an insurance component selection platform that transmits data to and receives data from an insurance product component storage unit storing one or more self-descriptive components of an insurance coverage. Each of the stored components may have associated properties defining attributes of the component and one or more values associated with the properties. The components may be selected via a graphical interface generated by the component selection platform to be included in an insurance coverage product. The components may then be combined within constraints of the properties and values of the individual components. An insurance coverage policy may then be presented based on the combination of components.

Abstract: A system includes an insurance component selection platform that transmits data to and receives data from an insurance product component storage unit storing one or more self-descriptive components of an insurance coverage. Each of the stored components may have associated properties defining attributes of the component and one or more values associated with the properties. The components may be selected via a graphical interface generated by the component selection platform to be included in an insurance coverage product. The components may then be combined within constraints of the properties and values of the individual components. An insurance coverage policy may then be presented based on the combination of components.

Abstract: A method and system for generating recommendations is provided. The method includes accepting queries and revised assumptions associated with shopping habits of a shopper. Responses to the queries are generated. The responses are associated with product features for products. A group of shoppers and associated interests are characterized resulting in a creation of a group of recommended products. Alternative products associated with the recommended products are determined based on the revised assumptions and a consistency of assumptions is managed.

Abstract: A computer system includes a data storage device. The data storage module receives, stores, and provides access to historical entity data and insurance coverage package data. A recommendation engine comprising program instructions stored in a program memory receives current entity data, creates a current entity representative record based on the received current entity data and historical entity data, creates one or more historical entity representative records for each of a plurality of insurance coverage packages, identifies one of the historical entity representative records based on the current entity representative record, identifies one or more of the plurality of insurance coverage packages based on the identified historical entity representative record, and presents the identified one or more insurance coverage packages when executed by a computer processor.

Abstract: A computer system includes a data storage device. The data storage module receives, stores, and provides access to historical entity data and insurance coverage package data. A recommendation engine comprising program instructions stored in a program memory receives current entity data, creates a current entity representative record based on the received current entity data and historical entity data, creates one or more historical entity representative records for each of a plurality of insurance coverage packages, identifies one of the historical entity representative records based on the current entity representative record, identifies one or more of the plurality of insurance coverage packages based on the identified historical entity representative record, and presents the identified one or more insurance coverage packages when executed by a computer processor.

Abstract: A method and system for generating recommendations is provided. The method includes accepting queries and revised assumptions associated with shopping habits of a shopper. Responses to the queries are generated. The responses are associated with product features for products. A group of shoppers and associated interests are characterized resulting in a creation of a group of recommended products. Alternative products associated with the recommended products are determined based on the revised assumptions and a consistency of assumptions is managed.

Abstract: A system includes an insurance component selection platform that transmits data to and receives data from an insurance product component storage unit storing one or more self-descriptive components of an insurance coverage. Each of the stored components may have associated properties defining attributes of the component and one or more values associated with the properties. The components may be selected via a graphical interface generated by the component selection platform to be included in an insurance coverage product. The components may then be combined within constraints of the properties and values of the individual components. An insurance coverage policy may then be presented based on the combination of components.

Abstract: A system may include an insurance component selection platform that transmits data to and receives data from an insurance product component storage unit storing one or more self-descriptive components of an insurance coverage. Each of the stored components may have associated properties defining attributes of the component and one or more values associated with the properties. The components may be selected via a graphical interface generated by the component selection platform to be included in an insurance coverage product. The components may then be combined within constraints of the properties and values of the individual components. An insurance coverage policy may then be presented based on the combination of components.

Abstract: Systems and methods are disclosed herein for identifying potential insurance prospects. The potential customers or prospects are identified by determining prospect underwriting affinity scores, prospect affinity scores, and prospect context scores with predictive models. The scores are then combined into a combined prospect score, which is used to adjust insurance underwriting, workflow, and premium determination processes for the prospects.

Abstract: Systems and methods are disclosed herein for identifying potential insurance prospects. The potential customers or prospects are identified by determining prospect underwriting affinity scores, prospect affinity scores, and prospect context scores with predictive models. The scores are then combined into a combined prospect score, which is used to adjust insurance underwriting, workflow, and premium determination processes for the prospects.

Abstract: According to some embodiments, a system may be provided including an insurance component selection platform that transmits data to and receives data from an insurance product component storage unit storing one or more self-descriptive components of an insurance coverage. Each of the stored components may have, for example, associated properties defining attributes of the component and one or more values associated with the properties. The components may be selected via a graphical interface generated by the component selection platform to be included in an insurance coverage product. The components may then be combined within constraints of the properties and values of the individual components. An insurance coverage policy may then be presented based on the combination of components.

Abstract: Systems and methods for performing fault analysis using numerically coded time series data are disclosed. First time series data, including a plurality of first time entries and an associated first data value for each first time entry, may be received for a machine variable for a first printer. Second time series data, including a plurality of second time entries and an associated second data value for each second time entry, may be received for the machine variable for each of a plurality of second printers. For each second printer, a similarity measurement may be determined for the first time series data for the first printer and the second time series data for the second printer. One or more closest matching second printers may be determined based on the similarity measurements. An association may be displayed between the first printer and each closest matching second printer.

Abstract: A computer system includes a data storage device. The data storage module receives, stores, and provides access to historical entity data and insurance coverage package data. A recommendation engine comprising program instructions stored in a program memory receives current entity data, creates a current entity representative record based on the received current entity data and historical entity data, creates one or more historical entity representative records for each of a plurality of insurance coverage packages, identifies one of the historical entity representative records based on the current entity representative record, identifies one or more of the plurality of insurance coverage packages based on the identified historical entity representative record, and presents the identified one or more insurance coverage packages when executed by a computer processor.

Abstract: Systems and methods for performing fault analysis using numerically coded time series data are disclosed. First time series data, including a plurality of first time entries and an associated first data value for each first time entry, may be received for a machine variable for a first printer. Second time series data, including a plurality of second time entries and an associated second data value for each second time entry, may be received for the machine variable for each of a plurality of second printers. For each second printer, a similarity measurement may be determined for the first time series data for the first printer and the second time series data for the second printer. One or more closest matching second printers may be determined based on the similarity measurements. An association may be displayed between the first printer and each closest matching second printer.

Abstract: Systems and methods for analyzing time series data are disclosed. A query including a machine variable identifier may be received. The machine variable identifier may include an identifier pertaining to one or more of a state, a condition and a performance measure for a printer. A first time series data entry may be determined based on the query. The first time series data entry may include a data value and a time entry for the machine variable identifier. One or more second time series data entries may be selected based on the data value associated with the first time series data entry. One or more maintenance operations may be performed based on the one or more second time series data entries.

Abstract: Systems and methods for performing fault analysis using numerically coded time series data are disclosed. First time series data, including a plurality of first time entries and an associated first data value for each first time entry, may be received for a machine variable for a first printer. Second time series data, including a plurality of second time entries and an associated second data value for each second time entry, may be received for the machine variable for each of a plurality of second printers. For each second printer, a similarity measurement may be determined for the first time series data for the first printer and the second time series data for the second printer. One or more closest matching second printers may be determined based on the similarity measurements. An association may be displayed between the first printer and each closest matching second printer.

Abstract: Systems and methods for analyzing time series data are disclosed. A query including a machine variable identifier may be received. The machine variable identifier may include an identifier pertaining to one or more of a state, a condition and a performance measure for a printer. A first time series data entry may be determined based on the query. The first time series data entry may include a data value and a time entry for the machine variable identifier. One or more second time series data entries may be selected based on the data value associated with the first time series data entry. One or more maintenance operations may be performed based on the one or more second time series data entries.

Abstract: Systems and methods for performing fault analysis using numerically coded time series data are disclosed. First time series data, including a plurality of first time entries and an associated first data value for each first time entry, may be received for a machine variable for a first printer. Second time series data, including a plurality of second time entries and an associated second data value for each second time entry, may be received for the machine variable for each of a plurality of second printers. For each second printer, a similarity measurement may be determined for the first time series data for the first printer and the second time series data for the second printer. One or more closest matching second printers may be determined based on the similarity measurements. An association may be displayed between the first printer and each closest matching second printer.