Abstract: A vehicle data collection and evaluation system. A vehicle data collection device is configured to collect the data associated with the operation of the vehicle. A transmitter is configured to transmit the collected data. An analytics server is configured to receive the collected data transmitted by the transmitter and to process the collected data. A rate processing server configured to determine a driver safety rating. The collected data comprises vehicle speed measured at a predetermined time interval and the analytics server (i) determines a change in speed value over the predetermined time interval and raises the change in speed value to an exponential power to determine an exponentiated change in speed value; (ii) determines a maximum speed of the vehicle during the predetermined time interval; and (iii) determines the driver safety rating based on the maximum speed and a magnitude of the exponentiated change in speed value relative to a distance traveled over the predetermined time interval.

Abstract: A system and method for calculating loss data associated with a data privacy and security breach event occurring within an organization based on collected data. Data describing a number of individuals affected by the event; an estimated number of hours spent by the organization on managing the event; enrollment by individuals affected by the event in a credit monitoring service; an estimated amount spent on communications within the organization relating to the event; an estimated number of hours of loss of productivity by the organization; an estimated credit monitoring service call center volume; an estimated amount spent on computer forensics; and an estimated amount spent on legal counsel is received.

Abstract: Improved computer modeling techniques, and uses thereof, are described herein. A set of unstructured textual data is received. Certain textual data is removed from the set of unstructured data to form an initial vocabulary set of textual data. One or more bigrams are added to the vocabulary set of textual data to form a final vocabulary set of textual data. The final vocabulary set of textual data is divided into a plurality of subsets of textual data based on type. A model is trained using each of the plurality of subsets of textual data to form a plurality of trained models, each corresponding to one of the types.

Abstract: The invention relates to detecting vulnerabilities in technology infrastructure environments. Data describing vulnerabilities detected in a technological environment of an enterprise is obtained. The vulnerability data is combined with data relating to servers, applications associated with the servers, and business functions associated with the applications, within the technological environment of the enterprise in order to create enriched data. The enriched data is enhanced using one or more of the following processes: deduplicating records in the enriched data; modifying of a severity assigned to vulnerabilities based on one or more enterprise-infrastructure factors; archiving and purging of records included in the enriched data; consolidating IP addresses associated with the vulnerabilities; excepting records in the enriched data for vulnerabilities undergoing active remediation; and validating the enriched data. After the enriched data is enhanced, it may be sorted in accordance with one or more filters.

Abstract: Methods and systems for processing and integrating data. A data file containing data describing a source transaction, associated with an identifier, is received. A type of the source transaction is identified based on a key indicator associated with the data file. The data contained in the data file is mapped to an object model based on the type of the source transaction identified. Output transaction objects are created by processing the data contained in the data file, mapped to the object model, using business rules. The business rules are selected based on a type of the object model. The output transaction objects are received and matched to the source transaction. A target system to receive the output transaction objects is identified based on the identifier associated with the data file.

Abstract: A method includes maintaining vehicle accident occurrence information, wherein the vehicle accident occurrence information includes accident location information, accident occurrence date information, and accident occurrence time information and identifying, based at least in part on the accident location information, one or more accident-prone locations. When a vehicle enters an area comprising one of the accident-prone locations, a notification is made that the vehicle has entered the area comprising one of the accident-prone locations. In addition, in response to a query, a visual representation of one of the accident-prone locations is displayed, along with accident occurrence date information and accident occurrence time information associated with the accident-prone location.

Abstract: Model metadata for each of a plurality of mathematical models is stored. Data describing two sets of models is received. Each of the sets identifies one or more models of the plurality of mathematical models. One of the sets comprises a transition-from set and one of the sets comprises a transition-to set. Data describing a launch date for commencing a transition from executing the model(s) in the transition-from set to executing the model(s) in the transition-to set is received. Data describing a transition period of time for the transition is received. The models in the transition-from set and in the transition-to set are executed during the transition period of time. An output of the execution of the model(s) in the transition-from set is combined with an output of the execution of the model(s) in the transition-to set. The output is stored in a database.

Abstract: Model metadata for each of a plurality of models is stored. The model metadata includes a statistical analysis technique identifier and one or more model input data identifiers. A request to execute a model is received. The request includes data identifying one of the plurality of models, and a model execution start date and end date. On the model execution start date, execution of the model associated with the model execution request is commenced. Outputs of the executed model are stored in a database. The outputs are associated with a model instance identifier, information describing a context for execution of the model, and model output type information. The outputs are retrieved, using the model instance identifier, for analysis.

Abstract: Model metadata for each of a plurality of models is stored. The model metadata includes a statistical analysis technique identifier and one or more model input data identifiers. A request to execute a model is received. The request includes data identifying one of the plurality of models, and a model execution start date and end date. On the model execution start date, execution of the model associated with the model execution request is commenced. Outputs of the executed model are stored in a database. The outputs are associated with a model instance identifier, information describing a context for execution of the model, and model output type information. The outputs are retrieved, using the model instance identifier, for analysis.

Abstract: Model metadata for each of a plurality of mathematical models is stored. Data describing two sets of models is received. Each of the sets identifies one or more models of the plurality of mathematical models. One of the sets comprises a transition-from set and one of the sets comprises a transition-to set. Data describing a launch date for commencing a transition from executing the model(s) in the transition-from set to executing the model(s) in the transition-to set is received. Data describing a transition period of time for the transition is received. The models in the transition-from set and in the transition-to set are executed during the transition period of time. An output of the execution of the model(s) in the transition-from set is combined with an output of the execution of the model(s) in the transition-to set. The output is stored in a database.

Abstract: A system and method for implementing a testing framework including a testing unit that receives test instructions; generates a mock consumer request for a web service from a web server and a mock provider response based on the test instructions; transmits the mock consumer request to a tested unit; receives a modified consumer request from the tested unit; and transmit the mock provider response to the tested unit.

Abstract: A method includes maintaining vehicle accident occurrence information, wherein the vehicle accident occurrence information includes accident location information, accident occurrence date information, and accident occurrence time information and identifying, based at least in part on the accident location information, one or more accident-prone locations. When a vehicle enters an area comprising one of the accident-prone locations, a notification is made that the vehicle has entered the area comprising one of the accident-prone locations. In addition, in response to a query, a visual representation of one of the accident-prone locations is displayed, along with accident occurrence date information and accident occurrence time information associated with the accident-prone location.

Abstract: A method includes maintaining vehicle accident occurrence information, wherein the vehicle accident occurrence information includes accident location information, accident occurrence date information, and accident occurrence time information and identifying, based at least in part on the accident location information, one or more accident-prone locations. When a vehicle enters an area comprising one of the accident-prone locations, a notification is made that the vehicle has entered the area comprising one of the accident-prone locations. In addition, in response to a query, a visual representation of one of the accident-prone locations is displayed, along with accident occurrence date information and accident occurrence time information associated with the accident-prone location.