Abstract: Techniques are described for automatically generating meta-alerts based on operational and security risk alert volumes for an entity. In particular, a central device receives entity alert information from other devices in a computer system of an enterprise business, which may have office branches that are each staffed by employees. The central device compares alert volumes of a given entity for a given period of time (e.g., a month) to one or more baseline thresholds determined based on the average alert volume of peer entities during the same period of time and the entity's own historical alert volumes to identify spikes or increases in the volume of alerts for the given entity. If the entity is trending high for the period of time, the central device generates a meta-alert to bring awareness to the relatively high volume of alerts identified for that entity.

Abstract: An example system configured to assess risk includes a server, an end-user system that generates an activity report in response to an employee performing an action via a computer device communicatively coupled to the end-user system, and a data warehouse that assigns a category to the activity report and populates a data table in a report database based the category of activity report. The server applies a rule to the populated data table. The rule is selected based on the category of the activity report. When the rule indicates that the action represents risky behavior, the server generates a current alert report. After performing validation checks on the current alert report, when the alert report passes the validation checks, the server transmits the current alert report in accordance with the rule. Additionally, the server stores a response to the alert report.

Abstract: Systems and methods for utilizing compliance drivers to conserve system resources are provided. Data that corresponds to a pre-determined historical period may be used. A method may extract issue information, regulations data, operations loss data, drivers data, pending activities data and/or pending examinations data. The method may perform a plurality of transformations on the issue information, the drivers data, the regulations data, and the operations loss. The transformations may apply enterprise compliance hierarchy information and transform the data associated with the issue information, the drivers data, the regulations data, and the operations loss data into quarterly information. The method may include performing transformations on issue information, regulations data, operations loss data and drivers data. The method may perform final transformations in order to either allocate resources to remediate a compliance trend, remediate a compliance projection, or correct a current compliance issue.

Abstract: Techniques are described for automatically generating meta-alerts based on operational and security risk alert volumes for an entity. In particular, a central device receives entity alert information from other devices in a computer system of an enterprise business, which may have office branches that are each staffed by employees. The central device compares alert volumes of a given entity for a given period of time (e.g., a month) to one or more baseline thresholds determined based on the average alert volume of peer entities during the same period of time and the entity's own historical alert volumes to identify spikes or increases in the volume of alerts for the given entity. If the entity is trending high for the period of time, the central device generates a meta-alert to bring awareness to the relatively high volume of alerts identified for that entity.

Abstract: Systems and methods for utilizing compliance drivers to conserve system resources are provided. Data that corresponds to a pre-determined historical period may be used. A method may extract issue information, regulations data, operations loss data, drivers data, pending activities data and/or pending examinations data. The method may perform a plurality of transformations on the issue information, the drivers data, the regulations data, and the operations loss. The transformations may apply enterprise compliance hierarchy information and transform the data associated with the issue information, the drivers data, the regulations data, and the operations loss data into quarterly information. The method may include performing transformations on issue information, regulations data, operations loss data and drivers data. The method may perform final transformations in order to either allocate resources to remediate a compliance trend, remediate a compliance projection, or correct a current compliance issue.

Abstract: Systems and methods for utilizing compliance drivers to conserve system resources are provided. Data that corresponds to a pre-determined historical period may be used. A method may extract issue information, regulations data, operations loss data, drivers data, pending activities data and/or pending examinations data. The method may perform a plurality of transformations on the issue information, the drivers data, the regulations data, and the operations loss. The transformations may apply enterprise compliance hierarchy information and transform the data associated with the issue information, the drivers data, the regulations data, and the operations loss data into quarterly information. The method may include performing transformations on issue information, regulations data, operations loss data and drivers data. The method may perform final transformations in order to either allocate resources to remediate a compliance trend, remediate a compliance projection, or correct a current compliance issue.

Abstract: Systems and methods for utilizing compliance drivers to conserve system resources are provided. Data that corresponds to a pre-determined historical period may be used. A method may extract issue information, regulations data, operations loss data, drivers data, pending activities data and/or pending examinations data. The method may perform a plurality of transformations on the issue information, the drivers data, the regulations data, and the operations loss. The transformations may apply enterprise compliance hierarchy information and transform the data associated with the issue information, the drivers data, the regulations data, and the operations loss data into quarterly information. The method may include performing transformations on issue information, regulations data, operations loss data and drivers data. The method may perform final transformations in order to either allocate resources to remediate a compliance trend, remediate a compliance projection, or correct a current compliance issue.

Abstract: Systems and methods for objective Deployment Failure risk assessments are provided, which may include fault trees. Systems and methods for the analysis of fault trees are provided as well. The risk assessments system may involve the development of a fault tree, assigning initial values and weights to the events within that fault tree, and the subsequent revision of those values and weights in an iterative fashion, including comparison to historical data. The systems for analysis may involve the assignment of well-ordered values to some events in a fault tree, and then the combination those values through the application of specialized, defined gates. The system may further involve the revision of specific gates by comparison to historical or empirical data.

Abstract: Systems and methods for objective Deployment Failure risk assessments are provided, which may include fault trees. Systems and methods for the analysis of fault trees are provided as well. The risk assessments system may involve the development of a fault tree, assigning initial values and weights to the events within that fault tree, and the subsequent revision of those values and weights in an iterative fashion, including comparison to historical data. The systems for analysis may involve the assignment of well-ordered values to some events in a fault tree, and then the combination those values through the application of specialized, defined gates. The system may further involve the revision of specific gates by comparison to historical or empirical data.

Abstract: Apparatus and methods for reducing infrastructure failure rates. The apparatus and methods may involve reduction of data complexity. The reduction may be based on the use of nonlinear analysis to derive representative variables, which may be multi-valued. Multi-valued variables may be consolidated. A model may be developed based on the values and relationships of the derived variables. The model may be applied to assess the risk involved in a prospective infrastructure change.

Abstract: Apparatus and methods for reducing infrastructure failure rates. The apparatus and methods may compile and store data related to the organizational segments associated with the approval and implementation of an infrastructure change. Variables may be derived from the data using a range of methods, and multiple variable values may be consolidated. A model may be developed based on the values and relationships of the derived variables. The model may be applied to assess the risk involved in a prospective infrastructure change.

Abstract: Apparatus and methods for reducing infrastructure failure rates. The apparatus and methods may compile and store data related to the physical devices and applications associated with an infrastructure change. Variables may be derived from the stored data using a range of methods and multiple variable values may be consolidated. A model may be developed based on the values and relationships of the derived variables. The model may be applied to assess the risk of a prospective infrastructure change.

Abstract: Apparatus and methods for reducing infrastructure failure rates. The apparatus and methods may compile and store data related to the physical devices and applications associated with an infrastructure change. Variables may be derived from the stored data using a range of methods and multiple variable values may be consolidated. A model may be developed based on the values and relationships of the derived variables. The model may be applied to assess the risk of a prospective infrastructure change. The risk may include an index that corresponds to the likelihood that the infrastructure change will lead to a failure. The model may predict the magnitude of a failure should the infrastructure change fail. The model may predict the expected failure impact based on the index and the failure magnitude.

Abstract: Apparatus and methods for reducing infrastructure failure rates. The apparatus and methods may involve reduction of data complexity. The reduction may be based on the use of nonlinear analysis to derive representative variables, which may be multi-valued. Multi-valued variables may be consolidated. A model may be developed based on the values and relationships of the derived variables. The model may be applied to assess the risk involved in a prospective infrastructure change.

Abstract: Apparatus and methods for reducing infrastructure failure rates. The apparatus and methods may compile and store data related to the physical devices and applications associated with an infrastructure change. Variables may be derived from the stored data using a range of methods and multiple variable values may be consolidated. A model may be developed based on the values and relationships of the derived variables. The model may be applied to assess the risk of a prospective infrastructure change.

Abstract: Apparatus and methods for reducing infrastructure failure rates. The apparatus and methods may compile and store data related to the organizational segments associated with the approval and implementation of an infrastructure change. Variables may be derived from the data using a range of methods, and multiple variable values may be consolidated. A model may be developed based on the values and relationships of the derived variables. The model may be applied to assess the risk involved in a prospective infrastructure change.

Abstract: A bundled mortgage package which includes several different features into a mortgage package, so that the process of actually obtaining a mortgage from a lender can be easier because the borrower's worries of the fees, charges, and other costs can be reduced or altogether eliminated since such fees charges and other costs may be combined, waived or otherwise resolved for the borrower is described. The lender may waive all lender fees, pay all 3rd party fees, and not require a lender's title policy. The lender may use the owner's title policy as the sole title insurance. A lender may not require mortgage insurance, waive fees associated with programs for borrower protection for involuntary unemployment or accidental death, guarantee that the loan will close within a certain period of time where the lender pays the borrower money if the loan doesn't close within the certain time period.

Abstract: A bundled mortgage package which includes several different features into a mortgage package, so that the process of actually obtaining a mortgage from a lender can be easier because the borrower's worries of the fees, charges, and other costs can be reduced or altogether eliminated since such fees charges and other costs may be combined, waived or otherwise resolved for the borrower is described. The lender may waive all lender fees, pay all 3rd party fees, and not require a lender's title policy. The lender may use the owner's title policy as the sole title insurance. A lender may not require mortgage insurance, waive fees associated with programs for borrower protection for involuntary unemployment or accidental death, guarantee that the loan will close within a certain period of time where the lender pays the borrower money if the loan doesn't close within the certain time period.