Abstract: A system that aggregates client data and cyber indicators to authenticate a client is provided. The system receives a request to access a financial account of the client, and retrieves a client profile. The client profile includes an aggregation of data into a plurality of data indicators. An optimal number of data indicators is determined based on an initial threshold inquiry regarding the request, with the optimal number of data indicators being determined based on a phone requesting the access to the financial account. A risk score is generated based on a weighting for each of the plurality of data indicators included within the optimal number, with the weighting representing a confidence in the accuracy of each of those data indicators. Access to predetermined actions by the client is granted based on the risk score.

Abstract: The invention relates to a method and system that aggregates client data and cyber indicators to authenticate a client. The system comprises: a computer server comprising at least one computer processor and coupled to the memory, programmed to: receive, via an electronic input, an authorization request from a requester for access to an account; identify a client identifier associated with the authorization request; using the client identifier, retrieve, from the memory, a client profile, wherein the client profile is based on an aggregation of client data, client device data, claims data and cyber data; generate a risk score based on the aggregated combination of the client data, client device data, claims data and cyber data to determine whether the requester is authenticated to access the account; and automatically apply an authentication determination to the authorization request.

Abstract: The invention relates to database abstraction and data linkage. According to an embodiment of the present invention, the invention takes a variety of attributes (e.g., names, IP address, device identifiers, addresses, phone numbers, account numbers, etc.) and returns the online activity, demographic data, account data and/or other activity, events and data associated with that attribute. The tool may then iterate over each attribute and return a network of connections having multiple degrees of association. The innovative tool may be linked to known bad actor data, and perform automated searches on this data to proactively alert potentially fraudulent activity. The tool may also be developed to add attributes and apply machine learning to the associations to more intelligently describe the returned network. Further, the tool may be developed to describe larger networks having multiple degrees of connections.

Abstract: The invention relates to a method and system that combines payment data and cyber fraud indicators to identify potential fraud in payment requests from a client. The system comprises: a memory that stores and maintains a list of known fraud characteristics and cyber fraud indicators; and a computer processor, coupled to the memory, programmed to: receive, via an electronic input, a payment instruction from the client; identify one or more cyber fraud indicators associated with the payment instruction; apply payment decisioning to merge the one or more cyber fraud indicators to the payment instruction; generate a risk score based on the payment decisioning to determine whether the payment instruction should be executed; and automatically apply the payment decisioning to the payment instruction.

Abstract: The invention relates to database abstraction and data linkage. According to an embodiment of the present invention, the invention takes a variety of attributes (e.g., names, IP address, device identifiers, addresses, phone numbers, account numbers, etc.) and returns the online activity, demographic data, account data and/or other activity, events and data associated with that attribute. The tool may then iterate over each attribute and return a network of connections having multiple degrees of association. The innovative tool may be linked to known bad actor data, and perform automated searches on this data to proactively alert potentially fraudulent activity. The tool may also be developed to add attributes and apply machine learning to the associations to more intelligently describe the returned network. Further, the tool may be developed to describe larger networks having multiple degrees of connections.

Abstract: The invention relates to a method and system that aggregates client data and cyber indicators to authenticate a client. The system comprises: a computer server comprising at least one computer processor and coupled to the memory, programmed to: receive, via an electronic input, an authorization request from a requester for access to an account; identify a client identifier associated with the authorization request; using the client identifier, retrieve, from the memory, a client profile, wherein the client profile is based on an aggregation of client data, client device data, claims data and cyber data; generate a risk score based on the aggregated combination of the client data, client device data, claims data and cyber data to determine whether the requester is authenticated to access the account; and automatically apply an authentication determination to the authorization request.

Abstract: The invention relates to database abstraction and data linkage. According to an embodiment of the present invention, the invention takes a variety of attributes (e.g., names, IP address, device identifiers, addresses, phone numbers, account numbers, etc.) and returns the online activity, demographic data, account data and/or other activity, events and data associated with that attribute. The tool may then iterate over each attribute and return a network of connections having multiple degrees of association. The innovative tool may be linked to known bad actor data, and perform automated searches on this data to proactively alert potentially fraudulent activity. The tool may also be developed to add attributes and apply machine learning to the associations to more intelligently describe the returned network. Further, the tool may be developed to describe larger networks having multiple degrees of connections.

Abstract: The invention relates to a method and system that aggregates client data and cyber indicators to authenticate a client. The system comprises: a computer server comprising at least one computer processor and coupled to the memory, programmed to: receive, via an electronic input, an authorization request from a requester for access to an account; identify a client identifier associated with the authorization request; using the client identifier, retrieve, from the memory, a client profile, wherein the client profile is based on an aggregation of client data, client device data, claims data and cyber data; generate a risk score based on the aggregated combination of the client data, client device data, claims data and cyber data to determine whether the requester is authenticated to access the account; and automatically apply an authentication determination to the authorization request.

Abstract: The invention relates to a method and system that analyzes domain names for potential fraud. The system comprises: a memory that stores and maintains a list of known domain names associated with an entity; and a computer processor, coupled to the memory, programmed to: receive, via an electronic input, one or more registered domain names from a registration source; access the list of known domain names; apply logic rules to determine visually similar domain names by comparing the one or more registered domain names to the list of known domain names; identify a relevant recipient based on the visually similar domain name; and generate and transmit, via a communication interface, a message to the recipient, the message comprising the visually similar domain name and associated information relevant to the domain name registration.

Abstract: The invention relates to a method and system that combines payment data and cyber fraud indicators to identify potential fraud in payment requests from a client. The system comprises: a memory that stores and maintains a list of known fraud characteristics and cyber fraud indicators; and a computer processor, coupled to the memory, programmed to: receive, via an electronic input, a payment instruction from the client; identify one or more cyber fraud indicators associated with the payment instruction; apply payment decisioning to merge the one or more cyber fraud indicators to the payment instruction; generate a risk score based on the payment decisioning to determine whether the payment instruction should be executed; and automatically apply the payment decisioning to the payment instruction.

Abstract: The invention relates to a method and system that aggregates client data and cyber indicators to authenticate a client. The system comprises: a computer server comprising at least one computer processor and coupled to the memory, programmed to: receive, via an electronic input, an authorization request from a requester for access to an account; identify a client identifier associated with the authorization request; using the client identifier, retrieve, from the memory, a client profile, wherein the client profile is based on an aggregation of client data, client device data, claims data and cyber data; generate a risk score based on the aggregated combination of the client data, client device data, claims data and cyber data to determine whether the requester is authenticated to access the account; and automatically apply an authentication determination to the authorization request.

Abstract: The invention relates to database abstraction and data linkage. According to an embodiment of the present invention, the invention takes a variety of attributes (e.g., names, IP address, device identifiers, addresses, phone numbers, account numbers, etc.) and returns the online activity, demographic data, account data and/or other activity, events and data associated with that attribute. The tool may then iterate over each attribute and return a network of connections having multiple degrees of association. The innovative tool may be linked to known bad actor data, and perform automated searches on this data to proactively alert potentially fraudulent activity. The tool may also be developed to add attributes and apply machine learning to the associations to more intelligently describe the returned network. Further, the tool may be developed to describe larger networks having multiple degrees of connections.