Abstract: A system for detecting fraudulent activity using account analytics obtains an interaction record for an interaction between a remote device and a user account via an interaction channel, where the interaction is an attempt to access the user account, obtains historical data relating to the user account and the interaction channel that includes one or more historical interaction records relating to the user account and activity records relating to the interaction channel, calculates a threat score for the user account based on the interaction record and the one or more historical interaction records that indicates a likelihood that the user account is subject to fraudulent activity, generates a database record based on the interaction record that includes the threat score, and initiates corrective action if the threat score exceeds a predetermined threshold.

Abstract: A system for a graphical user interface for fraud detection for a call center system includes a processor and a visual display in communication with the processor. The processor causes the visual display to present an identifier corresponding to a communication received; a graphical representation of a threat risk associated with the identifier; a numeric score associated with the threat risk, wherein the numeric score is a weighted score based on a plurality of predetermined factors updated substantially continuously.

Abstract: Systems and methods are provided to stop both external and internal fraud, ensure correct actions are being followed, and information is available to fraud teams for investigation. The system includes components that can address: 1) behavioral analytics (ANI reputation, IVR behavior, account activity)—this gives a risk assessment event before a call gets to an agent; 2) fraud detection—the ability to identify, in real time, if a caller is part of a fraudster cohort' and alert the agent and escalate to the fraud team; 3) identity authentication—the ability to identify through natural language if the caller is who they say they are; and 4) two factor authentication—the ability to send a text message to the caller and automatically process the response and create a case in the event of suspected fraud.

Abstract: A user interface for a fraud detection application includes a visual display; a plurality of panes displayed on the visual display, each pane including an identifier corresponding to a communication received; a graphical representation of a threat risk associated with the identifier; a numeric score associated with the threat risk, wherein the numeric score is a weighted score based on a plurality of predetermined factors updated substantially continuously. The graphical representation may include a status bar indicative of a threat risk associated with the identifier, the threat risk provided by the fraud detection algorithm and based on a weighted score. Each pane may include additional information about the identifier, such as a number of accounts accessed or attempted to be accessed associated with the identifier; a number of days the identifier has been active; a type of channel associated with the identifier; and a number of communications initiated by the identifier over a predetermined period of time.

Abstract: Systems and methods are provided to stop both external and internal fraud, ensure correct actions are being followed, and information is available to fraud teams for investigation. The system includes components that can address: 1) behavioral analytics (ANI reputation, IVR behavior, account activity)—this gives a risk assessment event before a call gets to an agent; 2) fraud detection—the ability to identify, in real time, if a caller is part of a fraudster cohort' and alert the agent and escalate to the fraud team; 3) identity authentication—the ability to identify through natural language if the caller is who they say they are; and 4) two factor authentication—the ability to send a text message to the caller and automatically process the response and create a case in the event of suspected fraud.

Abstract: Systems and methods are provided to stop both external and internal fraud, ensure correct actions are being followed, and information is available to fraud teams for investigation. The system includes components that can address: 1) behavioral analytics (ANI reputation, IVR behavior, account activity)—this gives a risk assessment event before a call gets to an agent; 2) fraud detection—the ability to identify, in real time, if a caller is part of a fraudster cohort? and alert the agent and escalate to the fraud team; 3) identity authentication—the ability to identify through natural language if the caller is who they say they are; and 4) two factor authentication—the ability to send a text message to the caller and automatically process the response and create a case in the event of suspected fraud.

Abstract: Systems and methods are provided to stop both external and internal fraud, ensure correct actions are being followed, and information is available to fraud teams for investigation. The system includes components that can address: 1) behavioral analytics (ANI reputation, IVR behavior, account activity)—this gives a risk assessment event before a call gets to an agent; 2) fraud detection—the ability to identify, in real time, if a caller is part of a fraudster cohort? and alert the agent and escalate to the fraud team; 3) identity authentication—the ability to identify through natural language if the caller is who they say they are; and 4) two factor authentication—the ability to send a text message to the caller and automatically process the response and create a case in the event of suspected fraud.

Abstract: A user interface for a fraud detection application includes a visual display; a plurality of panes displayed on the visual display, each pane including an identifier corresponding to a communication received; a graphical representation of a threat risk associated with the identifier; a numeric score associated with the threat risk, wherein the numeric score is a weighted score based on a plurality of predetermined factors updated substantially continuously. The graphical representation may include a status bar indicative of a threat risk associated with the identifier, the threat risk provided by the fraud detection algorithm and based on a weighted score. Each pane may include additional information about the identifier, such as a number of accounts accessed or attempted to be accessed associated with the identifier; a number of days the identifier has been active; a type of channel associated with the identifier; and a number of communications initiated by the identifier over a predetermined period of time.