Abstract: The present disclosure relates to systems, methods, and computer readable media for detecting periodic sequences of events. A computer-implemented method may include collecting processing times and values associated with each of a plurality of events. The method may also include assigning each of the plurality of events to at least one of a plurality of time phases, the plurality of time phases forming a period characteristic of the plurality of events. The method may also include grouping the events in each of the plurality of time phases into one or more clusters, based on the respective values associated with the events. The method may also include determining a periodic sequence of events based on the one or more clusters. The method may further include recording the periodic sequence of events in a database of periodic sequences.

Abstract: Systems and methods for presenting fraud detection information are presented. In one example, a computer system analyzes empirical data to detect potentially fraudulent activity and alerts users of the potentially fraudulent activity via a fraud detection user interface. The fraud detection user interface determines a set of user interface components to suitable to present the potentially fraudulent activity and presents facts associated with the potentially fraudulent activity to a user for further analysis and investigation.

Abstract: Systems and methods for presenting fraud detection information are presented. In one example, a computer system analyzes empirical data to detect potentially fraudulent activity and alerts users of the potentially fraudulent activity via a fraud detection user interface. The fraud detection user interface determines a set of user interface components to suitable to present the potentially fraudulent activity and presents facts associated with the potentially fraudulent activity to a user for further analysis and investigation.

Abstract: The present disclosure relates to systems, methods, and computer readable media for detecting periodic sequences of events. A computer-implemented method may include collecting processing times and values associated with each of a plurality of events. The method may also include assigning each of the plurality of events to at least one of a plurality of time phases, the plurality of time phases forming a period characteristic of the plurality of events. The method may also include grouping the events in each of the plurality of time phases into one or more clusters, based on the respective values associated with the events. The method may also include determining a periodic sequence of events based on the one or more clusters. The method may further include recording the periodic sequence of events in a database of periodic sequences.

Abstract: Systems and methods for presenting fraud detection information are presented. In one example, a computer system analyzes empirical data to detect potentially fraudulent activity and alerts users of the potentially fraudulent activity via a fraud detection user interface. The fraud detection user interface determines a set of user interface components to suitable to present the potentially fraudulent activity and presents facts associated with the potentially fraudulent activity to a user for further analysis and investigation.

Abstract: A systems and methods are described detect fraud in existing logs of raw data. There can be several disparate logs, each including data of disparate data types and generated by different and possibly unrelated software enterprise applications. The fraud management system aggregates and organizes the raw log data, extends the raw data with reference data, archives the data in a manner that facilitates efficient access and processing of the data, allows for investigation of potentially fraudulent usage scenarios, and uses the results of the investigation to identify patterns of data that correspond to correspond to high risk usage scenarios and/or process steps. In subsequent processing, archived data can be compared against the identified patterns corresponding to high risk usage scenarios to detect matches, and the invention thereby automatically detects high risk usage scenarios and issues appropriate alerts and reports.

Abstract: Described herein are methods and systems for registering a phone number as a payment facilitator. The phone number can be registered through a user's Bill Pay account, which is associated to the user's financial account. The user can specify the types of purchases that can be made using the phone number and request that a merchant processing a payment using the phone number convey customized details regarding the purchase. Purchase details associated with a purchase can then be provided to the consumer by the merchant. Also described herein are methods and systems for processing a payment using a phone number. The payment can be processed, in part, by a payment processor providing a consumer with a Bill Pay account associated with the consumer's financial account. The payment can be processed without the use of a credit card network and, as a result, without incurring unnecessary Interchange fees.

Abstract: Methods and systems are disclosed for implementing data matching techniques. In some embodiments, methods and systems may be implemented for filtering a received record associated with at least one record attribute against an entity record. The methods and systems comprise, for example, applying a record attribute weight to the at least one record attribute associated with the received record, performing at least one matching technique that compares the at least one record attribute of the received record against the entity record, wherein the at least one matching technique is associated with a corresponding matching technique multiplier, calculating a matching score based on a result of the at least one matching technique and the multiplier associated with the at least one matching technique, and comparing the matching score to a threshold to determine whether the received record represents a suspect entity.

Abstract: A systems and methods are described detect fraud in existing logs of raw data. There can be several disparate logs, each including data of disparate data types and generated by different and possibly unrelated software enterprise applications. The fraud management system aggregates and organizes the raw log data, archives the data in a manner that facilitates efficient access and processing of the data, allows for investigation of potentially fraudulent usage scenarios, and uses the results of the investigation to identify patterns of data that correspond to correspond to high risk usage scenarios and/or process steps. In subsequent processing, archived data can be compared against the identified patterns corresponding to high risk usage scenarios to detect matches, and the invention thereby automatically detects high risk usage scenarios and issues appropriate alerts and reports.

Abstract: A systems and methods are described detect fraud in existing logs of raw data. There can be several disparate logs, each including data of disparate data types and generated by different and possibly unrelated software enterprise applications. The fraud management system aggregates and organizes the raw log data, extends the raw data with reference data, archives the data in a manner that facilitates efficient access and processing of the data, allows for investigation of potentially fraudulent usage scenarios, and uses the results of the investigation to identify patterns of data that correspond to correspond to high risk usage scenarios and/or process steps. In subsequent processing, archived data can be compared against the identified patterns corresponding to high risk usage scenarios to detect matches, and the invention thereby automatically detects high risk usage scenarios and issues appropriate alerts and reports.

Abstract: A systems and methods are described detect fraud in existing logs of raw data. There can be several disparate logs, each including data of disparate data types and generated by different and possibly unrelated software enterprise applications. The fraud management system aggregates and organizes the raw log data, extends the raw data with reference data, archives the data in a manner that facilitates efficient access and processing of the data, allows for investigation of potentially fraudulent usage scenarios, and uses the results of the investigation to identify patterns of data that correspond to correspond to high risk usage scenarios and/or process steps. In subsequent processing, archived data can be compared against the identified patterns corresponding to high risk usage scenarios to detect matches, and the invention thereby automatically detects high risk usage scenarios and issues appropriate alerts and reports.

Abstract: Methods and systems are disclosed for implementing data matching techniques. In some embodiments, methods and systems may be implemented for filtering a received record associated with at least one record attribute against an entity record. The methods and systems comprise, for example, applying a record attribute weight to the at least one record attribute associated with the received record, performing at least one matching technique that compares the at least one record attribute of the received record against the entity record, wherein the at least one matching technique is associated with a corresponding matching technique multiplier, calculating a matching score based on a result of the at least one matching technique and the multiplier associated with the at least one matching technique, and comparing the matching score to a threshold to determine whether the received record represents a suspect entity.

Abstract: Systems and methods for presenting fraud detection information are presented. In one example, a computer system analyzes empirical data to detect potentially fraudulent activity and alerts users of the potentially fraudulent activity via a fraud detection user interface. The fraud detection user interface determines a set of user interface components to suitable to present the potentially fraudulent activity and presents facts associated with the potentially fraudulent activity to a user for further analysis and investigation.

Abstract: A method and system for analyzing and optimizing the distribution of work from a plurality of queues includes storing historical data in a database. The historical data may include sets of different types of data items, each of the data items having an associated monetary value. The method further includes assigning a relative score to each of the data items within the sets and calculating a cumulative monetary value for each relative score, the cumulative monetary value being the summation of the monetary values for all items having relative scores up to and including the relative score. The method further includes determining the maximum cumulative monetary value calculated and its corresponding relative score. In one embodiment, the corresponding relative score is then used to determine which items to work in a set of queues that has not yet been worked.

Abstract: Systems and methods for presenting fraud detection information are presented. In one example, a computer system analyzes empirical data to detect potentially fraudulent activity and alerts users of the potentially fraudulent activity via a fraud detection user interface. The fraud detection user interface determines a set of user interface components to suitable to present the potentially fraudulent activity and presents facts associated with the potentially fraudulent activity to a user for further analysis and investigation.

Abstract: Systems and methods for presenting fraud detection information are presented. In one example, a computer system analyzes empirical data to detect potentially fraudulent activity and alerts users of the potentially fraudulent activity via a fraud detection user interface. The fraud detection user interface determines a set of user interface components to suitable to present the potentially fraudulent activity and presents facts associated with the potentially fraudulent activity to a user for further analysis and investigation.