Abstract: Disclosed are systems and methods for robocall steering over voice-hosted traffic networks. The disclosed framework provides novel systems and methods for increasing the accuracy and efficiency in tracking, identifying, blocking and preventing robocalls and robocallers. The disclosed systems and methods provide mechanisms for identifying and removing unwanted voice traffic from networks. The disclosed systems and methods analyze voice traffic over a predetermined period of time (e.g., 1 day or 30 days, for example), and leverage this information into a “know your customer” (KYC) score. This score enables incoming calls to be routed, controlled and/or blocked as they are communicated over voice networks.

Abstract: Disclosed are systems and methods for robocall steering over voice-hosted traffic networks. The disclosed framework provides novel systems and methods for increasing the accuracy and efficiency in tracking, identifying, blocking and preventing robocalls and robocallers. The disclosed systems and methods provide mechanisms for identifying and removing unwanted voice traffic from networks. The disclosed systems and methods analyze voice traffic over a predetermined period of time (e.g., 1 day or 30 days, for example), and leverage this information into a “know your customer” (KYC) score. This score enables incoming calls to be routed, controlled and/or blocked as they are communicated over voice networks.

Abstract: Disclosed are systems and methods for robocall steering over voice-hosted traffic networks. The disclosed framework provides novel systems and methods for increasing the accuracy and efficiency in tracking, identifying, blocking and preventing robocalls and robocallers. The disclosed systems and methods provide mechanisms for identifying and removing unwanted voice traffic from networks. The disclosed systems and methods analyze voice traffic over a predetermined period of time (e.g., 1 day or 30 days, for example), and leverage this information into a “know your customer” (KYC) score. This score enables incoming calls to be routed, controlled and/or blocked as they are communicated over voice networks.

Abstract: A system, method and computer program product for processing event records. The present invention includes a detection layer, an analysis layer, an expert systems layer and a presentation layer. The layered system includes a core infrastructure and a configurable, domain-specific implementation. The detection layer employs one or more detection engines, such as, for example, a rules-based thresholding engine and a profiling engine. The detection layer can include an AI-based pattern recognition engine for analyzing data records, for detecting new and interesting patterns and for updating the detection engines to insure that the detection engines can detect the new patterns. In one embodiment, the present invention is implemented as a telecommunications fraud detection system. When fraud is detected, the detection layer generates alarms which are sent to the analysis layer. The analysis layer filters and consolidates the alarms to generate fraud cases.

Abstract: A fraud management system is configured to store rules for detecting fraud. The fraud management system is further configured to receive a transaction involving a consumer and a merchant; obtain network security information associated with malicious activity in a voice network or a data network, where the network security information indicates that the consumer has been involved in malicious activity in the voice network or in the data network; select a subset of rules based on the network security information and information associated with the transaction, the merchant, or the consumer; process the transaction using the subset of rules to generate alarms; process the alarms to generate a fraud score for the transaction; and output information regarding the fraud score to the merchant to assist the merchant in determining whether to accept, deny, or fulfill the transaction.

Abstract: An approach provides detection of unauthorized use of data services. The number of data calls for access to a data network is tracked over a predetermined time period, and the cumulative duration of the data calls is determined. Thereafter, a determination is made as to whether the number of the data calls and the cumulative duration satisfy, respectively, a first threshold and a second threshold. A potential fraudulent use of the account is determined, if the thresholds are satisfied.

Abstract: An approach provides fraud detection in support of data communication services. A list of single-event attributes (e.g., hot or cold attributes) is generated and includes a network address of an end user host originating a data call or a calling party identification (e.g., Automatic Number Identification (ANI) or an originating Calling Line Identification (CLI)) for network access, wherein entries of the list specify values of the hot attributes. An attribute value associated with the data call is compared with the entries. A fraud alert is generated if the attribute value matches one of the entries.

Abstract: A fraud management system is configured to store rules for detecting fraud. The fraud management system is configured to: receive a transaction involving a consumer and a merchant; select a set of the rules based on information associated with the transaction, information associated with the consumer, or information associated with the merchant; process the transaction, in parallel, using the selected rules to generate a set of alarms; group the alarms, into groups, based on information associated with the transaction; analyze the groups to generate a fraud score; and output information regarding the fraud score to the merchant to notify the merchant whether the transaction is potentially fraudulent.

Abstract: A fraud management system is configured to store rules for detecting fraud. The fraud management system is further configured to receive a transaction involving a consumer and a merchant; obtain network security information associated with malicious activity in a voice network or a data network, where the network security information indicates that the consumer has been involved in malicious activity in the voice network or in the data network; select a subset of rules based on the network security information and information associated with the transaction, the merchant, or the consumer; process the transaction using the subset of rules to generate alarms; process the alarms to generate a fraud score for the transaction; and output information regarding the fraud score to the merchant to assist the merchant in determining whether to accept, deny, or fulfill the transaction.

Abstract: A fraud management system is configured to receive a transaction from a merchant; select rules to use to process the transaction; process the transaction using the selected rules to generate a set of alarms; and generate an alarm score for each of the alarms. The fraud management system is further configured to combine the alarms with alarms from one or more other transactions to form a combined set of alarms; sorting alarms, in the combined set of alarms, into groups based on attributes of the transaction; generate a group score, for each group, based on at least one of the alarm scores for at least one alarm in the group; generate a fraud score, for the transaction, based on one or more of the group scores; and output information regarding the fraud score to the merchant to notify the merchant whether the transaction is potentially fraudulent.

Abstract: An approach provides detection of unauthorized use of data services. A determination is made as to whether connections supporting remote access to a data network are completed. The number of completed connections associated with a selected attribute is tracked over a time period. It is then determined whether the number of completed connections satisfies a connection frequency threshold. A fraud alert is generated if the connection frequency threshold is satisfied.

Abstract: An approach provides fraud detection in support of data communication services. A usage pattern associated with a particular account for remote access to a data network is monitored. The usage pattern is compared with a reference pattern specified for the account. A fraud alert is selectively generated based on the comparison.

Abstract: An approach provides detection of unauthorized use of data services. A determination is made as to whether connections supporting remote access to a data network are completed. The number of completed connections associated with a selected attribute is tracked over a time period. It is then determined whether the number of completed connections satisfies a connection frequency threshold. A fraud alert is generated if the connection frequency threshold is satisfied.

Abstract: An approach provides fraud detection in support of data communication services. A list of single-event attributes (e.g., hot or cold attributes) is generated and includes a network address of an end user host originating a data call or a calling party identification (e.g., Automatic Number Identification (ANI) or an originating Calling Line Identification (CLI)) for network access, wherein entries of the list specify values of the hot attributes. An attribute value associated with the data call is compared with the entries. A fraud alert is generated if the attribute value matches one of the entries.

Abstract: An approach provides fraud detection in support of data communication services. A threshold corresponding to a geographic location is set. The threshold corresponds to duration of a call supporting data communications. It is determined whether the call duration exceeds the threshold. A fraud alert is generated if the monitored call duration exceeds the threshold.

Abstract: An approach provides detection of unauthorized use of data services. A fraud case is created for a data call that is determined to be potentially fraudulent based on a fraud alert. A fraud score is determined for the case according to the fraud alert. The fraud score is adjusted according to adjustment criteria including an intermediate network involved with the data call, and an originating country of the data call.

Abstract: An approach provides fraud detection in support of data communication services. A list of single-event attributes (e.g., hot or cold attributes) is generated and includes a network address of an end user host originating a data call or a calling party identification (e.g., Automatic Number Identification (ANI) or an originating Calling Line Identification (CLI)) for network access, wherein entries of the list specify values of the hot attributes. An attribute value associated with the data call is compared with the entries. A fraud alert is generated if the attribute value matches one of the entries.

Abstract: A system, method and computer program product for processing event records. The present invention includes a detection layer, an analysis layer, an expert systems layer and a presentation layer. The layered system includes a core infrastructure and a configurable, domain-specific implementation. The detection layer employs one or more detection engines, such as, for example, a rules-based thresholding engine and a profiling engine. The detection layer can include an AI-based pattern recognition engine for analyzing data records, for detecting new and interesting patterns and for updating the detection engines to insure that the detection engines can detect the new patterns. In one embodiment, the present invention is implemented as a telecommunications fraud detection system. When fraud is detected, the detection layer generates alarms which are sent to the analysis layer. The analysis layer filters and consolidates the alarms to generate fraud cases.

Abstract: A system, method and computer program product for processing event records. The present invention includes a detection layer, an analysis layer, an expert systems layer and a presentation layer. The layered system includes a core infrastructure and a configurable, domain-specific implementation. The detection layer employs one or more detection engines, such as, for example, a rules-based thresholding engine and a profiling engine. The detection layer can include an AI-based pattern recognition engine for analyzing data records, for detecting new and interesting patterns and for updating the detection engines to insure that the detection engines can detect the new patterns. In one embodiment, the present invention is implemented as a telecommunications fraud detection system. When fraud is detected, the detection layer generates alarms which are sent to the analysis layer. The analysis layer filters and consolidates the alarms to generate fraud cases.

Abstract: A data processing system program to develop, train, and implement a neural network for identifying customers who represent a bad debt risk is disclosed. A feature vector is applied to a neural network to generate outputs that approximate the relative likelihood that customers who are the subjects of the records used to generate the feature vector will be a bad debt risk. Statistical values relating categorical attributes of the customers to the likelihood of their becoming a bad debt risk are substituted for the categorical attributes, and the attributes are normalized before the feature vector is applied to the network. In one embodiment the customers are customers of a long distance service provider.