Methods and apparatus for call traffic anomaly mitigation are described herein. One or more embodiments include receiving a scoring request including a telephone number associated with a telephone call at a scoring device from a call processing entity, receiving a violator list of telephone numbers and their corresponding severity values at the scoring device from an anomaly analyzer, determining a severity value associated with the telephone number by performing a lookup operation in the violator list, performing a random simulation using the severity value as a probability to determine an indicator value, and inputting the indicator value into a model to determine a call reputation score.

Methods and systems described in this disclosure allow customers to personalize their phone experience when calling into an organization. In some embodiments, customers who may benefit from this service are identified based on the content of the customer's previous or current phone calls to the organization. The identified customers may be invited to enroll and to provide preferences for a customized Interactive Voice Response experience. In some embodiments, the customer can elect to hear the balances of one or more of his accounts without going through a phone menu or asking a representative to look up the relevant amounts. Once enrolled, when the customer dials into the organization and upon successful authentication, the organization proactively states the customer's account balances with no further customer request.

A method for handling call originations is provided. The method includes sending origination information from a mobile device to an application server in an enterprise network using Short Message Service (SMS) and determining whether a hotline feature is present in a subscriber profile associated with the mobile device. Data is then routed from the mobile device to a predetermined destination based on the hotline feature.

A computer-implemented method for correlating payment service submissions and data captured from a call stream is described herein. The method comprises receiving data captured from a call stream by a data capture device; receiving a payment service submission comprising an identifier; determining an association between the identifier and the call stream; and replacing the identifier in the payment service submission with the data captured from the call stream associated with the identifier.

One example method of operation may include collecting call metric data over a predefined period of time for identified calls, querying the call metric data to identify whether one or more call filtering criteria parameters require changes, determining one or more call filtering criteria parameters require changes based on a deviation from one or more expected call metric data values included in the call metric data, modifying one or more of the call filtering criteria parameters, and updating an active call scam model stored on a call processing server based on the one or more call filtering parameters.

To provide a called one with information on the caller, a reference to a resource containing real-time or near-real-time information relating to the caller, or information deduced using the real-time or near-real-time information, or the real-time or near-real-time information, or the information deduced using the real-time or near-real-time information, is transmitted with a connection establishment request, and the information in the resource or the received information is displayed to the called one before the requested connection is established so that the called one can make a decision whether or not to answer the call.

A method, computer system, and a computer program product for filtering a phone call are provided. An incoming phone call to a phone is detected. Call metadata from the incoming phone call is received. The call metadata is compared to entries of a learned relationship filter. The entries of the learned relationship filter are obtained by monitoring behavior of a phone user on the phone during previous calls to the phone and application usage on the phone so that learned relationships to the phone user are identified and saved. The learned relationship filter provides a filtering response. The filtering response is performed to the incoming phone call.

Disclosed herein are systems, methods, and non-transitory computer-readable storage media for collecting call data, feeding call data to applications, and providing advanced call features.

The disclosed techniques enable selective forwarding and blocking of messages directed to an alias email address based on a whitelist, as well as email alerts triggered by emails from unauthorized senders. More generally, the disclosed techniques enable an enterprise system to store contact emails for users (i.e., alias email addresses) while avoiding storing and managing personal email addresses for the user. For example, the enterprise system may forward personal email addresses to an aliasing server configured to generate alias email addresses based on the personal email addresses. The aliasing server may operate as a “middle man” that receives emails directed to the alias email addresses and that forwards the emails to the personal email addresses (when appropriate). The enterprise system may store and maintain the alias email addresses in lieu of the personal email addresses.

A system, server, and method of DTMF detection in a VoIP network.