A method and a User Equipment, UE (120) for detecting that the UE has received a fraudulent missed call, e.g. from a non-legitimate device (150). When receiving a missed call which is ended before a user of the UE has answered the incoming call, the UE determines the duration of the missed call, and indicates, e.g. to a user of the UE, the 5 duration of the missed call. The missed call may be determined as potentially fraudulent if the duration of the missed call is below or equal to a predetermined threshold.

Described are techniques including a computer-implemented method of maintaining a list of newly assigned phone numbers. The method further comprises intermittently removing phone numbers from the list of newly assigned phone numbers. The method further comprises determining that a newly assigned phone number initiates a number of calls per unit time that exceeds a threshold number of calls per unit time. The method further comprises automatically flagging the newly assigned phone number as a possible robocaller.

This document discusses, among other things, limiting contact to a networked contact center that is a host to multiple tenants. In an example embodiment, a communication is received by a networked contact center. In determining whether to allow the communication to reach contact center resources, a contact rate value may be examined. The contact rate value may represent an allowable quantity of contact within a time interval. For some example embodiments, a determination of whether the network contact center is to accept or reject the communication is made based on the contact rate value.

The disclosure provides a processing method for a priority notification of an incoming call and a mobile device. The processing method for a priority notification of an incoming call is applied to a mobile device. The processing method includes: receiving an incoming call signal and generating a notification signal when a plurality of trigger conditions is met. The trigger conditions include: determining, according to the incoming call signal, that a repeated call is within a first preset time or a time interval between repeated calls is less than a second preset time, that a caller number corresponding to the incoming call signal is in a priority contact list, and that the mobile device is in a preset use situation. Then, a mandatory reminder mode is activated according to the notification signal to notify a user.

A dialing list comprising call records can be processed by a call handling component(s) in a contact center in various dialing modes. A call record may be processed to originate a voice call, where the agent manually dials the call as a voice telephone call. In another embodiment, one or more call records can be processed to originate a SMS text call or group text call, where the agent also determines when the call(s) originates. The agent is presented with a graphical user interface tailored to the dialing mode. The dialing mode used may be defined by the dialing list the call record is retrieved from, information from within the call record itself, application of a rule, or input from the agent. The dialing mode may be altered under certain conditions. When the call is originated, various compliance oriented tests, including calling windows and call attempts, are performed.

A method for detecting a denial of service attach on a call center, the method including automated means for detecting at least one anomaly in calls made to the call center from at least one source, determining if a detected anomaly has a match in a historical file of previously detected anomalies, and filtering calls received from the at least one source if the detected anomaly does not have a match in the historical file of previously detected anomalies.

Disclosed are systems and methods for forecasting inbound telecommunications, and more particularly, for analyzing real-time and historical call center data, and applying a forecasting model to said data in order to predict inbound call volume. Additionally, tools are disclosed for manipulating call center data and generating visual representations of metrics pertaining to forecasting call center data via a dashboard.

Certain exemplary aspects of the present disclosure are directed to a data-communications system including a networked contact center for which, in an example embodiment, a communication is received by a networked contact center. In determining whether to allow the communication to reach contact center resources, a contact rate value is examined. The contact rate value may represent an allowable quantity of contact within a time interval. For some example embodiments, a determination of whether the network contact center is to accept or reject the communication is made based on the contact rate value.

A method and apparatus of maintaining time information for a multi-tasking customer service agent is disclosed. One example method of operation may include maintaining time information allocated to a plurality of tasks. The method may include receiving a first task and starting a first timer at a computing device corresponding to the beginning of work performed on the first task. The method may also include receiving a second task and starting a second timer different from the first timer, which corresponds to the beginning of work performed on the second task. The method may further include transferring a total time allocation record representing a total time counted by the first timer and a total time counted by the second timer to a data record stored in memory, wherein the data record associates the total time counted by the first timer with a corresponding task, and associates the total time counted by the second timer with a different corresponding task.

In some embodiments, a system and method for generating phrase based categories of interactions may include obtaining a base category, the base category including one or more phrases. A base trend for the base category may be generated based on a frequency of appearance of at least one of the one or more phrases in a set of recorded interactions; a candidate phrase may be obtained and a candidate trend may be generated for the candidate phrase based on a frequency of appearance of the candidate phrase in the set of recorded interactions; a correlation level may be determined by relating the candidate trend to the base trend; and, if the correlation level is greater than a threshold level then the candidate phrase may be included the in the base category.