The present disclosure relates to systems and methods for matching electronic activities with record objects based on entity relationships. The method can include accessing a plurality of electronic activities, identifying an electronic activity, identifying a first participant associated with a first entity and a second participant associated with a second entity, determining whether a record object identifier is included in the electronic activity, identifying a first record object of the system of record that includes an instance of the record object identifier, and storing an association between the electronic activity and the first record object. The method can include determining a second record object corresponding to the second entity, identifying, using a matching policy, a third record object linked to the second record object and identifying a third entity, and storing, by the one or more processors, an association between the electronic activity and the third record object.

A system and method for fraud detection and management are provided. The system includes a first communication device that receives a phone call from a second communication device, wherein a call flow of the phone call comprises one or more distinct phases. The system also includes a fraud detection and management system (FDMS) platform that determines whether the phone call exceeds a predetermined risk threshold at each distinct phase of the call flow.

The system and methods described herein can classify electronic activities based on sender and recipient information. The system can determine a relationship between a sender of an electronic activity and at least one recipient of the electronic activity using a sender node profile and a recipient node profile. The system can assign a tag to the electronic activity based on the relationship between the sender and one or more recipients of the electronic activity. The system can process the electronic activity based on the assigned tag.

Disclosed are a bill generation method and device, a mobile edge platform and a storage medium. The method includes: a charging service entity acquires a consumption record and charging policy configuration information, where the consumption record includes at least one of: a resource and a service on a mobile edge computing (MEC) platform used by a user terminal on the MEC on which the charging service entity is located, or a resource and a service on the MEC platform used by an application instance on the MEC platform on which the charging service entity is located; and the charging service entity generates a charging bill based on the consumption record and the charging policy configuration information.

The present disclosure relates to a method for determining a completion score for a record object based on electronic activities. The method includes accessing record objects, each of which corresponds to a record object type and includes object fields having object field-values. The method includes selecting one of the record objects. The method includes identifying electronic activities transmitted or received associated with the record object. Each of the electronic activities has a timestamp indicating a receipt time or transmission time of the respective electronic activity. The method includes determining a participant of each of the electronic activities. The method includes determining a completion score indicating a likelihood of completing an event associated with the record object based on the timestamp of each of the electronic activities and the participant of each of the electronic activities. The method includes storing an association between the record object and the completion score.

The present disclosure is related to systems and methods of merging tenant shadow systems of record into a master system of record. First tenant record objects of a first tenant system of record can be accessed. A master record object for a master system of record can be generated using the corresponding first tenant record object. A second tenant record object of a second tenant system of record can be accessed. Whether the second tenant record object is to be merged into the corresponding master record object can be determined. When determined to merge, the second tenant record object can be merged into the corresponding master record object. When determined to not merge, a new master record can be generated.

The present disclosure relates to systems and methods for determining an engagement profile of a participant by associating electronic activities to a profile. It may generate the engagement profile based on analysis of the electronic activity level. An example implementation may contain the following steps. The system may access for a first record object a plurality of electronic activities linked with the first record object. The system may identify for a participant from the plurality of electronic activities a set of electronic activities including the participant. The system may determine an engagement profile of the participant based on a first number of electronic activities of the set of electronic activities sent by the participant, a second number of the set of electronic activities received by the participant and a temporal distribution of the set of electronic activities. The system may store the engagement profile in one or more data structures.

Systems and methods are described herein for determining dropped call rates (DCR) for various communications networks, such as IP Multimedia Networks (IMS), which include Voice over LTE (VoLTE) networks. For example, the systems and methods utilize data (e.g. abnormal cause codes) generated by layers of the IMS networks, such as a Session Initiation Protocol (SIP) layer of the IMS network, when determining dropped call rates for IMS networks.

The present disclosure relates to methods, systems, and storage media for detecting events based on updates to node profiles from electronic activities. Exemplary implementations may access an electronic activity transmitted or received via an electronic account associated with a data source provider; generate a plurality of activity field-value pairs; maintain a plurality of node profiles; identify a first state of a first node profile of the plurality of node profiles; update the first node profile using the electronic activity; identify a second state of the first node profile subsequent to updating the first node profile using the electronic activity; detect a state change of the first node profile based on the first state and the second state; determine that the state change satisfies an event condition; and store an association between the first node profile and an event type corresponding to the event condition.

The system described herein can automatically match, link, or otherwise associate electronic activities with one or more node profiles. For an electronic activity that is eligible or qualifies to be matched with one or more node profiles, the system can selectively apply rules to match the electronic activity to a subset of the one or more node profiles based on values of fields extracted from the electronic activity and values of the node profiles. The system can then store an association between the electronic activity and the subset of the one or more node profiles.