Abstract: A computing platform may receive, from a web server, entity identification information in different formats, and normalize the entity identification information. After normalizing the information, the computing platform may receive a plurality of interaction records each associated with an interaction between a system and a client of the system. The computing platform may compare the normalized entity identification information with the interaction records of the interactions between the system and the clients of the system. After determining that the entity identification information matches client information for one of the interaction records, the computing platform may send an alert to a control server. The alert may cause the control server to take one or more actions with respect to the client. For example, future attempts by the client to access one or more services offered by the system may be blocked for access by the client.

Abstract: Aspects of the disclosure relate to implementing and using a data processing system with a machine learning engine to provide automated collaboration assistance functions. A computing platform may receive, from a teleconference hosting computer system, a content stream associated with a teleconference. Responsive to receiving the content stream associated with the teleconference, the computing platform may generate, based on a machine learning dataset, real-time transcript data comprising a real-time textual transcript of the teleconference. The computing platform may receive a request for a summary of the teleconference. Responsive to receiving the request for the summary of the teleconference, the computing platform may generate, based on the real-time transcript data comprising the real-time textual transcript of the teleconference, a summary report of the teleconference.

Abstract: A computing platform may receive, from a web server, entity identification information in different formats, and normalize the entity identification information. After normalizing the information, the computing platform may receive a plurality of interaction records each associated with an interaction between a system and a client of the system. The computing platform may compare the normalized entity identification information with the interaction records of the interactions between the system and the clients of the system. After determining that the entity identification information matches client information for one of the interaction records, the computing platform may send an alert to a control server. The alert may cause the control server to take one or more actions with respect to the client. For example, future attempts by the client to access one or more services offered by the system may be blocked for access by the client.

Abstract: A computing platform may receive, from a web server, entity identification information in different formats, and normalize the entity identification information. After normalizing the information, the computing platform may receive a plurality of interaction records each associated with an interaction between a system and a client of the system. The computing platform may compare the normalized entity identification information with the interaction records of the interactions between the system and the clients of the system. After determining that the entity identification information matches client information for one of the interaction records, the computing platform may send an alert to a control server. The alert may cause the control server to take one or more actions with respect to the client. For example, future attempts by the client to access one or more services offered by the system may be blocked for access by the client.

Abstract: Aspects of the disclosure relate to implementing and using a data processing system with a machine learning engine to provide automated collaboration assistance functions. A computing platform may receive, from a teleconference hosting computer system, a content stream associated with a teleconference. Responsive to receiving the content stream associated with the teleconference, the computing platform may generate, based on a machine learning dataset, real-time transcript data comprising a real-time textual transcript of the teleconference. The computing platform may detect, during the teleconference, based on the real-time transcript data comprising the real-time textual transcript of the teleconference, an action item associated with the teleconference.

Abstract: A computing platform may receive, from a web server, entity identification information in different formats, and normalize the entity identification information. After normalizing the information, the computing platform may receive a plurality of interaction records each associated with an interaction between a system and a client of the system. The computing platform may compare the normalized entity identification information with the interaction records of the interactions between the system and the clients of the system. After determining that the entity identification information matches client information for one of the interaction records, the computing platform may send an alert to a control server. The alert may cause the control server to take one or more actions with respect to the client. For example, future attempts by the client to access one or more services offered by the system may be blocked for access by the client.

Abstract: A computing platform may receive, from a web server, entity identification information in different formats, and normalize the entity identification information. After normalizing the information, the computing platform may receive a plurality of interaction records each associated with an interaction between a system and a client of the system. The computing platform may compare the normalized entity identification information with the interaction records of the interactions between the system and the clients of the system. After determining that the entity identification information matches client information for one of the interaction records, the computing platform may send an alert to a control server. The alert may cause the control server to take one or more actions with respect to the client. For example, future attempts by the client to access one or more services offered by the system may be blocked for access by the client.

Abstract: Aspects of the disclosure relate to implementing and using a data processing system with a machine learning engine to provide automated collaboration assistance functions. A computing platform may receive, from a teleconference hosting computer system, a content stream associated with a teleconference. Responsive to receiving the content stream associated with the teleconference, the computing platform may generate, based on a machine learning dataset, real-time transcript data comprising a real-time textual transcript of the teleconference. The computing platform may detect, during the teleconference, based on the real-time transcript data comprising the real-time textual transcript of the teleconference, an action item associated with the teleconference.

Abstract: Aspects of the disclosure relate to implementing and using a data processing system with a machine learning engine to provide automated collaboration assistance functions. A computing platform may receive, from a teleconference hosting computer system, a content stream associated with a teleconference. Responsive to receiving the content stream associated with the teleconference, the computing platform may generate, based on a machine learning dataset, real-time transcript data comprising a real-time textual transcript of the teleconference. The computing platform may identify one or more subject matter experts associated with one or more topics by processing the real-time transcript data using at least one activation function. Subsequently, the computing platform may update the machine learning dataset based on identifying the one or more subject matter experts associated with the one or more topics.

Abstract: Aspects of the disclosure relate to implementing and using a data processing system with a machine learning engine to provide automated collaboration assistance functions. A computing platform may receive, from a teleconference hosting computer system, a content stream associated with a teleconference. Responsive to receiving the content stream associated with the teleconference, the computing platform may generate, based on a machine learning dataset, real-time transcript data comprising a real-time textual transcript of the teleconference. The computing platform may receive a request for a summary of the teleconference. Responsive to receiving the request for the summary of the teleconference, the computing platform may generate, based on the real-time transcript data comprising the real-time textual transcript of the teleconference, a summary report of the teleconference.

Abstract: A computing platform may receive, from a web server, entity identification information in different formats, and normalize the entity identification information. After normalizing the information, the computing platform may receive a plurality of interaction records each associated with an interaction between a system and a client of the system. The computing platform may compare the normalized entity identification information with the interaction records of the interactions between the system and the clients of the system. After determining that the entity identification information matches client information for one of the interaction records, the computing platform may send an alert to a control server. The alert may cause the control server to take one or more actions with respect to the client. For example, future attempts by the client to access one or more services offered by the system may be blocked for access by the client.

Abstract: Systems and methods are disclosed for assessing a relocation option. More specifically, a line of business may assess a relocation option by generating a geographic model that may be based on data about a relocation option. The system and method of generating a geographic model may include the generation of a reward score based on reward drivers. The model may also include generating a risk score that is based on risk factors. The reward score and the risk score may be compared. The line of business may also conduct an in-country/due diligence visit based at least in part on the geographic model and may assemble a risk mitigation framework. In addition, outputs of the model may be analyzed using portfolio theory analysis. Such portfolio theory analysis may include determining the Markowitz Efficient Frontier of optimal location sets. The analysis may also include obtaining an optimal location set based on a preferably predetermined concentration risk tolerance.

Abstract: Systems and methods are disclosed for assessing a relocation option. More specifically, a line of business may assess a relocation option by generating a geographic model that may be based on data about a relocation option. The system and method of generating a geographic model may include the generation of a reward score based on reward drivers. The model may also include generating a risk score that is based on risk factors. The reward score and the risk score may be compared. The line of business may also conduct an in-country/due diligence visit based at least in part on the geographic model and may assemble a risk mitigation framework. In addition, outputs of the model may be analyzed using portfolio theory analysis. Such portfolio theory analysis may include determining the Markowitz Efficient Frontier of optimal location sets. The analysis may also include obtaining an optimal location set based on a preferably predetermined concentration risk tolerance.