Abstract: Disclosed is an approach in which news alerts are scanned in real-time or near real-time, relevant alerts identified through a topic extraction model, and associated actors identified through an entity extraction model. An entity resolution model may be applied to determine which actors are clients. The topic extraction, entity extraction, and/or entity resolution models may apply, for example, natural language processing models. The alert may be enriched by being packaged with client and transactional data to generate an enriched alert. A predictive model may be applied to the enriched alert to identify events with a high probability of law enforcement referral, and the enriched alert may be automatically transmitted to certain identified devices. The predictive model is trained using a combination of news alerts and data on clients and transactions, yielding enhanced predictions.

Abstract: Disclosed is an approach in which news alerts are scanned in real-time or near real-time, relevant alerts identified through a topic extraction model, and associated actors identified through an entity extraction model. An entity resolution model may be applied to determine which actors are clients. The topic extraction, entity extraction, and/or entity resolution models may apply, for example, natural language processing models. The alert may be enriched by being packaged with client and transactional data to generate an enriched alert. A predictive model may be applied to the enriched alert to identify events with a high probability of law enforcement referral, and the enriched alert may be automatically transmitted to certain identified devices. The predictive model is trained using a combination of news alerts and data on clients and transactions, yielding enhanced predictions.

Abstract: Disclosed is an example approach in which news alerts are scanned in real-time or near real-time, relevant alerts identified through a topic extraction model, and associated actors identified through an entity extraction model. An entity resolution model may be applied to determine which actors are clients. The topic extraction, entity extraction, and/or entity resolution models may apply, for example, natural language processing models. The alert may be enriched by being packaged with client and transactional data to generate an enriched alert. A predictive model may be applied to the enriched alert to identify events with a high probability of law enforcement referral, and the enriched alert may be automatically transmitted to certain identified devices. The predictive model is trained using a combination of news alerts and data on clients and transactions, yielding enhanced predictions.

Abstract: Disclosed is an approach in which news alerts are scanned in real-time or near real-time, relevant alerts identified through a topic extraction model, and associated actors identified through an entity extraction model. An entity resolution model may be applied to determine which actors are clients. The topic extraction, entity extraction, and/or entity resolution models may apply, for example, natural language processing models. The alert may be enriched by being packaged with client and transactional data to generate an enriched alert. A predictive model may be applied to the enriched alert to identify events with a high probability of law enforcement referral, and the enriched alert may be automatically transmitted to certain identified devices. The predictive model is trained using a combination of news alerts and data on clients and transactions, yielding enhanced predictions.

Abstract: Disclosed is an approach in which news alerts are scanned in real-time or near real-time, relevant alerts identified through a topic extraction model, and associated actors identified through an entity extraction model. An entity resolution model may be applied to determine which actors are clients. The topic extraction, entity extraction, and/or entity resolution models may apply, for example, natural language processing models. The alert may be enriched by being packaged with client and transactional data to generate an enriched alert. A predictive model may be applied to the enriched alert to identify events with a high probability of law enforcement referral, and the enriched alert may be automatically transmitted to certain identified devices. The predictive model is trained using a combination of news alerts and data on clients and transactions, yielding enhanced predictions.

Abstract: Disclosed is an example approach in which news alerts are scanned in real-time or near real-time, relevant alerts identified through a topic extraction model, and associated actors identified through an entity extraction model. An entity resolution model may be applied to determine which actors are clients. The topic extraction, entity extraction, and/or entity resolution models may apply, for example, natural language processing models. The alert may be enriched by being packaged with client and transactional data to generate an enriched alert. A predictive model may be applied to the enriched alert to identify events with a high probability of law enforcement referral, and the enriched alert may be automatically transmitted to certain identified devices. The predictive model is trained using a combination of news alerts and data on clients and transactions, yielding enhanced predictions.