Abstract: Systems and methods to facilitate credit risk assessment are described herein. The systems and methods described herein relate to implementing and training a credit risk model comprising a document model and a company model. The document model may be configured to read text of a document, understand long range relationships between words, phrases, and the occurrence of one or more financial events, and create a document score that indicates whether the financial events are likely to occur based on that document. A document-model-state vector may be generated that represents important features and relationships identified within each document and across a set of documents for a given entity based on the document scores. The company model may produce a sequence of default probability scores representing overall likelihoods of the occurrence of the financial events for an entity based on the document-model-state vector for documents associated with that entity.

Abstract: Systems and methods to facilitate credit risk assessment are described herein. The systems and methods described herein relate to implementing and training a credit risk model comprising a document model and a company model. The document model may be configured to read text of a document, understand long range relationships between words, phrases, and the occurrence of one or more financial events, and create a document score that indicates whether the financial events are likely to occur based on that document. A document-model-state vector may be generated that represents important features and relationships identified within each document and across a set of documents for a given entity based on the document scores. The company model may produce a sequence of default probability scores representing overall likelihoods of the occurrence of the financial events for an entity based on the document-model-state vector for documents associated with that entity.

Abstract: Systems and methods to facilitate credit risk assessment are described herein. The systems and methods described herein relate to implementing and training a credit risk model comprising a document model and a company model. The document model may be configured to read text of a document, understand long range relationships between words, phrases, and the occurrence of one or more financial events, and create a document score that indicates whether the financial events are likely to occur based on that document. A document-model-state vector may be generated that represents important features and relationships identified within each document and across a set of documents for a given entity based on the document scores. The company model may produce a sequence of default probability scores representing overall likelihoods of the occurrence of the financial events for an entity based on the document-model-state vector for documents associated with that entity.