Abstract: Provided herein are systems and methods for processing unstructured data for insurance pricing. In particular, the data processing systems and methods provided herein may be useful to price simulation for the optimization of insurance pricing. The data processing systems and methods use machine learning algorithms to automatically detect relevant rate factor tables in unstructured data sources, such as regulatory filing documents. The machine learning algorithms then extract rate factor data from the tables and place extracted rate factor data in a structured form, eliminating or reducing the need for manual structured data extraction. In some embodiments, the data processing systems and methods also include an audit interface for receiving one or more changes to the structured rate factor data. In the manner, the audit interface may be used to validate the structured rate factor data obtained via the methods described herein.

Abstract: Provided herein are systems and methods for processing unstructured data for insurance pricing. In particular, the data processing systems and methods provided herein may be useful to price simulation for the optimization of insurance pricing. The data processing systems and methods use machine learning algorithms to automatically detect relevant rate factor tables in unstructured data sources, such as regulatory filing documents. The machine learning algorithms then extract rate factor data from the tables and place extracted rate factor data in a structured form, eliminating or reducing the need for manual structured data extraction. In some embodiments, the data processing systems and methods also include an audit interface for receiving one or more changes to the structured rate factor data. In the manner, the audit interface may be used to validate the structured rate factor data obtained via the methods described herein.