Identify and locate text contained within unstructured data.
Data Extraction - Entity extraction, also known as entity identification and named entity recognition (NER). Is the process of identifying and locating a required piece of text or an entity e.g, a name contained within a piece of unstructured text.
360Retrieve turns known format semi-structured text documents into structured data by extracting all properties and entities and aligning them with the field identifier including this includes;
- MOJ Documents
- OIC Portal Documents
- Medical Reports
The extracted data can then be used to produce analytical outputs and insights on information that embedded within unstructured data and join with structured data and other data sources, enabling Insurers to efficiently analyse all of their data.
Data extracted from unstructured data can also be delivered in data slabs to enrich data and join with other data in case management and Business Information systems Insurers of 100% of their data you can make sense of the trends and topics important to your business, which can help create more accurate strategies
Extracts of data held within 360Retrieve for customisable business information, interrogation and joining with internal case management systems and platforms
Joining Data - 360Retrive joins all internal, external, Industry and third-party data with unstructured data delivering a “One World” view of all available data.
Data sources include;
- Structured data from case management systems.
- Data held within legacy systems.
- Internal databases
- Business Information systems.
- Industry data sources including.
- CUE (Claims Underwriting Exchange)
- MIAFTR (Motor Insurance Anti-Fraud and Theft Register).
- MID (Motor Insurance Database).
- Third-party data sources subscribed to by the Insurer.
- Data sources from 360Globalnet data provision partners.
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