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Data Extraction

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Overview

Our Machine Learning and Natural Language Understanding solution reads, extracts, classifies, and ingests data from unstructured digital insurance documents like policies, submissions, applications, binders, quotes, statements of value, loss run reports, and more hundreds of times faster than a human. Purpose-built for commercial insurance, it understands insurance jargon, enabling it to automatically recognize insurance-specific data points including broker name, insurer name, street address, city, state, limits, premiums, deductibles, coverages, exclusions, and more from multiple insurance documents in one second, compared to a human knowledge worker who can extract only 15 to 50 data points in 30 minutes. Giving underwriters greater access to data for better risk assessment and pricing; and brokers can compare quotes and check policies faster, enabling them to spend more time nurturing policyholder relationships.

Key Features

  • Machine Learning and Natural Language Understanding
  • Contextually understands the relationship between the data points
  • Extracts data from emails, Word, Excel, and PDF
  • Extract data rapidly and map to ACORD standards or legacy systems
  • Outputs data in XML or JSON

Key Benefits

  • Give underwriters access to data for better pricing and risk assessment
  • Automate and streamline the data extraction process and eliminate data rekeying
  • Free up skilled knowledge workers to focus on more strategic work

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