Addressing the unstructured data problem

According to SSON Analytics’ latest interactive workbook, more than a third of Shared Services/GBS are struggling with significant levels (>50%) of unstructured data in their enterprise, while slightly more than 40% have moderate levels (26-50%).

The inability to capture and process unstructured and unformatted data from the ever-increasing variety of documents enterprises are having to process poses a huge challenge in achieving end-to-end automation for document-centric business processes and unlocking the true value of intelligent automation. 86% of the survey respondents believe that unstructured data is impacting their operational productivity and business effectiveness.

OCR has been the go-to solution for scanning and translating non-structured data into digital form but requires rules-based templates or documents with a common structure. Based on the survey, more than half of the respondents believe that their OCR solution provides less than 60% accuracy rate which is a pretty disappointing result. This means, only a quarter are achieving great results and high accuracy rates of 80% or more with their OCR solutions.

So how do we address the limitations of OCR and rules-based approaches to document digitization?

Intelligent document processing (IDP) represents the next generation of automation solutions that transform unstructured and semi-structured information into usable data. It can capture data from a variety of document formats, categorize and validate that data, and then extract it for further processing utilizing artificial intelligence technologies like deep learning and machine learning, natural language processing or computer vision.

Best practice IDP solutions offer the following capabilities: And deliver these benefits:
  • The ability to automate data entry from various types of documents, ranging from handwritten forms, emails, images, and even voice, into enterprise systems with a high level of accuracy
  • An automated platform that trains the model on data extraction, learning and evolving through AI 
  • Advanced document and dossier validation rules and methodologies
  • Pre-trained models out-of-the-box for common use cases
  • Cloud-based deployment for greater agility
  • Easy integration with enterprise applications and systems, such as RPA
  • Easy transfer of validated data into third-party analytics tools
  • Clear cost savings through efficient processing of large volumes of data
  • Easy to use, so operations can set up quickly
  • Increase in data accuracy
  • Improved straight-through processing
  • Improved end-to-end automation of document-centric processes for greater efficiency
  • Improved employee and customer experience

Source: SSON’s How Intelligent Document Processing is Driving Customer Centric Transformation in Insurance

For more data and full results of the IDP survey, read the recently published analytics workbook: Intelligent Document Processing: A Game Changer for Successful Digital Transformation & Digitization

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