Other parts of this series:
In my last blog, I discussed how manual data entry creates multiple problems for life insurers related to data quality, efficiency and workforce scalability. And why finding the right approach to data capture is critical to success in today’s marketplace. However, developing efficient data capture capabilities in-house is not very easy.
Life insurance must seek help from vendors that specialize in a man + machine approach. These vendors combine advanced machine computing and analytics with superior contextual recognition powers of the human brain to accurately recognize printed and handwritten text, and transform it into structured digital data.
Here are few data capture tools and methodologies insurers can consider:
Word recognition technologies
Three primary technologies are commonly used to convert images or PDFs of static documents containing typed or handwritten text into machine-encoded text: Optical character recognition (OCR), intelligent word recognition (IWR) and intelligent character recognition (ICR).
OCR can recognize a multitude of fonts, patterns and numbers, and convert static documents into searchable text. ICR is an advanced form of OCR that can identify handwritten characters. And, IWR can identify words and phrases that are handwritten either in block-print or cursive.
Application of text recognition technologies
Recognition technology is often integrated with document management systems (DMS) and more broadly, enterprise content management (ECM) systems. For example, document imaging, PDF conversion and text recognition technologies developed by ABBYY are used across the globe by document capture solution specialists including Dell, Kurzweil, EPSON and Captiva. Kofax Image Products uses ABBYY technologies as part of its capture platforms.
Mobile data capture
With mobile data capture (MDC), users take images of documents using a camera-equipped mobile device. The image data is sent to a data capture server that extracts the information stored in the image. MDC is flexible, scalable, and increases speed while significantly decreasing the operating costs associated with data capture. ABBYY and Kofax offer on-device mobile capture solutions.
Crowdsourcing and machine learning
Merging human and artificial intelligence to capture data is a flexible as well as scalable solution. Software alone, even with far-reaching abilities to capture information from static sources, cannot accurately contextualize data. That ability remains a function of human intelligence. Crowdsourcing—the collection of meaningful human intelligence from virtually unlimited sources at any time and for any purpose—can be used to significantly enhance data capture software.
Data as a service
Data-as-a-service (DaaS) solutions such as those from Captricity make captured data available in a record that can be viewed and downloaded from a secure website, or imported directly into existing CRM and ERP systems and statistical analysis tools. All interactions with the product occur via a web browser, agent or application process interface (API).
The next step for insurers
Insurers must find economical, accurate and scalable solutions for accessing the data on which their future depends. They can join forces with leading technology providers to leverage reliable, efficient data capture software that enables extremely high accuracy levels and requires relatively small to no complex integrations or IT resources.
To learn more about these data capture techniques, read our point of view Automated Data Capture Enables Insurance Growth. I’m sure you will find it useful.