Tuesday March 13, 2018 0 comments
LONGMONT -- Parascript today announced powerful, best-in-the-industry classification and recognition for black-and-white claims in addition to its red drop-out claims capture.
Parascript said it has overcome the perpetual image quality and scaling challenges of black-and-white claims and now provides 200-400 percent better performance than other solutions on the market today -- achieving close to the same results as extracting data from much more straightforward red drop-out claim forms.
“The keys to our unequaled technology performance are Parascript’s proprietary image processing and field-level recognition technology,” said Greg Council, Parascript’s VP of marketing and product management.
“We call it “virtual drop-out” since it performs in most cases as well as red drop-out recognition because of its field-level image clean-up and alignment. To do this, Parascript applied new deep learning algorithms to improve out-of-the-box accuracy to the industry’s highest level.”
Unlike other claims recognition solutions, Parascript said FormXtra provides not only pre-built configuration for claims documents, but in addition, each field is tuned and optimized to achieve a specific statistically-measured accuracy rate that is the equivalent of dual-pass data entry.
“We have found that most of our prospective clients gave up on black-and-white claims a long time ago due to the inability to deal with image quality problems or due to interference that the form structure has on achieving good OCR,” said Council.
“Even though these claims represent a smaller portion of overall production volume, it represents an outsized cost. With this new capability, that cost can be significantly reduced by 80 percent or better.
“The same platform can also deal with automating multi-page claims and the supporting documentation through use of our automated document classifier. We’ve found that it drastically reduces the need to manually sort and organize every page. Pages can be scanned in any order, further reducing labor-intensive hours spent in document preparation.”