How to move beyond data extraction and OCR as core competencies in document processing in order to meet evolving client data needs and expectations.
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How to move beyond data extraction and OCR as core competencies in document processing in order to meet evolving client data needs and expectations.
Find out about the latest capture and recognition trends including the key considerations in RPA and artificial intelligence powered by machine learning.
Reimagining auditing requires looking at the data on documents like invoices and tax forms to provide insights outside the normal business processes.
Many capture systems cannot provide the level of certainty necessary for data extraction to be truly automated–find out why…
Advanced image processing for scanned documents is now more important than ever—find out why and how it makes your life easier in this article.
Often in conversations with clients and prospective clients, we hear phrases such as “we want to get 90 percent accuracy” from our system, but what does that really mean?
BPOs with services fragmentation are increasingly at risk since they have often electing to procure technology on a project-by-project (a.k.a., client-by-client) basis, but there are approaches to overcome this fragmentation.
Now is the time for restrictive endorsement in fraud prevention, which means financial institutions will need to implement technology to detect the presence of the restrictive endorsement in addition to the signature.
When it comes to the classification of documents, one accepted approach is using text. And yet, visual classification can offer a powerful alternative.
Getting good and reliable OCR accuracy from your system may involve more than you think.
Panorama of AP automated solutions–traditional approaches versus machine learning and how to determine what solution works best for you.
How to move beyond features and attributes in document processing automation to identify the solution that best meets your enterprise’s needs.