New Aite Research Highlights Remittance Processing Pains of the B2B Middle Market

Back in March and April, Parascript commissioned research with the Aite Group to better understand the current state of receivables processing automation at mid-market companies ($50m – $500m). Most specifically, we were interested in the more complex, business-to-business (B2B) market. We learned a great deal. A few of the highlights: The average mid-size B2B company […]

Read More

The 2 Most Common Misconceptions about Recognition Technology

When it comes to automated recognition technology, there are 2 common misconceptions about expected results that can be easily solved with tuning. Misconception #1: All items in a stream are equally hard to read, both automatically and manually The items that cause the most errors and rejects are not random. In fact, the items that […]

Read More

Efficient Processing of Incoming Mail

For small companies and large enterprises alike, mail continues to be an integral part of the document workflow. In a typical mail center, 60 to 70 percent of the labor is spent sorting incoming and interoffice mail. Incoming mail is defined as those mail pieces that are received by any company, and in addition to […]

Read More

The Truth about Trainable Forms Processing

There are many capture systems that market the ability to automatically “learn” document formats and layouts or to allow the system to be “trained”. In either case, the objective is twofold: Minimize the effort required to define document rules specific to each document variant and Improve overall recognition rates and lower error rates. The Problem […]

Read More

Understanding Recognition: Reject Mechanism

Let’s explore the mathematical model for optimizing the tradeoff between errors and rejects. The reject mechanism helps to guarantee the specified error level required by an application. Recognition engines usually return an answer accompanied by a value parameter called confidence value. The confidence value ranges from 0 to 100 and indicates how confident the engine is that […]

Read More

Back to School – Field v Character Recognition Circa 1999

Ever dust off something your company was working on ten years ago and scratch your head in a moment of deja-vu, wondering if anything has actually changed? Here’s a scan of a Parascript newsletter, from 1999! The funny thing is, reading it feels like not much has changed. There have been M&A’s, (Captiva to name […]

Read More

Understanding Recognition: Errors and Rejects

There are 3 possible outcomes when recognition engines attempt to read any data: the correct answer, error, or reject. This post will focus on understanding errors and rejects and how to find the right balance between them. Errors refer to the instances when a recognition engine gives an incorrect result. The problem with errors is […]

Read More

Big Decision Coming Up? A Process for Making Better Choices

By Don Dew, Director of Marketing Do you have a big decision coming up? Whether buying a car, looking for a job, or evaluating capture software, one thing is for certain. As a human, your likelihood of making the best decision is, frankly, flawed out of the gate. The good news is, with a little […]

Read More

AIIM Report: Only 13% of Form Data is Being Extracted

AIIM just released the market watch report “Winning the Paper Wars – Capture the Content and Mobilize the Process Troops” where they explore the reasons why paper-free processes have been slow to be adopted. Not surprisingly, the report shows that while 70% of businesses are scanning as part of their process, only 13% are using […]

Read More

Operating Point – The Most Critical Number in Recognition

There’s a lot of confusion around how to judge the accuracy of intelligent character recognition (ICR). Creating a metric is critical, as it helps us define the business case. To that end, Parascript engines produce an internal metric, called “confidence value”. And while this metric is critical to defining the business case, it is really […]

Read More

Vocabularies and ICR – Why You May Not Be Getting The Results You Expect

The goal of every recognition engine is to produce the highest accuracy possible which is probably pretty obvious (who uses technology to get poor results?). But did you know that the type and quality of images being recognized can and often produces significantly different results, depending upon which recognition technology is used? For example, in […]

Read More

Advanced Capture for Managing Data Exceptions

There are three primary areas businesses should examine when approaching a document capture project. Without having a solid grounding, business can face significant pain regarding their ability to effectively collect data and ensure its quality, all without significantly increasing exception handling. Many companies don’t take advantage of data recognition and extraction capabilities, even for the […]

Read More

Eliminating Common Errors in Forms Processing for Healthcare

More and more hospitals and insurers are looking to move medical records, claims and enrollment applications online. However, due to doctors’ and patients’ limited access to computers and the ease of applying pen to paper, healthcare organizations are still very reliant on paper forms. The many steps involved in processing healthcare documents, from completing information […]

Read More

How Context and Business Rules Can Help Get the Most from Your Data

Considering all of the ways that businesses rely on data, the benefits of increasing the accuracy of information and processing it more quickly can be huge. From improving internal and external transactions to enhancing customer service; increasing collections and saving time, money and the hassle of researching incorrect data, most organizations stand to gain both […]

Read More

Document Recognition: Speed versus Accuracy

With any document recognition workflow, both speed and accuracy come into play when designing the process. Each has pros and cons requiring analysis to determine the best approach while defining document types, field recognition requirements and validation and verification workflows. In most cases, the tradeoff might not be obvious or apparent. Multiple factors affect speed […]

Read More