Catch Me If You Can - How AI software prevents fraud

Catch Me If You Can – How AI Fraud Detection Software Transformed the Check Fraud Investigator’s Job

Catch Me If You Can – Today, AI-powered software can mimic human investigators, detect check fraud in milliseconds and stop the scam.

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Cognitive capture can help reduce fraud and human error impacting insurers

Fraud and Human Error Impact Health Insurers

Find out how cognitive capture can help eliminate the heavy toll of fraud and human error that impacts health insurers and patients.

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Is that training data any good?

Cognitive Capture: Is that training data any good? | Applied AI

The need for a data science approach where machine learning is applied to cognitive capture starts with high quality input data. Find out why.

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Guideposts for Cognitive Capture

Beware of Impostors: How to Tell If It’s Really Cognitive Capture

Here are some guideposts that are useful in evaluating the authenticity of an AI capture product – whether it’s really cognitive capture.

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Automation with ML: Are we there yet?

Magic of Machine Learning Applied to Automation: Are We There Yet?

The automation industry is on year-3 of its infatuation with everything machine learning and ‘unparalleled accuracy’ claims, what’s changed?

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Is there Machine Learning that does NOT require training?

IDP: Machine Learning and the Training Required for Reliable Results

No machine learning to-date works with zero training, but advances to reduce the training required for reliable results are underway. Details here.

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IDP Key Factors - minimizing human intervention

Dramatically Minimize Human Intervention – Key Factors Driving IDP

Key factors driving IDP adoption involve data science and specifically the confidence score that is arguably the most important factor involved with any decision to adopt IDP.

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context in IDP with Parascript

Understanding Complex Data via Context in Key Factors Driving New IDP

This new IDP article covers a major automation trend necessary for the claims submission-to-payment reconciliation process.

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Check fraud is now rampant among Millennials

“Check fraud is now rampant among Millennials!” Who would have thought?

Check fraud is now rampant among millennials when checks remain a huge part of the payments landscape – the case for investing in check fraud detection software.

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Machine Learning: Ability to learn and improve with Parascript

Key Factors Significantly Impacting IDP Adoption – Factor 2: Ability to Learn and Improve

This week is a deep-dive into the second factor, which addresses how modern IDP software can learn and improve—different solutions tackle the problem in different ways—some better than others.

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Key Factors Driving Intelligent Document Processing

Key Factors Driving New “Intelligent Document Processing”

Modern IDP software enables the automation of processes due to key factors including the ability to work in suboptimal conditions discussed here.

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Insurtech - 2021 Trends for Healthcare Insurance: Interoperability and Data Mining

2021 Trends for Healthcare Insurance: Interoperability and Data Mining

2021 trends for healthcare insurance explored here including how to mine the wealth of medical data and interoperability using Intelligent Document Processing.

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Mortgage Lending Automation - Parascript

Investment in “Smart” OCR Is a Must-do for Mortgage Lenders in 2021

Loan file review is critical in the loan process with the automation of file sorting, extracting and verifying of data taking on new urgency. Discover why here.

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Machine learning software solves claims processing challenges

New Machine Learning Software Solves the Most Difficult Healthcare Claims Processing Problems

Bridging the gap between healthcare today and healthcare tomorrow requires machine learning. Find out how ML solves healthcare claims processing problems.

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Automation with Parascript

Automation: Why Templates Are the Best and Worst Solution

In automation, using that most derided approach—the template—can be useful, but it has its limitations with the best and worst discussed here.

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