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AI Innovation

Both the financial and healthcare industries are undergoing an AI evolution. Review our vision for Artificial Neural Networks (ANN) and deep learning targeting these industries.

AI-Based Check Automation

Check recognition & fraud detection are the most important components in today's check processing and omni-channel capture. Learn how OrboAnywhere using OrbNet AI technology reduces costs and mitigates risk.

AI-Based Healthcare Electronification

OrboAccess, powered by OrbNet AI, provides electronification to remits and payments, enabling RCM companies to automate posting, improve research, and deliver business intelligence

About Us

Celebrating 25 years of innovation, OrboGraph has transformed into an AI company delivering targeted automation solutions to the banking and healthcare industries.


From news and events to case studies, trends, and videos, this section provides a range of information resources for payment automation in the banking and healthcare industries.


OrboGraph produces four blog series on a weekly basis covering topics from check processing, fraud prevention, AI technologies, RCM, and healthcare electronification. Select one the blog to the right. We hope you enjoy!

  • Image analysis has been an effective tool in preventing check fraud
  • Marketing firms use and modify many of the same image analysis algorithms to raise their brand profile
  • Check fraud detection benefits from data collected in brand-building programs

We've discussed at length the ways in which Image Analysis is a crucial tool in preventing and detecting check fraud. For instance, image analysis is deployed to “see the attributes of an image” and compare that to previously cleared checks for match purposes.

As it turns out, Image Analysis is also a crucial tool in analyzing the effectiveness of online marketing, as explained in this Brandwatch article:


A valuable “moment of consumption.”

Over three billion photos are shared daily on social media according to Mary Meeker. Many of those photos contain brands’ products and logos, but 85% of them don’t include a text reference to the brand. Without image analytics, brands are missing out on a huge chunk of the social conversations about their brand, products, customers, and competitors.

Take, for example, the paparazzi pics at film openings (see below). Those logos aren't in the background for nothing. However, Anna Kendrick doesn't overtly mention or "hashtag" the brands that appear incidentally in the background of her widely-seen Instagram post. It's up to the brands themselves to be able to efficiently "harvest" references like this without having interns scouring iPhone screens. That's where Image Analysis comes in.


Brands also use Image Analysis to identify "moments of consumption." As explained at Brandwatch:

Unlike text, images provide visual validation of the who, where, and how people are using your product. Without image analysis, your fans and customers have to specifically mention your product, which is less likely to happen.

Visual evidence of product usage in the wild provides a much more powerful metric for brands than just measuring mentions. To take it a step further, you can start to correlate sales data with the number of times your product is appears up in social photos. Crimson Hexagon’s research has shown a strong correlation between sales numbers and the volume of social photos that show use of your products.

Among the benefits of widespread adoption of ever-improving Image Analysis is a growing stockpile of data and resultant increased effectiveness in check fraud detection. That's basically how check stock validation and automated signature verification work and expand their accuracy.

Join us on October 30, 2020, for the Fighting Fraud sessions at the ORBOIMPACT Virtual Conference. We'll cover:

  • Check Fraud Case Study
  • Introduce OrbNet AI for Check Fraud Detection
  • Round Table: Check Fraud Detection
  • Platform Decisions for the Future

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