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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 and Deep Learning-Based Check Processing

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 for any check image capture workflow.

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.

Resources

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.

Blogs

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!

Seven-Step Deposit Fraud: Would Your Bank Catch This?

  • Banks in New Jersey were taken for many thousands of dollars
  • The scam was a fairly elaborate, multi-step affair
  • $250,000 had been stolen before the scammers were caught

We all know about scams involving passing fake or altered checks, but what about elaborate multi-step operations? Here's an interesting "What if?" exercise -- could your bank spot this scam?

The short version: A 37-year-old New Jersey man and two accomplices used the stolen identities of three children to construct an elaborate scam that netted at least $250,000 for the conspirators before they were found out.

Business, technology, internet and networking concept. Young businessman working on his laptop in the office, select the icon Fraud prevention on the virtual display.3d illustration

A Step-by-Step Review of the Scam

  • Step One: Identity theft via lifting the names, Social Security numbers, and other vital statistics of three minors
  • Step Two: Create sham businesses using the names and vital statistics stolen from the minors
  • Step Three: Secure articles of organization or certificates of incorporation, with complete paperwork, for the fictional companies as well as fake ID

  • Step Four: Open bank accounts at multiple banks for the sham businesses using the above "real" documents
  • Step Five: Deposit stolen and fraudulent checks into the fake businesses' now-real accounts
  • Step Six: Make maximum-allowed withdrawals from targeted banks at the earliest possible time
  • Step Seven: Disappear

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Scammers Caught

In the end, Benjamin Rich, of Edison, New Jersey got caught somewhere between Step Six and Step Seven.

Mr. Rich was indicted on one count of conspiracy to commit bank fraud and one count of aggravated identity theft, the U.S. Attorney’s Office for New Jersey said in a statement. He and two accomplices (who were arrested as well) netted at least $250,000 from the scheme before being caught, however.

Looking at the component parts of the scam above, it's an interesting exercise to wonder at what point your bank may have spotted the fraud.

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Multi-Layer Protection

When we take a view at this use case of deposit fraud, the perpetrators were not a sophisticated syndicate exploiting hundreds or thousands of victims through an elaborate scheme. However, as you can see, this still cost the banks and their customers (or in this case three innocent children) thousands of dollars. As noted above, these perpetrators were caught between steps 6 and 7. However, utilizing a multi-layered detection technologies with image forensics and image recognition on the stolen and fraudulent checks could have stopped them cold at step 5 before funds were withdrawn.

OrboGraph detects deposit fraud via multiple OrboAnywhere modules including; Anywhere Fraud, Anywhere Validate, and Anywhere Payee. These modules deploy image forensics (OrbNet Forensic AI) and image recognition (OrbNet AI) to deliver a unique blend of protection to the FI and its clients on deposited items. The modules work in combination to analyze the image of each check, generating a risk score that indicates the probability of a fraudulent check -- flagging potential fraud items and enabling banks to review them before funds are withdrawn.

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