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Check out our reservoir of information related to check recognition and healthcare payment technologies. We frequently update this section with the latest news, trends, and analysis of the banking and healthcare industries.

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Platform Modernization

Both the financial and healthcare industries are undergoing modernization initiatives in check payments and remittance.  See how OrboGraph is using AI, self-learning and deep learning models to drive innovation in these industries to deliver workflow automation.

Platform Modernization

Modernizing payments in the banking and healthcare industries

AI, Self Learning & Deep Learning Technologies

Optimized AI and deep learning models for the automation of check processing and healthcare posting

Operationalizing AI & Self Learning in Checks

Revolutionizing check processing and fraud prevention for the banking industry

Delivering Healthcare Payment Electronification

Increased accuracy levels, decreased error rate for healthcare payments posting

Product Videos

See how each product/service module of OrboAnywhere and OrboAccess delivers value from our check and healthcare payment platforms

Corporate Video & Podcast

See and hear how OrboGraph incorporates AI, deep learning and self learning technologies into its product suite

Healthcare Payments

OrboAccess automates remittance and payment posting as well as enables full research and business intelligence analysis for RCM companies, clearinghouses, billers, and providers.

Access EOB Conversion

Delivers EOB/EOP electronification with information intelligence via AI and deep learning technologies

Access Correspondence Letters

Extracts posting data and tracks reimbursement progress via workflow management

Access Payment Reconciliation

Streamlines the reconciliation process of ERA, ACH, EOB and checks

Access Patient Payments

Automates patient payments for posting

Access Denial Intelligence

Spotlights trends in denials to reduce receivables via prevention

Healthcare Payments Automation Center

Scalable, reliable, flexible cloud-based hosted data center on Amazon Web Services (AWS)

Modernizing RCM with AI

An informative resource to assist RCM companies in understanding how to solve today's problems with the help of AI.

Check Processing

OrboAnywhere automates paper originated payments (i.e. checks, money orders, drafts) and remittances for balancing and posting while reducing risk and losses in the areas of check fraud, payment negotiability and compliance.

Anywhere Fraud

Transaction and image analysis for on-us and deposit fraud detection of counterfeits, forgeries, and alterations.

Anywhere Recognition

Divergent multi-engine CAR/LAR, ICR, OCR & AI check recognition for the Omnichannel

Anywhere Validate

Validate payment negotiability of paper originated items

Anywhere Payee

Match, read, and validate payees for risk and operational workflows

Anywhere Positive Pay

Payee name verification of business checks using issue files

Anywhere Compliance

Mitigate risk in check payments for OFAC, BSA/AML, UCC, Reg CC, and KYC

Restrictive Endorsement

Automatic validation of restrictive, mobile and non-restrictive endorsements

Traditional Products

Based on the Accura XV platform

Modernizing Omnichannel Check Fraud Detection

An informative blog series exploring payments fraud and image technologies used to fight financial crimes.

Modernizing Omnichannel Check Fraud Detection

An informative blog series exploring payments fraud and image technologies used to fight financial crimes.

Multi-Victim and Multi-Layered Fraud Challenges Banks

  • Double-layer fraud: fraudsters who actually defrauded other recruits who thought they were "in on it"

  • Both banks and accomplices alike were defrauded

  • The FI's solution: strategically aligning technologies to detect fraud

In Charlotte, NC, a check fraud group was able to steal an extensive amount of cash from five banks for over a year before being apprehended. Their methodology offers a look into what can sometimes be a strangely "entrepreneurial" aspect of organized fraud.

Omontie Rowe, 22, Fredrick Clark, 27, Fabio Wolfe, 27, and Jacoby Berry, 26, all pleaded guilty in federal court to aggravated identity theft on January 9, 2020.

The group called themselves the “All Profit Group” or “AP Group,” boasting about their successful check fraud scheme via social media.

That's right -- they posted photos of themselves with fistfuls of cash, and, what's more, this was apparently enough to convince people to respond to their invitation to "come aboard": All you had to do was open a bank account (or two) that the AP Group could access in order to deposit large checks. As reported by Eyewitness News 9, they would post messages like "Active bank accounts. I got a band 4 u. Cash up front."


Two Layers of Fraud to Look For?

The recruited straw account holders -- all with visions of windfalls dancing in their heads -- were promised a payment of $100 to $1,500, in exchange for allowing the co-defendants to use the account holders’ new or existing bank accounts to perpetuate the fraud.

The primary check fraud used stolen, counterfeit, or altered business and personal checks as "deposits" into the the new bank accounts, from which multiple cash withdrawals and purchases are made before the victim banks can detect the fraud.

For those keeping score, that's two levels of fraud that the bank is charged with detecting.

  • LAYER ONE: Persons opening new accounts that are essentially "shells" for the scammers that hired them
  • LAYER TWO: Counterfeit and altered checks, created from stolen checks, deposited into accounts just long enough to facilitate a fraudulent withdrawal

Rare occurrence? Hardly! A rap group known as Free Bandz Gang made $1.5 million in a bank fraud scheme using the same technique -- and they were based in Charlotte as well!

Strategically Aligning Technologies to Detect Fraud

Fraud continues to headline the news, with fraudsters deploying myriad techniques (some old, some new) to swindle money from banks and their customers. The AP Group's techniques are not new by any means, but the way they were able to deceive and defraud the customers -- and de facto accomplices -- into opening new accounts and sharing information, then depositing fraudulent checks and withdrawing the cash provides insight on how creative fraudsters have become.

So what could have the banks done to detect the fraud?

With the details provided by the new source, identifying the counterfeits by matching previous cleared checks at the bank to the ones being deposited. Using an image-based fraud system that scans the image of the check and compares it previously deposited checks would detect the counterfeits.

Additionally, banks can leverage the advancements in AI and Machine Learning technologies for analytics-based systems. If a new account receives a deposit of a transit check that contains attributes common to alterations or forgeries, the item will be flagged before the funds are made available.

When money is involved, fraudsters will continue to exploit any weaknesses in the system. It is up to the banks to use the best available technologies to combat the fraudsters.


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