Everything about the funds transfer looked like a routine online banking session. The customer logged in using a familiar device, and the IP address matched their region. The cursor moved across the screen before hovering over the confirmation button and clicking it to initiate the transfer.
Nothing unusual here—except that the transfer was being initiated by an AI-driven bot trained to mimic the customer’s online behavior. But since all the correct authentication protocols were followed, the bank’s fraud monitoring dashboard gave it the green light to proceed.
What is all-green fraud in banking? It's a sophisticated scheme in which every authentication indicator—device recognition, location, credentials—shows as "green" or approved, yet the transaction is fraudulent. And it is shaping up to be one of the biggest operational challenges for community banks in 2026.
“All-green fraud is the number one fraud issue our bank is dealing with now,” says Miguel Rivera, assistant vice president and fraud manager at $3.3 billion-asset Ponce Bank N.A. in Bronx, New York.
According to the 2025 State of Fraud and Financial Crime in the United States report, conducted by PYMNTS Intelligence, account takeover fraud in which cybercriminals impersonate legitimate users accounts for 71% of all fraud incidents at U.S. financial institutions, up from 48% a year ago.
“I’ve talked to many community bankers who are experiencing this type of fraud,” says Scott Anchin, senior vice president of strategic initiatives and policy for ICBA.
The many faces of all-green fraud
All-green fraud can occur online or in person at a bank branch.
With in-person fraud, scammers pressure customers to withdraw large amounts of cash and use it to buy gift cards or deposit a check and then immediately transfer some of the money to someone else.
“For example, someone might be hovering around in the background and whispering to the customer or talking to the customer on the phone or through earbuds,” says Anchin. “Then, the customer proceeds to conduct a transaction they wouldn’t normally, like sending a wire transfer for the first time.”
Gay Dempsey, CEO of $230 million-asset Bank of Lincoln County in Fayetteville, Tennessee, says battling fraud, including all-green fraud, is how the county sheriff’s department is now spending most of its time.
“We’re seeing a number of different scams,” says Dempsey. “For example, fraudsters meet customers online through dating or social media sites and convince them to withdraw money and send them cash.”
In another scam, fraudsters tell customers that they will lose money, face legal trouble or miss out on lottery winnings if they don’t perform a certain transaction immediately.
“Sometimes, the customer is told to use digital currency, send the money to a cryptocurrency wallet or buy gift cards with it,” says Dempsey. “In almost every case, the fraudster tries to pressure the customer into doing something they ordinarily wouldn’t do.”
Training employees to spot fraud: Your first line of defense
Solutions to combat all-green fraud are powered by both humans and technology.
“Prevention starts with training branch employees how to spot the warning signs that this type of fraud might be occurring and then what to do if it is,” says Rivera. “Your employees are your first line of defense, so they need to understand all the different scams that are prevalent, including all-green fraud.”
As Ponce Bank’s fraud manager, Rivera spends up to two hours with each new branch employee teaching them how to spot potential fraud red flags.
“I emphasize to them that preventing fraud is a team effort,” he says. “I can’t do my job without their help.”
Knowing your customers is also critical to fraud prevention, so tellers and other bank staff can recognize any unusual behavior and transactions that are out of the ordinary for a customer.
“We train our tellers to be inquisitive and ask questions if they’re ever suspicious about a transaction,” says Rivera.
All-green fraud red flags
The Bank of Lincoln County has created tools tellers can use if they suspect fraud might be occurring. This includes a checklist with several potential red flags, such as:
Is the transaction consistent with normal account activity?
Is the customer making decisions independently, without instruction from someone else?
Does the customer appear unsure about making the transaction?
Can the customer clearly explain the reason for the transaction if asked?
The community bank also has a small form tellers can slide across the counter that asks customers if there is someone listening on the phone or lurking in the background.
“If so, the customer can discreetly let us know, and we can end the transaction right away,” says Dempsey. “The most important thing is to get the customer to slow down and pause, because fraudsters instill a sense of fear and urgency.”
All-green fraud usually targets senior citizens, so the Bank of Lincoln County works with the sheriff’s department to give anti-fraud presentations at senior centers.
“But fraudsters don’t discriminate,” says Dempsey. “We’ve seen doctors and attorneys who have fallen for these scams, so it’s not limited to age or education level.”
Behavioral biometrics and AI fraud detection: Technology that spots what humans miss
On the technology side, some community banks are using behavioral biometrics to identify and stop all-green fraud before fraudulent transactions occur.
This technology confirms customers’ identities by tracking and analyzing their online behavior patterns and how they interact with devices in real time. Behaviors include keystroke dynamics, typing speed, mouse movements, touchscreen fluency, navigation patterns, cognitive timing and smartphone orientation.
Such online behavior patterns are as unique as individual fingerprints, so they create distinctive user-behavior profiles that can be monitored in the background using artificial intelligence and machine learning. These patterns are distinctive from the behavioral patterns of bots, which move the cursor in a straight line instead of a curved path, type at a constant speed instead of variable cadence and make decisions immediately instead of hesitating like a human normally would.
By detecting unexpected behavior patterns, such as unusual variations in typing speed and irregular mouse or touchpad movements, behavioral biometrics can flag potentially fraudulent transactions that aren’t picked up by normal authentication protocols. Once flagged, an online transaction can be subjected to additional verification steps and delayed or cancelled until more information is gathered.
Legal fraud-prevention tactics
In some states, such as Tennessee, the law allows banks to pause suspicious transactions.
“Our form explains that the bank reserves the right to halt the transaction if any red flags appear in order to protect the customer and the bank,” says Dempsey.
According to the PYMNTS report, more than two-thirds of banks have raised spending on advanced, AI-based fraud detection tools. Anchin says this underscores the need for layers of fraud protection.
“Fraudsters today are adept at getting around a single layer of protection,” he says. “But adding multiple layers, both human and technology, gives community banks a leg up in fraud protection.”
10 signs of potential ‘all-green’ fraud: A bank teller's warning checklist
The key to fighting all-green fraud is learning to spot the signs that it’s occurring. Here are a few common red flags to watch out for, both in branch and online.
In-branch human behaviors
- The transaction isn’t consistent with the customer’s normal account activity.
- The customer appears hesitant to complete the transaction.
- The customer appears to be under pressure from someone on the phone or standing in the background.
- The customer appears confused or fearful about the transaction.
- The customer cannot or refuses to answer simple questions from the teller about the transaction.
- The transaction appears to match common social engineering schemes perpetuated on online dating websites, phishing scams and social media.
Digital identifiers of bot-driven fraud
- The cursor moves in straight lines instead of being curved and irregular, indicating that a bot is in control.
- The typing speed is constant instead of variable.
- The transaction is submitted immediately instead of after a few seconds’ hesitation, like a human would probably do.
- The touchscreen pressure is constant instead of variable.
