Bank Fraud Task Force Member Identifies ATM Theft Suspect
BENEFITS
Allows bank fraud investigators to identify over 3x as many ATM theft suspects
Saved weeks or months as opposed to traditional investigative methods
Helped prevent the suspect from stealing thousands more dollars from the bank
PROBLEM
BANK FRAUD TACTICS MAY BE SIMPLE BUT SOLVING A CASE CAN BE COMPLEX
Bank fraud can be as simple as opening a new bank account by depositing counterfeit checks and using an automated teller machine (ATM) to withdraw the funds before the bank identifies the checks as counterfeit. The account also may have been opened using a counterfeit identification card with a fictitious name. These practices make it challenging to identify the suspect.
Other investigative methods, such as checking the counterfeit checks for latent fingerprints, may yield enough information to identify the suspect. However, these procedures take weeks or months and are resource intensive.
The Williamson County Sheriff’s Office (TN) was investigating a bank fraud case in which the suspect had used an ATM to cash thousands of dollars’ worth of counterfeit checks. Because of the level of fraud that was committed, the case met the threshold for investigation by the U.S. Secret Service, and therefore the case was shared with a group of bank officials and investigators, Banks United Against Criminal Organizations (BUNCO), along with an image of the suspect taken from an ATM camera.
“They use a counterfeit check to deposit money then go to the ATM and withdraw it. By the time the bank realizes it’s a counterfeit check, they’ve already got that cash.”
SOLUTION
TIME IS MONEY
An AI-driven facial recognition solution can drastically accelerate the identification process. Facial recognition compares an uploaded probe image against a database of images. Law enforcement agencies use facial recognition results as investigative leads, and when supported by other evidence, they can accurately and rapidly identify suspects, persons of interest, and victims of crimes.
The technology Clearview AI provides is a post-event research tool, using over 40 billion photos derived from publicly available web sources, including social media posts, personal and professional websites, news articles, online mugshots and other criminal databases, public record sites and thousands of other open source records.
“The ATM cameras at the bank provide great facial images.”
THE RESULTS
THE NASHVILLE CRIMINAL INVESTIGATIONS DIVISION IDENTIFIES ATM THEFT SUSPECT
Lt. Scott Harding of BNA’s Public Safety Criminal Investigations Division is part of a regional group of bank officials and investigators that share information to assist in the identification, apprehension, and prosecution of individuals who commit financial crimes. The group received a notification of a bank fraud case by Williamson County who shared an ATM camera image of the person who fraudulently withdrew money from the bank.
Lt. Harding searched the image from the ATM camera using Clearview AI. Within seconds, he received a result showing a jail booking image tied to an arrest of an individual charged with fraud in Arkansas.
Further investigation using the FBI’s National Data Exchange (N-DEx) System revealed that the person had recently been released from prison after serving time for a conviction in a fraud case.
This information provided the agency with an investigative lead that it could use to help establish probable cause for an arrest warrant in the case.
Before Clearview AI was available to the investigators, they were only able to identify fewer than 10% of ATM thieves. With Clearview AI, investigators report that they are now able to identify more than 30% of these individuals, more than tripling their identification capabilities.
“Our ability to identify offenders from bank cameras has increased from less than 10% to more than 30% with Clearview AI.”
