SmartSearch has released a new document and identity verification solution to help combat rising fraud rates during the pandemic. The solution has been dubbed SmartDoc, and it supplements automated document recognition technology with facial recognition and manual document reviews.
The SmartDoc solution was built to prevent money laundering in industries like real estate and finance. According to SmartSearch, criminals are laundering as much as $2 trillion on an annual basis, and inadequate document and identity checks are only exacerbating the problem.
With that in mind, SmartDoc scans a document’s machine readable zone and uses an optical character recognition algorithm to make sure that each document is authentic, and to make sure that it has not been modified in any way. It then uses facial recognition to match the person depicted on the document to the face of the person holding it. Any cases that cannot be cleared automatically will be referred to a document expert trained to spot signs of forgery.
All names that go through the SmartDoc system will be cross-referenced with lists of Politically Exposed Persons and those facing sanctions. The solution will help SmartSearch meet the client demand for solutions that enable remote onboarding and identity verification while still allowing businesses to fulfill their Know Your Customer obligations.
“The lack of face-to-face interactions caused by lockdown opened a window for criminals to attempt to deceive, and despite restrictions being relaxed, this wave of fraud has not stopped,” said SmartSearch CEO John Dobson. “Businesses need to be aware that they are responsible for ensuring they comply with AML regulations and could face severe fines for allowing this activity to go on unchecked.”
Acuant has also started connecting customers with live agents to help businesses navigate a stricter regulatory environment. SmartSearch updated its onboarding platform at the beginning of the year, and followed that with the release of a new TripleCheck solution back in May.
(Originally posted on FindBiometrics)