With greatly adopted neural network algorithms, financial organizations can pinpoint the problem, significantly reduce tedious work and bring down processing costs.
ServReality is pleased to announce its AI-driven solution that analyzes millions of checks automatically, identifies anomalies and delivers a confidence score – whether a check is good, fraudulent or needs further review.
One of the key challenges that financial organizations face is the inability to detect irregular customer behavior and flag suspicious transactions. In many banking organizations, the process of spotting signs of fraud in checks that are still handwritten is time-consuming and tedious. That makes banks lose millions of dollars annually  to counterfeiters and fraudsters. Recognizing these challenges, ServReality has delivered a new solution that drives greater speed and accuracy across banking business processes, spots fraudulent checks in real time at the length of deposit and reduces the number of checks requiring manual review. With ServReality’s AI-fueled solution, the financial organization is managing fraud, improving operational efficiency and mitigating risks.
When ServReality tested its AI-driven solution, analyzing scanned images of handwritten checks to find out fraudulent checks, it demonstrated the following results:
● Kept initial and ongoing prices low while reducing manual
● Enabled the ability to identify fraudulent checks.
● Accurate and fast confidence score – 60 milliseconds on each
check that is up to 1,300 checks per second.
● 60% savings on losses due to fraud that are 35 U.S. million
“Machines on their own, they don’t know anything. They don’t know a table from a chair. They don’t know how to learn and get better at a task. They’re trained to do this using data and different types of processes to do the training. And so AI is that. It’s this big picture idea of enabling machines to get smart,” Paul Roetzer, CEO of PR 20/20 said on an episode of the Rethink Marketing Podcast .
Ray Kurzweil, a leading engineer who has radically advanced the fields of speech, text and audio technology, once said: “I’m working on artificial intelligence. Actually, natural language understanding, which is to get computers to understand the meaning of documents.”
ServReality successfully did it: it adopted a neural network to analyze previously scanned checks like payees, check numbers, routing transit and account numbers, even the signatures kept in the database. These terabytes of data enable to create a set of comparative algorithms that helped ServReality to identify whether the check is good or not.