Once a “Luxury,” AI Becomes a Necessity Against Modern Fraud Tactics
- Fraud is rampant, but preventable
- AI technology is being deployed by fraudsters
- Fighting fraud will require AI tools
There's no question about it: modern fraud detection systems -- including check fraud detection -- require the utilization of artificial intelligence to keep up with fraudsters.
Why, you may ask? Because AI is used in half of banks scams, according to Fortune.com.
From the article:
Thanks to increasingly sophisticated digital tools, bank scams and frauds have become a pervasive threat to consumers and financial institutions alike. From AI-powered deepfakes to elaborate check fraud schemes, criminals are employing a wide array of tactics to separate unsuspecting victims from their hard-earned money.
When focusing on check fraud, the article mentioned the tried-and-true check overpayment scam, but fraudsters have evolved to more sophisticated schemes. They utilize AI in a variety of ways, such as digitally editing and even full creation of check stock.
With AI being so prevalent in fraud, FIs need to match the fraudsters.
AI for Transactional Analysis
Forbes.com recently published an article detailing why AI is a necessity for fighting financial crimes. One key technology highlighted is transactional monitoring -- aka transactional analysis.
AI technology is essential to gathering "financial intelligence" and recognizing these changing patterns and evolving trends. What was once a straightforward albeit slow manual function in the analog world now requires data automation to parse through galaxies of transaction data to determine what is and isn’t illicit activity.
While focused mainly on the compliance side, transactional analysis is essential for check fraud detection. By leveraging the data from a check transaction, along with extracting data off the check, FIs have the ability to detect not only patterns that indicate possible money laundering, but also anomalous transactions that are fraudulent.
Analyzing different fields of the check such as amount, serial number, the life of the account (brand new), velocity of check transactions, dormancy of the account, check out-of-state, and payee fields are important components for on-us and deposit fraud detection. By leveraging AI to analyze this data with other transactional data from the account, FIs can identify more fraud and reduce losses.
AI for Analyzing Check Images
Previously, FIs leveraged image analysis to interrogate the images of checks, comparing them to previous cleared items. While considered groundbreaking 15-20 years ago, innovations in the industry remained stagnant due to the lack of investment -- with many pointing to the "checks are dead" sentiment as the reason.
However, fintechs like OrboGraph understood the stickiness of checks and chose to invest in AI technologies for check fraud detection -- even prior to the 2022 check fraud boom. Our OrbNet Forensic AI technology leverages advanced deep learning models to achieve 95% detection rates on targeted use cases. Each analyzer has been developed to examine certain features of the checks, from the check stock to the handwriting/font styles utilized on checks -- exceeding the capabilities of legacy OCR technology and image analysis.
The future of fighting fraud starts today with AI-powered tool integration for fraud departments. These tools analyze a vast of amount of data or accurately analyze single transactions to detect fraudulent activity -- providing fraud departments the upper hand against fraudsters.