As payment channels have multiplied, so have the routes open to fraudsters; increasing banks’ potential liabilities. Adoption of real-time payments, Open Banking and digital-led interactions exacerbates these problems. Traditional anti-fraud practices find it all but impossible to efficiently prevent payment fraud. Most rely on hundreds of static, reactive rules that fail to detect new fraud patterns and trigger too many poor hits.
Leveraging award-winning 3D artificial intelligence (3D AI) technology, NetGuardians’ platform NG|Screener monitors all of the bank’s payment transactions in real-time catching more fraud with fewer false positives. It identifies suspicious payments coming from social engineering techniques or scams (such as invoice redirection, love scams, CEO-fraud) and ties this in with digital banking fraud indicators (such as eBanking/mBanking sessions redirected by malware, hijacked by hackers or account takeover fraud resulting from identity theft).
NetGuardians Payment Fraud solution offers ready-to-go pre-defined AI risk models for real-time fraud prevention. It ensures banks can meet SWIFT CSP and PSD2 requirements while proactively preventing both current and emerging payment fraud schemes.
Social engineering, false bills or fake phone calls that give the victim new payment details for utility bills are the most popular and widespread types of payment fraud these days. Corporates are targeted for larger amounts, but individuals are equally under attack.
Fraud detection on SWIFT messages
NetGuardians’ machine-learning fraud-mitigation software allows banks to monitor SWIFT messages to spot fraudulent payments in real time, helping them meet SWIFT Customer Security Program (CSP) requirements.
Customer success stories
NetGuardians AI platform analyzes a retail bank’s payment transactions over the period of 12 months. The results show that the bank significantly reduces the number of false positives, decreases operational costs, and improves the fraud detection rate.
Within seven months, NG|Screener had analyzed more than five million transactions yet blocked 10 times fewer payments than Aargauische Kantonalbank’s former system and achieved a better fraud detection rate.