Protect your business from fraud, enhance compliance, and boost operational efficiency with real-time AI-Native solutions.
Enhance trust, reduce losses, and improve customer experience by effectively addressing these pressing fraud challenges.
Issuers lose cardholder trust and absorb chargebacks when phishing, credential stuffing, or SIM swaps let fraudsters commandeer online and mobile banking sessions.
Fraudsters blend real and fabricated data to open new credit lines, leaving issuers with uncollectible balances and skewed risk models.
Over-aggressive rules cause issuers to block legitimate transactions, damaging customer experience and reducing interchange revenue.
Evolving mandates (PSD2, AML/KYC, CFPB) require issuers to prove rigorous controls, creating costly audit prep and reporting workloads.
FraudNet safeguards issuers by detecting threats early, reducing losses, and enhancing customer trust.
We don’t just promise better fraud control—we deliver tangible improvements that protect your business.
Approve more valid transactions confidently.
Experience double-digit reductions in fraud-related chargebacks
Save time and resources while securing your revenue.
With an integrated platform designed for precision, agility, and impactful results, enabling your team to make smarter decisions, improve operational efficiency, and fuel your business growth.
No-code rules engine, flexible dashboards, and tailor-made machine learning models that are designed to adapt seamlessly and scale alongside your business.
Unify fraud detection, compliance, and risk management into one powerful solution, saving valuable time and streamlining your operations.
Reduce false positives, detect and prevent more fraud, and mitigate risk with highly accurate, real-time risk scoring and anomaly detection you can trust.
Leverage advanced analytics, comprehensive reporting, and our Global Anti-Fraud Network to make faster, smarter decisions on the spot.
Issuer major fraud loss prevention refers to strategies and measures implemented by financial institutions that issue credit and debit cards to minimize financial losses due to fraudulent activities. This involves using advanced fraud detection systems, monitoring transactions for unusual patterns, and implementing robust authentication processes to protect cardholders' accounts and the institution's financial interests.
Real-time transaction monitoring is crucial in fraud prevention as it allows issuers to detect and respond to suspicious activities immediately. By analyzing transactions as they occur, issuers can identify potentially fraudulent behavior, such as unusual spending patterns or transactions from unrecognized locations, and take swift action to prevent unauthorized access or fraudulent purchases, thus minimizing financial losses.
Machine learning algorithms enhance fraud detection by analyzing vast amounts of transaction data to identify patterns and anomalies that might indicate fraud. These algorithms can adapt and learn over time, improving their accuracy in predicting and identifying fraudulent activities. This enables issuers to proactively prevent fraud by recognizing new and evolving tactics used by fraudsters, enhancing overall security and reducing false positives.
Multi-factor authentication (MFA) systems significantly bolster fraud prevention by requiring more than one form of verification to access accounts. This added layer of security makes it more difficult for fraudsters to gain unauthorized access, as they would need to bypass multiple verification methods, such as a password, a fingerprint, or a one-time passcode sent to a mobile device. MFA thus reduces the likelihood of account takeovers and unauthorized transactions.
Customer education is a vital component of fraud prevention, as informed customers can better protect themselves against fraud attempts. By educating customers on recognizing phishing scams, securing their personal information, and using strong passwords, issuers empower them to be vigilant and proactive in detecting and reporting suspicious activities. This collaborative approach helps in early fraud detection and prevention, reducing the overall risk of fraud losses.
To prevent card-not-present (CNP) fraud, issuers can implement measures such as tokenization, which replaces sensitive card information with unique identifiers, and use advanced verification technologies like 3D Secure. Additionally, issuers can employ fraud detection tools that analyze transaction data and use behavioral analytics to identify unusual activities. Encouraging merchants to use secure payment gateways and promoting customer awareness about safe online shopping practices are also effective strategies.