As online commerce fraud becomes increasingly industrialised, payment networks are shifting toward earlier-stage intervention models designed to stop fraudulent merchants before transactions even occur. Mastercard’s launch of Merchant Trust Services reflects a broader move across the payments industry to combine identity intelligence, behavioural analytics, and network-level risk monitoring into real-time merchant screening systems.
Mastercard has officially launched Merchant Trust Services, an enterprise software platform designed to help banks and payment providers identify and intercept scams generated by fraudulent online storefronts. These scam operations frequently lure consumers using exceptionally low prices or rare items to secure funds before disappearing, or they function as front lines for phishing expeditions to harvest credit card details for dark web resale. The new technology integrates network intelligence, identity capabilities, and real-time data analytics to differentiate legitimate digital merchants from high-risk entities during both initial onboarding and subsequent transaction cycles.
The platform aims to eliminate scam operations during the onboarding phase, preventing fraudulent actors from opening digital storefronts or mitigating damage during the early stages of business operations. Ann Johnson, Executive Vice President of Security Solutions at Mastercard, emphasised that allowing scammers to pose as legitimate businesses damages consumer confidence across the entire digital ecosystem. Alongside this platform, the network is introducing the Merchant Scam and Risk Indicator, a tool that transmits merchant risk signals directly to issuing banks during the authorisation process.
During an initial pilot program conducted with a prominent issuer, the risk indicator successfully identified approximately 80% of risky merchants, with many entities being flagged up to 90 days before the initial escalation by the issuer. Simon Collins, Chief Franchise Officer at Mastercard, noted that bad experiences online cause shoppers to second-guess legitimate businesses, leading to higher transaction declines, disputes, and abandoned shopping carts. The risk indicator tool will be deployed first across Europe and the United States, with a broader global expansion scheduled to take place within the year.
What this means for the industry
- Fraud prevention is moving upstream into merchant onboarding
Payment providers are no longer focusing solely on transaction monitoring. Increasing attention is being placed on detecting fraudulent businesses before they can begin accepting payments. - Scam storefronts have become a major threat to digital commerce
Fake e-commerce sites are increasingly sophisticated, often mimicking legitimate retailers while using social media advertising and discounted pricing to attract victims quickly. - Issuer banks want earlier fraud intelligence signals
Mastercard’s risk indicator model highlights growing demand from banks for predictive fraud insights during transaction authorisation rather than relying only on chargebacks and customer complaints after the fact. - AI and network analytics are becoming core to trust infrastructure
Large payment networks are leveraging transaction patterns, identity data, and behavioural analytics to distinguish legitimate merchants from emerging fraud operations at scale. - Merchant trust is becoming a competitive advantage in e-commerce
Poor online shopping experiences damage overall consumer confidence, increasing cart abandonment and reducing transaction approval rates even for legitimate businesses. - Real-time merchant reputation scoring may become standard
The ability to assess merchant risk dynamically during onboarding and payment processing could become a foundational layer across acquiring banks, payment gateways, and digital marketplaces globally. - Cross-border e-commerce fraud remains a growing concern
As international online selling expands, networks are under pressure to identify high-risk merchants operating across multiple jurisdictions and payment ecosystems more rapidly.
