TrustScore & TrustSignals: Unlock Seamless Transactions for Acquirers

As the old saying goes, knowledge is power. This is especially true in the fight against fraud for merchant acquirers. But the key question for acquirers is how to access the right data at the right time to prevent fraud, maintain trust with merchants, and ensure growth? That’s where TrustScore and TrustSignals, core components of the Feedzai IQ™ solution, come into play.

Both components are already yielding promising results. Using Feedzai IQ™ TrustScore, an EU-based payment provider experienced a 4x improvement in fraud detection and a 50% reduction in false positive alerts. Meanwhile, acquirers in the Feedzai community have seen a 27% improvement in payment acceptance rates and reduced alerts by 270,000 with Aggregated TrustSignals. 

Using federated learning, Feedzai IQ™ pivots away from traditional data consortium approaches to intelligence-based fraud prevention. In this article, we’ll explore how its underlying components, TrustScore and TrustSignals, not only offer acquirers data-first protection. It also transforms fraud prevention from a cost center to a growth enabler. 

Key Takeaways

• Many merchant acquirers encounter data challenges when implementing their fraud prevention solutions, including heavy volumes of raw data, a lack of historical data, and maintaining privacy.
• Feedzai IQ™, built on its two core components, TrustScore and TrustSignals, aggregates data insights from across the Feedzai Community, protecting data privacy. 
• TrustSignals aggregates segregated customer data based on different attributes (including card BINs, email domains, zip codes), enhancing the Feedzai Community’s collective intelligence.
• TrustScore evaluates fraud scores across multiple models, assessing each model’s contribution using a weighted process. 

How TrustScore Turns Shared Intelligence Into Real-time Protection

Building upon the foundation of TrustSignals, Feedzai’s TrustScore takes collective intelligence to the next level. TrustScore aggregates fraud scores from various customer models. 

But it doesn’t just average them out.

Instead, it dynamically determines each model’s contribution through a periodic, calibrated weighting process, ensuring that the most relevant insights rise to the top. These weights vary depending on the consumer’s fraud labels, resulting in a more tailored approach. This sophisticated aggregation is part of Feedzai IQ™’s  global federated learning approach, which means intelligence is gathered without ever compromising sensitive customer data, thereby ensuring privacy. 

Why Traditional Data Sharing Fails Acquirers

When implementing data into their fraud prevention strategies, many acquirers frequently encounter three key challenges. These include: 

• Overwhelming Volumes of Raw Data: Incorporating collective data into fraud prevention strategies has faced notable hurdles in the past. Take consortium models, for example. While these models aim to pool knowledge, they often rely on raw, unprocessed data that bogs down merchant acquirers. This makes it challenging to standardize insights and apply them universally across the diverse portfolios of different merchants. The sheer volume of raw data, rather than being a benefit, becomes a burden, hindering effective fraud response.
• Lack of Historical Data: Another limitation is the attempt to build robust fraud prevention models without access to historical data. This presents a significant barrier to entry for new acquirers that lack the necessary data infrastructure on day one. This dependency on historical data creates a vicious cycle: new players can’t adequately protect themselves against fraud without data, and they can’t acquire data without being vulnerable to fraud.
• Privacy and Trust Concerns: Sharing sensitive customer data in traditional models carries the risk of exposing proprietary information or even customer relationships to competitors. This competitive tension inadvertently forces acquirers into data silos, preventing them from leveraging a broader network effect against organized, cross-merchant fraud rings, ultimately leaving the entire ecosystem more vulnerable.

“Federated learning flips the traditional data-sharing model on its head. Instead of financial institutions sending sensitive raw data to a central location, Feedzai IQ™ brings the AI to the data.” – Anusha Parisutham, Senior Director of Product at Feedzai.

Feedzai IQ™ Opens a New Era of Collaborative Fraud Intelligence

Feedzai IQ™ delivers a powerful answer to these challenges, built on a foundation of cutting-edge artificial intelligence and network intelligence. Instead of traditional data sharing, where raw information might be commingled, Feedzai IQ™ aggregates insights from across the Feedzai Community, ensuring privacy while building collective intelligence.

TrustScore and TrustSignals are the core components that comprise Feedzai IQ™. Let’s look more closely at each one individually.

What are TrustSignals? Your Early Warning System Against Merchant Fraud

Not all merchants are the same. So, how can merchant acquirers gain key, standardized data insights from across their merchant portfolios? Feedzai’s Acquiring TrustSignals unlocks new insights that help acquirers boost acceptance rates and reduce false positives. 

Imagine a group of doctors, each treating different patients but observing similar symptoms.  Instead of sharing all the confidential patient details and personal information, the doctors contribute anonymized data points and observations to build a secure, shared medical database. In this example, Feedzai acts as the central research facility, analyzing anonymized data points, identifying common medical patterns across multiple patient cases without ever knowing the specific medical history of any single patient. 

Feedzai IQ™ Acquiring TrustSignals serves as the secure collection of merchant (non-medical) information. Here’s how it works in practice.

• Acquiring Risk Signals: Acquiring TrustSignals aggregates segregated customer data and fraud intelligence to extract risk signals. 
• Aggregate Scores: Next, the solution aggregates specific risk scores based on different attributes, including card BIN, email domain, zip code, or country, and calculates a fraud ratio for each of them. These fraud ratios are based on confirmed intelligence and insights shared across the Feedzai Community and are based on established fraud linked to a specific attribute considered against the total number of transactions. 
• Enhanced Risk Strategies: Information is shared via API to Feedzai’s Pulse Risk Engine. Insights are categorized as either fraudulent or non-fraudulent, shared on Case Manager, and fed back into the risk engine, thereby elevating the effectiveness of the Feedzai Community’s intelligence pool.

How TrustScore Turns Shared Intelligence Into Real-time Protection

Building upon the foundation of TrustSignals, Feedzai’s TrustScore takes collective intelligence to the next level. TrustScore aggregates fraud scores from various customer models. 

But it doesn’t just average them out.

Instead, it dynamically determines each model’s contribution through a periodic, calibrated weighting process, ensuring that the most relevant insights rise to the top. These weights vary depending on the consumer’s fraud labels, resulting in a more tailored approach. This sophisticated aggregation is part of Feedzai IQ’s global federated learning approach, which means intelligence is gathered without ever compromising sensitive customer data, thereby ensuring privacy. 

For acquirers, TrustScore offers immediate fraud protection from day one, eliminating the need to build extensive historical data sets. Furthermore, its underlying models continuously refine themselves, adapting in real time to new and evolving fraud patterns, ensuring your defenses are always current and effective.

Key Benefits of Feedzai IQ™ for Acquirers

Supported by TrustSignals and TrustScore, Feedzai IQ™ offers key advantages for merchant acquirers to move beyond basic fraud detection.

• Privacy-preserving intelligence. The federated learning approach at the heart of Feedzai IQ™ aggregates intelligence without ever commingling customer data, ensuring customer privacy. Importantly, this is not a “give to get” system. All clients benefit regardless of their data contribution, directly addressing a significant concern for larger institutions hesitant to share their valuable data without a proportional return for their contribution. This model builds trust and lowers the entry barrier for high-value clients, significantly expanding market reach.
• Immediate protection and continuous refinement. TrustScore offers immediate fraud protection from day one, eliminating the need for an acquirer to build a historical data set.1 The models continuously refine themselves, adapting to new fraud patterns in real-time, ensuring defenses are always current.
• Seamless integration and actionable insights. Acquiring TrustSignals delivers pre-calculated fraud ratios via API, eliminating the need for additional technical effort from the acquirer. Instead of a mountain of data to sift through, acquirers can gain immediate access to actionable insights for fraud prevention. This translates into significant operational efficiencies, reducing the need for heavy data science or infrastructure investments, freeing up valuable internal resources, and accelerating time-to-market for new fraud prevention strategies.

Future-Proofing Your Portfolio with Feedzai IQ™ 

Feedzai IQ™, with its innovative TrustScore and TrustSignals components, represents a significant leap forward for merchant acquirers. By moving beyond the limitations of traditional data-sharing models, it offers enhanced fraud detection, substantially reduced losses, and improved operational efficiency, all while strengthening trust with merchants. 

The ability to provide immediate protection without relying on historical data, coupled with privacy-preserving intelligence and seamless integration, positions Feedzai IQ™ not merely as a fraud prevention tool, but as a strategic asset. It empowers acquirers to onboard new merchants faster, confidently expand into new markets, and ultimately, future-proof their portfolios in the dynamic world of payments.

• Blog: How Feedzai IQ™ Is Redefining Fraud Intelligence
• Solution Guide: Feedzai IQ™ for Acquirer Risk Management
• Webinar: Roadmap to Actionable Intelligence Sharing
• Solution: Feedzai IQ™