The Single Source of Truth: Thredd and Featurespace Launch ‘One View’ to Revolutionize Cross-Channel Fraud Detection
The payments landscape is fractured, and that fragmentation is costing the financial sector billions. In a world where a customer might use a physical card, a virtual card, or an instant bank transfer—often within minutes—financial institutions (FIs) are struggling to keep pace with the sheer volume, velocity, and complexity of transaction data. Fraudsters thrive in this environment, exploiting the cracks that exist between disparate payment channels. As fintechs and digital banks scale their ambitious offerings, the old approach of managing card fraud in one system and payment fraud (like Account-to-Account or P2P) in another is no longer tenable. It creates operational bottlenecks, blinds fraud analysts to critical behavioral patterns, and ultimately leads to rising fraud losses and poor customer experiences.
The Multi-Channel Payments Reality and the Failure of Siloed Systems
To fully appreciate the necessity of One View, one must first understand the severe challenges of the current multi-channel payments environment. Today’s digital customers interact with their money across numerous, constantly evolving touchpoints: a debit card for online shopping, a virtual corporate card for B2B expenses, and an instant payment app for splitting a restaurant bill or transferring funds via an Open Banking interface.
For a fraud operations team, this variety of instruments presents a nightmare of data silos. Card transactions are processed, monitored, and analyzed via the issuer processor’s platform, often using legacy rule-based engines or a separate, card-centric fraud solution. Crucially, non-card transactions—such as Account-to-Account (A2A) and Person-to-Person (P2P) payments, or those facilitated by Faster Payment rails—are monitored via a different, often proprietary, payment engine. These two systems rarely, if ever, talk to one another effectively.
The Problem: Blind Spots and Operational Friction
This architectural fragmentation leads directly to two major critical flaws in any organization’s fraud defense: severe blind spots for fraud detection and crippling operational inefficiency.
- Fatal Blind Spots for Fraud: The most sophisticated fraud attacks are multi-channel. For example, a fraudster might test a compromised card with a series of small, easily-missed transactions (a form of low-level card fraud) before immediately moving the bulk of a stolen amount to an external ‘mule’ account via an A2A transfer (a form of high-value payment fraud). When these two event types are viewed in isolation—as they are in siloed systems—the card transactions may look like typical low-level testing and the A2A transfer may look like a high-value, but legitimate, single payment. Only when the full sequence of behavior is analyzed in a single, unified view does the coordinated, criminal attack pattern become obvious. The siloed approach literally prevents fraud teams from spotting the entire, context-rich pattern of criminal behavior. It’s like watching two different camera feeds of a crime without being able to synchronize them.
- Crippling Operational Inefficiency: Fraud analysts are forced into a constant state of context-switching, manually logging into and out of multiple user interfaces, cross-referencing alerts from separate rules engines, and attempting to stitch together different reporting formats. This process is time-consuming, mentally taxing, and slows down response times. Every minute lost searching for data across disconnected systems is a minute a fraudster has to complete their crime and disappear. This endemic friction creates a significant strain on internal resources, leading to slower resolution times, increased staff burnout, and ultimately raising the total financial burden of running fraud operations.
Thredd and Featurespace designed One View specifically to collapse these performance-inhibiting silos, ensuring that the technology used to fight financial crime is finally aligned with the complex reality of how money moves and how criminals operate in the digital age.
One View: The Unified Defense Powered by Adaptive AI
The core innovation of One View is its ability to ingest, normalize, and analyze all payment types—card, A2A, and P2P—within a single, unified interface and rules engine. This unified engine is powered by Featurespace’s cutting-edge Artificial Intelligence.
Featurespace’s Adaptive Behavioral Analytics (ABA)
At the heart of One View lies the ARIC™ Risk Hub from Featurespace, a Visa solution. This system is not reliant on static, backward-looking rules (e.g., “Flag any transfer over $5,000”). Instead, it leverages Adaptive Behavioral Analytics (ABA) and advanced machine learning to create a unique, continually evolving, real-time profile of each individual customer’s normal behavior.
The profound power of ABA is that it can identify an anomaly—a statistically significant deviation from a customer’s normal pattern—instantly. This is a crucial defense against the most modern and complex fraud attacks, such as Authorized Push Payment (APP) fraud and social engineering scams, where the activity might look legitimate according to traditional rules (e.g., the transaction amount is ‘normal’, and it passed 3D Secure), but is wildly out of character for the specific customer (e.g., sending money to a never-before-seen beneficiary).
Key Technological Advantages:
- Unified 360° Customer View: By aggregating card and non-card data into a single, cohesive feed, the Featurespace engine can build a far richer and more accurate behavioral profile. For instance, the system can now flag a suspicious chain of events such as a quick sequence of failed card PIN attempts immediately followed by a high-value P2P transfer, a pattern that would be completely missed by isolated monitoring systems.
- Real-Time, Predictive Processing: The solution delivers real-time risk-based scoring for every transaction—often in milliseconds. This speed is non-negotiable for modern payments, allowing FIs to intercede before a fraudulent transaction is authorized and before stolen funds have left the ecosystem.
- API-First, Plug-and-Play Architecture: The solution is designed to be API-first and plug-and-play, meaning clients can go live quickly and see immediate value without extensive upfront training or lengthy, customized integration projects. It is flexible, able to be deployed as a complete replacement for a rigid legacy system or as an augmentation layer to existing infrastructure, providing intelligence across existing card and payment channels. This flexibility significantly accelerates time-to-value for Thredd’s clients.
The Operational Dividend: Transforming Fintech Back-Office Efficiency
The impact of One View extends far beyond simple fraud loss reduction; it fundamentally transforms the operational model for fintechs, digital banks, and payment processors. This platform is not just about protection; it’s about efficiency and customer experience.
- Streamlined Investigation and Reduced Workload
The core benefit for the team is the single, unified interface with consistent workflows and logic across all payment types. This eliminates the need for fraud analysts to constantly “toggle” between separate card and payments systems. This streamlining of investigations cuts resolution times dramatically and significantly reduces the daily operational and psychological strain on fraud teams. As Anthony Gudgeon, Thredd’s Head of Fraud Operations, has emphasized, the ability to spot unusual patterns that isolated systems would miss leads to better overall coverage with less strain on internal resources.
- Fewer False Positives, Enhanced Customer Experience
A major, often-overlooked challenge for any fraud system is the delicate balance between security and customer experience. Overly cautious or rule-heavy fraud systems lead to high rates of false positives—legitimate customer transactions being declined. This creates friction, generates costly customer support calls, and can cause a customer to lose trust and switch providers. The Featurespace machine learning engine is specifically designed to minimize false positives by adapting to a customer’s evolving behavior, ensuring that genuine customers can transact without unnecessary interruption or annoyance.
- The Power of Self-Resolving Alerts and Customer Autonomy
A standout operational feature is the capability for self-resolving alerts. When a suspicious yet uncertain pattern is detected, the platform can automatically send a real-time alert (e.g., via SMS) directly to the customer, allowing them to instantly approve or decline the transaction themselves. This feature immediately shifts the burden of resolution away from the fraud team, effectively eliminating the need for 24/7 manual monitoring and significantly reducing the customer service workload. It’s a powerful two-way win: the customer retains control and autonomy over their finances, and the financial institution saves substantial time and operational costs.
