Feedzai opens $9 trillion fraud intelligence network to every bank, delivering 4x improvement in fraud detection from day one. new product June 09, 2026 Delivered through a single API and available on AWS Marketplace, Feedzai IQ Score gives banks of all sizes access to network-derived intelligence to stop fraud and scams in real time. NEW YORK and LISBON, Portugal, June 9, 2026 /PRNewswire/ - Feedzai, the global leader in AI-native financial crime prevention, today announced the availability of Feedzai IQ Score, an AI-native, network-derived fraud risk scoring solution for banks of all sizes. Feedzai IQ Score marks a fundamental shift in how fraud is detected. Financial institutions today face a growing "Silo and Legacy Paradox," meaning data used to prevent fraud is restricted to internal sources, and replacing existing end-to-end risk infrastructure can be time consuming and disruptive. As fraudsters become ever more creative, routinely attacking banks via multiple channels and with increasing sophistication, a limited view of data is no longer a defensible strategy. Delivered through a lightweight API integration, Feedzai IQ Score gives banks real-time access to anonymized, aggregated insights from Feedzai's $9 trillion global transaction network. There is no historical data requirement for banks, no lengthy model training process, and no heavy operational lift. Institutions can move from integration through to value realization in days using expert AI models that are already trained and validated across Feedzai's network. Network-derived fraud risk scoring is especially significant for regional and mid-sized financial institutions that often lack the internal data volume or AI resources needed to build sophisticated fraud models independently. With Feedzai IQ Score, these institutions can tap into anonymized, network-level intelligence, while keeping customer data private and secure. Feedzai's federated intelligence architecture ensures that intelligence travels across the network without customer data. "Fraud has outpaced what any single institution can stop alone," said Pedro Barata, Chief Product Officer at Feedzai. "Feedzai IQ Score puts an end to isolated defense by giving banks access to collective insights from across our entire network. Today, we open up this product to institutions of all sizes who now have a ready-made way to make smarter fraud decisions and modernize their defenses without the disruption of fully overhauling infrastructure." Feedzai IQ Score delivers immediate impact and rapid time-to-value: * Proven detection gains: 4x more fraud detected and 50% fewer alerts compared to traditional rules-based approaches. * Operational speed: For a faster payment use case, institutions need as few as 15 data fields to begin benefiting from the solution. * Aggregated, anonymized insights: Feedzai's federated learning model shares aggregated risk signals from across the network, never raw or sensitive customer data. Unlike consortium-based approaches, there is no compliance risk and no data trade-off. "Network fraud intelligence sharing is becoming increasingly important in the monitoring of fragmented fraud signals within the financial ecosystem," said Philip Mackenzie, Senior Research Principal at Chartis. "We considered this capability to be a key differentiator of Feedzai's IQ Score solution, which combines real-time cross-institutional fraud insights and collective intelligence across a range of financial institutions." About Feedzai Feedzai powers trust in global finance. Australian Associated Press protect people and payments using trusted AI to detect and prevent financial crime, fraud, and money laundering in real time, so money moves safely. Every year, the world's top banks, payment networks, and acquirers use Feedzai's technology to safeguard more than one billion consumers and $9 trillion in payment volume. Learn more at feedzai.com.

Feedzai launches RiskFM to enhance financial crime detection. * Financial crime and fraud prevention specialist Feedzai unveiled its RiskFM (Risk Foundational Model) solution this week. * RiskFM covers a broad range of financial data to provide risk decisioning across fraud detection, anti-money laundering, and other financial crime. * Headquartered in New York and founded in 2008, Feedzai made its Finovate debut at FinovateEurope 2014 in London. Financial crime prevention innovator Feedzai introduced its RiskFM (Risk Foundational Model) solution this week. The new offering leverages a Tabular Foundation Model that is purpose-built for financial data and risk decisioning, changing the way that financial crime is detected and prevented. Spanning across fraud detection, anti-money laundering (AML), and other financial crime-related risk decisions, RiskFM is trained on a broad, deep, global dataset covering onboarding, digital activity, payments, fund transfers, and AML workflows to enable institutions to identify, prevent, and adapt to financial crime quickly and accurately. The solution is designed to handle some of the special challenges of dealing with transactional data. In their statement announcing the new offering, Feedzai compared this challenge with large language models (LLMs) and their ability to deal with domains such as language, audio, and video. These domains, the company noted, all have finite grammar and a certain linear causality. By contrast, financial transactions are far less predictive, in large part because the consumer behavior behind these transactions, from payment types to fraud modalities, can and does change - frequently. "Next transactions are far less predictable than the next word in a sentence," Feedzai Chief Science Officer Pedro Bizarro said. "Consumer spending habits, payment types, and fraud modes change continuously. More importantly, financial risk is an adversarial domain; fraudsters actively adapt to evade detection in real time." The ability to operate across multiple institutions and geographies at the same time is one key feature of RiskFM, and when used to power a customized model for a single customer, RiskFM matches the performance of high-tuned, supervised models while avoiding time-consuming, manual feature engineering. RiskFM outperformed traditional models based on Gradient Boosting and Deep Learning strategies, and is built for the full range of financial crime prevention, from mule account detection to anti-money laundering. The company refers to the technology as the "foundational AI layer for financial risk," ensuring institutions have an intelligent, scalable solution that grows as they do. "RiskFM proves our multi-year investment in foundation models is paying off," Feedzai Chief Product Officer Pedro Barata said. "We're not just part of the conversation; we're defining how it applies to the complexities of global financial crime prevention." Feedzai made its Finovate debut at FinovateEurope 2014. Headquartered in New York and founded in 2008, Feedzai today offers an AI-native financial crime prevention platform that helps banks, payment networks, acquirers, and other financial services providers detect and prevent financial crime, fraud, and money laundering in real time. The company's platform serves more than one billion consumers, processes 90 billion events, and secures $9 trillion in payment volume annually. In the wake of its RiskFM announcement, the company since reported that it has been named to Fast Company's World's Most Innovative Companies 2026 roster. "We at Feedzai are honored by this prestigious recognition of our innovation and research in trusted AI to build a world of safer money," Feedzai Co-Founder and CEO Nuno Sebastiao said.

Feedzai has unveiled RiskFM, the financial services industry's first Tabular Foundation Model designed specifically for financial crime prevention. The AI model addresses fraud detection, anti-money laundering and risk decisioning across the entire financial crime lifecycle. Unlike traditional rules-based systems or narrow models limited to card network data, RiskFM is trained on global datasets spanning onboarding, digital activity, payments, transfers and AML workflows. The model tackles the unique challenge of transactional data, where spending patterns and fraud methods continuously evolve in an adversarial environment. Feedzai processes $9 trillion in payments annually across 120 billion events worldwide, providing the breadth of data needed to train RiskFM as a comprehensive model rather than a specialised application. The company describes the launch as a fundamental shift from manually-engineered, customer-specific machine learning models.