Feedzai, a global leader in AI-native financial crime prevention, has unveiled RiskFM, describing it as the industry’s first Tabular Foundation Model purpose-built for financial data and risk decisioning.
The launch addresses a longstanding challenge in financial crime detection. For decades, institutions have relied on rules-based systems and manually engineered machine learning models built on a customer-by-customer basis.
RiskFM represents a fundamental shift in that approach, designed to span fraud detection, anti-money laundering (AML), and broader risk decisions across the entire financial crime lifecycle.
Feedzai is a financial crime prevention company that annually risk-assesses $9tn in payments across 120bn events worldwide. Its platform covers the full financial risk lifecycle, from onboarding and digital activity to card payments and real-time transfers — a breadth of data that the company says uniquely positions it to train and test models at scale.
Unlike existing industry models limited to card network data, RiskFM is trained on a broad and deep global dataset spanning onboarding, digital activity, payments, transfers, and AML workflows. This enables financial institutions to detect, prevent, and adapt to financial crime with greater speed and precision. The model is already demonstrating the ability to match the performance of bespoke supervised models using data from a single customer, and surpasses them when trained across multiple institutions and geographies.
Following rigorous testing, RiskFM delivers three headline capabilities. First, compounding intelligence: when trained across multiple institutions and geographies simultaneously, the model outperforms traditional approaches based on Gradient Boosting and Deep Learning, and continues to improve as it ingests more data. Second, day-one performance: when powering a bespoke model for a single customer, RiskFM matches highly tuned supervised models without the need for manual feature engineering. Third, unified coverage: the model is designed to serve as a foundational AI layer across the full range of financial crime prevention use cases, from mule account detection to AML.
Feedzai is currently working with early adopters to validate initial RiskFM frameworks, with plans to scale these methodologies to large datasets and ultimately integrate them across its full suite of use cases.
Feedzai chief science officer Pedro Bizarro said, “Next transactions are far less predictable than the next word in a sentence. 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.”
IDC research director, risk, financial crime, and compliance Sam Abadir said, “Foundation models have reshaped language, vision, and audio, but financial crime has remained stubbornly resistant to that wave. Feedzai’s RiskFM is a credible attempt to close that gap. The ability to match bespoke supervised models out of the box, without manual feature engineering, has real implications for how institutions think about deployment speed, cost, and coverage across the full financial crime lifecycle, from card fraud to AML. The early performance data is worth watching, as is how the model holds up as it expands into more complex use cases.”
Feedzai chief product officer Pedro Barata said, “Our vision is coming true: this is not just another Large Tabular Model for a single data type. We’ve developed a foundation model for financial data that covers multiple use cases — from cards to real-time payments — and geographies, delivering strong performance from Day One at global scale. RiskFM proves our multi-year investment in foundation models is paying off. We’re not just part of the conversation; we’re defining how it applies to the complexities of global financial crime prevention.”
Lloyds Banking Group business platform lead, economic crime prevention Tom Martin said, “Lloyds Banking Group works collaboratively across the industry to protect consumers from financial crime. We’ve been collaborating with Feedzai for years on AI innovation to give fraud fighters the upper hand against criminals, and RiskFM is an exciting milestone in that journey.”
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