Announcing Feedzai Risk Ledger: Leveraging Federated Data to Find and Prevent Financial Crime at Scale

Feedzai announced today the release of Risk Ledger: financial crime prevention at scale using secure, federated data from Feedzai’s diverse customer base and third-party vendors. While siloed data solutions can miss illicit activity due to limited visibility, Risk Ledger makes it possible to find and stop risk earlier by detecting otherwise unnoticed fraudsters using one of the most integrated data consortia in the industry. This enables more comprehensive, timely, and accurate detection that lowers false positives. Risk Ledger has been shown to neutralize repeat fraudsters up to 5 months earlier compared to traditional methods, resulting in a significant improvement in money recall.

Risk Ledger’s capacity to effectively prevent fraud and money laundering is rooted in the diversity of the data. Feedzai processes $5 billion of transactions every day across more than 200 countries and territories and more than 100 different payments schemes from traditional to digital payments methods. The unique combination of billions of online and offline data elements (e.g. emails, IPs, cards, merchants, terminals and their connections) observed along the entire customer lifecycle (account opening, account monitoring, transactions, and compliance), ensures one-of-a-kind protection for the entire ecosystem: Issuers, Networks, Acquirers, and Merchants.

Image 1: Without Risk Ledger

Image 2: With Risk Ledger


Risk Ledger brings Feedzai’s battle-proven omni-channel risk engine to new frontiers. As the participants contribute pseudonymized and aggregated data in real time or in batch, Feedzai Risk Ledger maintains a knowledge graph along with global Segment of One profiles, which can total 150 billion data points for a single nationwide bank. The machine-learning-first approach provides a fertile ground for advanced algorithms, such as uncovering common points of compromise, while secure and private by design architecture ensures regulatory compliance, including GDPR.

  • Privacy and data security

    • All personal data is pseudonymized and pre-aggregated into profiles, meaning no sensitive information is shared among participants.

  • Data diversity

    • While many data consortia are limited to a single industry or use case, making it impossible to see new threats, Risk Ledger uses data across verticals and use cases to find and prevent far more illicit activity.

  • Powered by machine learning

    • Risk Ledger feeds into Feedzai’s machine learning platform to preserve important consortium insights while adapting to the needs of individual customer companies.

“Our goal has always been to make it harder and harder for fraudsters to hide, while making it easier for businesses to serve their loyal customers without friction,“ says Saurabh Bajaj, Feedzai’s Head of Product. “As our customer base across the world continues to grow, the network effect of all of that data will only make Risk Ledger stronger.”

Risk Ledger follows the recent release of Genome, another tool that uses graphic link analysis on top of Feedzai’s advanced AI platform to find networks and patterns of fraud more effectively and faster than ever before. Risk Ledger plugs directly into Genome, supercharging fraud analysts’ workflows. Financial crime has evolved into highly complex fraud and money laundering rings, operated in cross-channel attacks that can leave any one channel helpless. Feedzai is committed to bringing solutions to banks and other financial institutions across the world to more effectively find and prevent this increasingly sophisticated crime.

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