Discover Feedzai Research

Applied Research to produce the best financial risk mitigation product in the world.

We don’t just build models. We nurture the environment in which they can adapt faster, defend customers more robustly, and instantly reveal shadows in the global financial network.

100+ patents

50+ peer reviewed papers

1800+ citations

45+ Youtube explainer videos

30+ PhD and master's theses supported

1M+ downloads of 10 open-source packages

Recent Publications

All Publications

Rethinking XAI Evaluation: A Human-Centered Audit of Shapley Benchmarks in High-Stakes Settings

Rethinking XAI Evaluation: A Human-Centered Audit of Shapley Benchmarks in High-Stakes Settings

AI, yet their proliferation into competing formulations has created a fragmented landscape with little consensus on practical deployment. While theoretical differences are well-documented, evaluation remains reliant on quantitative proxies whose alignment with human utility is unverified. In this work, we use a unified amortized framework to isolate semantic differences between eight Shapley variants under the […]

Causal Discovery on Irregular Time Series

Causal Discovery on Irregular Time Series

Causal discovery methods have shown strong performance in temporal systems, but they typically rely on regular and discrete lag structures, limiting their applicability to regularly sampled data. However, many real-world tasks require dealing with irregularly sampled streams of events, such as sensor streams, healthcare data, and financial transactions. In this work, we propose an extension […]

Decoupling Inference from State Updates in Low-Latency Feature Engines via Probabilistic Thinning

Decoupling Inference from State Updates in Low-Latency Feature Engines via Probabilistic Thinning

Streaming data systems increasingly underpin Machine Learning workflows that maintain large numbers of continuously updated aggregations. In production settings, each incoming event typically triggers read-modify-write operations to persistent storage, making high-frequency state updates a dominant source of latency, contention, and operational cost. In this work, we decouple inference from state persistence in streaming Machine Learning […]

The Balance between Nuance and Clarity: Decluttering Tabular Sequential Graphs to Counter Money Laundering

The Balance between Nuance and Clarity: Decluttering Tabular Sequential Graphs to Counter Money Laundering

Money laundering is not only about moving illicit funds, but about hiding the money’s origin and traces to complicate detection. Financial criminals resort to many methods to avoid regulators and legal thresholds. But analysts investigating alerts, dedicated to pin mule accounts and track suspicious transactions daily, also have theirs. Network visualizations can be key in […]

Uncertainty-Aware Systems for Human-AI Collaboration

Uncertainty-Aware Systems for Human-AI Collaboration

Learning to defer (L2D) algorithms improve human-AI collaboration (HAIC) by deferring decisions to human experts when they are more likely to be correct than the AI model. This framework hinges on machine learning (ML) models’ ability to assess their own certainty and that of human experts. L2D struggles in dynamic environments, where distribution shifts impair […]

Feedzai Reaches 100 Filed Patents

Awarded People

Catarina Belém

IST Maria de Lourdes Pintasilgo award, 2021

Fulbright Scholarship, 2021

André Cruz

Outstanding MSc Thesis Award for the best thesis in Computational Intelligence by IEEE Portugal, 2020

Sofia Gomes

Portuguese Women In Tech Awards finalist in the Systems and Network Engineer category, 2021

Francisco Silva

Excellence in Academia Award in the category of Electrical and Computer Engineering by Ordem dos Engenheiros Sul (OERS), 2026

Sérgio Jesus

Winner of the Vencer o Adamastor, for the best work by a young scientist in Portugal in Computer Science / Electrical Engineering, INESC, 2026

Research in Action

Explainers from the researchers solving tomorrow's problems today.

Finding the Truth: No More Compromises

Responsible AI: Identify and Address AI Biases

Latency in Fraud Prevention: Don’t Let the Numbers Fool You

The Feedzai Research Blog

Home to an ongoing series of exciting tales and cool articles, elucidating the latest developments on how our experts combat financial crime through continuous innovation in data visualization, system research, engineering, data science and Artificial Intelligence.

From a Trace to Money Flow: How we built an interactive visualization to uncover money laundering

From a Trace to Money Flow: How we built an interactive visualization to uncover money laundering

Money laundering works by staying invisible. Feedzai’s Money Flow visualization turns scattered transaction traces into a readable map of who moved money, where, and when.

Benchmark It Yourself (BIY): Preparing a Dataset and Benchmarking AI Models for Scatterplot-Related Tasks

Benchmark It Yourself (BIY): Preparing a Dataset and Benchmarking AI Models for Scatterplot-Related Tasks

When we need to visualize and interact with millions, or even just thousands, of individual points while analyzing data, we typically resort to rendering them in the browser using a canvas.

Benchmarking LLMs in Real-World Applications: Pitfalls and Surprises

Benchmarking LLMs in Real-World Applications: Pitfalls and Surprises

“Are newer LLMs better?”, In this post, Jean Vieira Alves and Ferran Pla Fernández explore that question with rigorous benchmarking work. Spoiler/hint: recall Betteridge’s law of headlines (“Any headline that ends in a question mark can be answered by the word no.”)

Causal Concept-Based Explanations

Causal Concept-Based Explanations

Over the years, we have evolved from using simple, often rule-based algorithms to sophisticated machine learning models. These models are incredibly good at finding patterns in large datasets, but due to their complexity it is frequently challenging for a human to understand why a certain input leads to its respective output. This is especially problematic in areas where high-stakes decisions are being made and where human-AI collaboration is critical.

Paying it Forward:

Open-Source at Feedzai

We give back to the community that makes our work possible. Our open-source packages are used by data scientists and ML engineers worldwide and have had over 1M+ downloads.

FairGBM

FairGBM

An easy-to-use and lightweight fairness-aware ML algorithm with state-of-the-art performance on tabular datasets.

TimeSHAP

TimeSHAP

A model-agnostic, recurrent explainer that builds upon KernelSHAP and extends it to the sequential domain.

Aequitas

Aequitas

A bias auditing and Fair ML toolkit for data scientists, machine learning researchers, and policymakers. Aequitas was started by the Data Science for Social Good Foundation.

AutoVizuA11y

AutoVizuA11y

A React library to automate the creation of accessible data visualizations

Academic Partnerships

Feedzai Research academic partnerships span internships, scholarships, PhD supervision, and university partnerships.

30 MSc and PhD theses supported or co-supervised

Sponsors of the Feedzai Chair of Machine Learning, currently held by Professor Mario A. T. Figueiredo

Sponsors of the Women in Science scholarship program at the University of Lisbon, supporting over 15 MSc and PhD students since 2022

Partnership with the University of Coimbra to sponsor the First Foundation Project

Awards and Recognition of Research Work

World Changing Ideas - Software category finalist, 2021 

Fast Company - World Changing Ideas - AI & Data category finalist, 2021

Fintech Breakthrough Awards - Fraud prevention Innovation of the Year, 2021

Asia Fintech Awards - Regtech of the Year, 2021

The Stack - Tech for Good, 2021

Page printed in October 29, 2026. Please see https://www.feedzai.com/research for the latest version.