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Pesquisa Aplicada com o objetivo de entregar o melhor produto do mundo para mitigação de riscos financeiros.
Vamos além da construção de modelos. Nutrimos o ambiente para que eles se adaptem mais rápido, protejam os clientes de forma mais sólida e revelem, em tempo real, pontos cegos no sistema financeiro mundial.
Publicações recentes
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
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
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
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 […]
Responsible AI & The TRUST Framework
Why bother with Responsible AI? What are the tradeoffs? How to get started with Responsible AI? What is the TRUST Framework? In this keynote Pedro presents some context and some misconceptions about Responsible AI and shows how the TRUST Framework can guide the development of Responsible AI systems. Keynote at the Center for Responsible AI Forum 2025
3 áreas de pesquisa. 1 missão.
Os pesquisadores da Feedzai estão dedicados a oferecer a tecnologia mais recente para proteger as finanças no ritmo da vida atual.
Feedzai alcança 100 patentes registradas
Pessoas premiadas
Catarina Belém
Prêmio IST Maria de Lourdes Pintasilgo, 2021
Bolsa Fulbright, 2021
André Cruz
Prêmio de Melhor Dissertação de Mestrado (Outstanding MSc Thesis Award) na área de Inteligência Computacional, concedido pela IEEE Portugal, 2020
Sofia Gomes
Finalista do Prêmio Mulheres Portuguesas na Tecnologia (Portuguese Women in Tech Awards) na categoria de Engenheira de Sistemas e Redes, 2021
Francisco Silva
Prêmio de Excelência Acadêmica (Excellence in Academia Award) na categoria de Engenharia Elétrica e Computacional pela Ordem dos Engenheiros Sul (OERS), 2026
Sérgio Jesus
Vencedor do “Vencer o Adamastor”, pelo melhor trabalho de um jovem cientista em Portugal nas áreas de Ciência da Computação/Engenharia Elétrica, reconhecendo a excelência e os benefícios para a sociedade, 2026
Pesquisa em ação
Explicações de pesquisadores que resolvem hoje os problemas de amanhã.
Encontrando a verdade: sem mais concessões
IA responsável: identificar e abordar vieses de IA
Latência na prevenção de fraudes: não deixe os números enganarem você
O blog da Feedzai Research
Lar de uma série contínua de histórias empolgantes e artigos interessantes, elucidando os últimos desenvolvimentos sobre como nossos especialistas combatem o crime financeiro por meio de inovação contínua em visualização de dados, pesquisa de sistemas, engenharia, ciência de dados e Inteligência Artificial.
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
“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
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.
Feedzai TrustScore: Enabling Network Intelligence to Fight Financial Crime
Detecting financial fraud is like finding a moving needle in a shifting haystack. Fraud accounts for a tiny fraction of financial transactions, often less than 0.1%. At the same time, fraudsters are constantly adapting their tactics to evade detection. And this happens within a live and dynamic environment, where financial behaviors and technologies are changing over time. In short, this is an exceptionally difficult problem for financial institutions.
Compartilhando o conhecimento:
código aberto na Feedzai
Retribuímos à comunidade que torna nosso trabalho possível. Nossos pacotes de código aberto são usados por cientistas de dados e engenheiros de ML em todo o mundo, com mais de 1M+ downloads.
BIY dataset
A synthetic, annotated dataset (and its generation pipeline) for scatterplot-related tasks.
feedzai-altair-theme
Feedzai’s theme for Altair charts.
OpenL2D
A framework designed to realistically simulate expert decisions on any tabular dataset, enabling Human-AI Collaboration research on public datasets.
SARSum
A comprehensiveness and relevance-aware summarization dataset focusing on the development of Suspicious Activity Reports in the course of Anti Money Laundering Investigations.
Parcerias acadêmicas
As parcerias acadêmicas da Feedzai Research abrangem estágios, bolsas de estudo, supervisão de doutorado e parcerias universitárias.
Prêmios e reconhecimento do trabalho de pesquisa
World Changing Ideas - Finalista da categoria Software, 2021
Fast Company — World Changing Ideas — Finalista da categoria IA e dados, 2021
Fintech Breakthrough Awards — Inovação do Ano em prevenção de fraudes, 2021
Asia Fintech Awards — Regtech do ano, 2021
The Stack — Tecnologia para o bem, 2021
Página impressa em 18 de setembro de 2026. Consulte https://www.feedzai.com/pt-br/research/ para obter a versão mais recente.
