Fraud Detection Using OpenShift Data Science - A Step-by-Step Guide
Detect fraudulent transactions using AI/ML on OpenShift Data Science. Learn the workflow, partner solutions, and step-by-step implementation for financial institutions.
Near-Optimal Fully Dynamic Densest Subgraph
Explore near-optimal algorithms for dynamic densest subgraph problems, covering applications, definitions, and techniques for efficient graph orientation and load balancing.
How to Secure the Journey to Big Data Microservices - Fraud Management at Arvato
Explore Arvato's secure migration to microservices for fraud detection, featuring Docker containers, data protection compliance, and machine learning integration in a Big Data environment.
Mission Critical Data and Evaluating Open Source Communities in Financial Technology
Explore Apache Cassandra's role in financial institutions, its community revitalization, and applications in real-time payments, fraud detection, and KYC. Includes code examples and demos for hands-on learning.
The Distributed Open Source Graph Database - NebulaGraph
Explore graph databases, their applications, and NebulaGraph's features in this informative talk. Learn about use cases like recommendation systems and fraud detection.
Event Streaming Applications with Kafka - A Live Coding Session
Live coding session on event streaming with Kafka, covering Spring Kafka, Kafka Streams, and Spring Actuator. Learn to create consumers, producers, and streams for scalable, fault-tolerant applications with real-time monitoring.
Under Pressure: Applying Machine Learning in Real-Time Systems
Explore real-time machine learning implementation strategies, from handling low latency requirements to building scalable systems for streaming scenarios in autonomous vehicles, healthcare, and fraud detection.
Crisis Fincrime - Using AI to Combat Financial Crime During Coronavirus
Explore AI-driven strategies to combat financial crime amid the coronavirus crisis, focusing on KYC/KYB verification and fraud prevention in government aid programs.
Crisis Fincrime - Using AI to Combat Financial Crime During Coronavirus
Explore AI-powered strategies to combat financial crime during the coronavirus crisis, focusing on KYC/KYB verification and identity matching techniques.
How to Build a Real-Time ML Pipeline for Fraud Prediction
Build a real-time ML pipeline for fraud prediction, addressing challenges in online feature engineering and real-time data ingestion. Learn to generate ML features, use a feature store, and monitor for drift.
Fraud De-Anonymization for Fun and Profit
Explore innovative techniques for detecting and combating search rank fraud in online systems using deep learning and multi-worker validation approaches.
Doing Good by Fighting Fraud - Ethical Anti-Fraud Systems for Mobile Payments
Explore ethical anti-fraud systems for mobile payments, addressing algorithmic bias and user challenges while examining key metrics and design principles for effective fraud detection.
Approaches to Fraud Detection - Autoencoder and Isolation Forest - Fraud Detection Using ML
Learn fraud detection techniques using KNIME, including random forest, autoencoder, and isolation forest. Explore methods for both labeled and unlabeled data, with practical demonstrations and insights on implementation.
Fraud Detection in Bitcoin Payment Networks
Explore fraud detection in Bitcoin networks using machine learning, covering techniques like deep learning and entity recognition for effective cryptocurrency security.
Fraud Detection and Forensics on Telco Networks
Explore new fraud techniques and attacks exploiting SS7 vulnerabilities in telecom networks, including demonstrations of money transfers from electronic accounts and their impact on payment systems integration.
The Challenges of Deploying Real-time AI for Finance and How Open Source Can Help
Exploring challenges in deploying real-time AI for finance and how open-source solutions like feature stores can address them. Includes case studies and resources for implementing MLOps in fintech.
Decoding Fraud: The Evolution and Impact of Netflix's Fraud Metrics
Explore Netflix's approach to fraud metrics, their impact on strategic decisions, and insights for creating effective security measures against evolving threats.
Real-time Fraud Detection: Challenges and Solutions
Explore real-time fraud detection challenges and solutions using machine learning and the Hazelcast Open Source platform for rapid, scalable decision-making.
Fighting Fraud in the Trenches
Discover practical strategies for combating fraud from the frontlines with insights from an experienced cybersecurity professional.
Detecting White-Collar Cybercrime - SAP Forensics
Explore SAP Forensics techniques for detecting and investigating white-collar cybercrime in enterprise systems, enhancing your ability to secure critical business data and processes.
PoorSKeme - El Esquema de los Pobres
Explora una herramienta Open Source que combina OSINT, visualización de datos y blockchain para detectar anomalías en smart contracts y flujos de wallets, útil para identificación temprana de estafas.