Real-time Fraud Detection - Challenges and Solutions

Conference

Room: NT

Scheduled at : Wednesday 10:15 11:15

Abstract

Fraud can be considerably reduced via speed, scalability, and stability. Investigating fraudulent activities, using fraud detection machine learning is crucial where decisions need to be made in microseconds, not seconds or even milliseconds. This becomes more challenging when things get demanding and scaling real-time fraud detection becomes a bottleneck. The talk will address these issues and provide solutions using the Hazelcast Open Source platform.

Fawaz Ghali

Fawaz Ghali

Fawaz Ghali is the Principal Data Science Architect and the Head of Developer Relations at Hazelcast with 20+ years of experience in software development, machine learning and real-time intelligent applications. He holds a PhD in Computer Science and has worked in the private sector as well as Academia as a Researcher and Senior Lecturer. He has published over 46 scientific papers in the fields of machine learning and data science. His strengths and skills lie within the fields of low latency applications, IoT & Edge, distributed systems and cloud technologies.

Speaker's bio
Presentation type Conference, 45mn
Track Cloud & Scaling
Presentation level beginner/novice

Room NT