ICMLC 2026 will be held in Nanjing, China on February 06-09, 2026. The ICMLC 2026 organizing committees invite you to submit the papers to special session. Each special session will be arranged for around 2 hours on Feb. 07 or 08's afternoon. Now the information on special session as following:

Topic: Predictive Analytic and Machine Learning for Real Time Fraud-theory and Practice

Organizer | 组织者

 

Introduction

The migration of commerce, banking, healthcare, and public services to always-on digital channels has turned real-time fraud into a multi-billion-dollar problem that erodes consumer trust and destabilises markets. Classical rule-based defences are too slow and brittle to cope with adversaries that adapt within minutes. Recent breakthroughs in predictive analytics, streaming machine learning, graph mining, and privacy-preserving computation now make it possible to detect—and even pre-empt—fraudulent behaviour while a transaction is still in flight. This special session provides a focused forum for researchers and practitioners who are closing the gap between offline proof-of-concept models and production-grade systems that must score thousands of events per second with sub-100 ms latency, withstand concept drift, and satisfy regulatory constraints. We invite contributions that advance the theoretical foundations of real-time fraud detection and, equally important, demonstrate how those theories survive the harsh operational realities of scale, adversarial manipulation, and evolving governance frameworks.

 

Scope of the Session

Streaming & Online Learning
Ultra-Low-Latency Scoring
Graph & Relational Learning
Adversarial & Explainable ML
Federated & Privacy-Preserving Analytics
Hybrid Human-AI Systems
Domain-Specific Fraud Problems
Governance, Risk & Compliance
Deployment & MLOps Case Studies
Emerging Paradigms

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Welcome to submit more proposal on ICMLC 2026 special session, please download:
 Proposals Submission Guidelines.

Learn more details or submit the proposal, please contact us:
Ms. Doris Ge
Email: icmlc@vip.126.com
Tel: +86-13709044746