Handbook of Customs Risk Management with Data and AI
Practical Methods, Python Applications, and AI for Operational Readiness
This book provides a practical and structured approach to customs risk management in the age of data and artificial intelligence. It shows how operational data can be transformed into decision-support tools to improve targeting, measure control effectiveness, strengthen compliance and facilitate legitimate trade.
Using realistic customs scenarios, the book covers the full analytical lifecycle: data quality and preparation, risk indicators, profiling, machine learning, model evaluation, explainability, anomaly detection, governance and production monitoring.
Designed for customs administrations, analysts, policymakers, researchers and digital transformation professionals, it emphasizes useful, measurable and well-governed artificial intelligence that supports — rather than replaces — customs decision-making.