Handbook of Customs Risk Management with Data and AI: Practical Methods, Python Applications, and AI for Operational Readiness (en Inglés) - François Bertrand Akoa

Customs administrations already have the data. The real challenge is turning it into decisions that officers can act on, traders can understand and contest, and auditors can reconstruct. Many analytics books stop at model accuracy. In customs, that is where the work begins.

This handbook covers the whole path from data to decision. It brings together customs risk management, statistics, machine learning, explainability, governance and deployment around one central principle: a score is not a decision. Across thirty chapters, the reader moves from data quality and mirror-trade analysis to risk scoring, calibration, drift monitoring and production deployment under the EU AI Act, with each method tied to targeting, selectivity and control.

Key Features

Written for customs leaders, risk managers, analysts, data scientists, policymakers and students, this handbook is both an implementation guide and a strategic reference. Its argument is practical: value comes not from more sophisticated models, but from decisions that can be measured, defended and, when the evidence changes, overturned.

This book is supported by additional online materials which include a synthetic customs dataset, a data generator, Python notebooks, figure-reproduction scripts, supporting templates, environment requirements, and reader instructions.