Reversing the trend: Low cost and low risk methods for assuring proper duty payments

Abstract

This paper examines the extent to which commodity classification errors may contribute to customs revenue shortfalls. It identifies the root causes of this chronic problem and the traditional approaches that have been applied to address traditional community classification monitoring and enforcement, with little evidence of success. It then discusses other approaches that are worthy of examination, such as artificial intelligence technologies, to monitor Harmonized System (HS) declarations that affect duty underpayments, commodity data quality, systems integrity, and risk assessment.