Customs tariff classification is pivotal in international trade, as it determines the duties and taxes applicable on cross-border movement of goods.
Traditionally, this process has been manual, leading to inaccuracies and penalties for non-compliance arising from variations in interpretation and ambiguity in goods descriptions.
The manual and time-intensive nature of cross-checking items against the harmonised system (HS) further exacerbates these challenges.
Strategic advancements in technology have emerged as essential solutions for effective tariff classification.
Key technologies leading this evolution include a machine learning (ML)-based harmonised keyword search engine, an artificial intelligence (AI) document processing tool for effective data extraction from invoices, and blockchain technology that provides a secure foundation for information processing.
Customs documentation should be correct, comprehensive, readable, and consistent for successful tariff classification. The immutability and additional security provided by blockchain technology fosters confidence and improves customs procedures by lowering fraud and increasing transparency.
These technologies allow importers to swiftly retrieve HS codes, accurately classify products, and ensure compliance with customs regulations, facilitating smoother international trade operations.
Companies and tax authorities can significantly simplify their administrative processes by emphasisng data digitisation through AI document processing and automated data extraction from PDF documents.
Reduced data loss and smooth data retrieval create an extensive digital trail of relevant records and transactions. This enhances taxpayers’ compliance and reduces the burden of data and documentation retrieval during tax audits by the revenue authorities. The application of AI-powered solutions extends beyond customs procedures, transforming various aspects of tax administration.
For instance, AI has revolutionised the audit process within the tax and accounting profession. Traditionally, audit involved manual reviewing of financial data, which was time-consuming and prone to human errors.
However, with the advent of AI-powered audit software, the process has become more efficient and accurate, with the algorithms analysing vast amounts of financial data, identifying potential risks and flagging suspicious transactions.
By leveraging on AI, tax and audit professionals can instil greater confidence in the accuracy of financial statements.
Accurate classification depends on the seamless operation of warehouse control systems that ensure all relevant records are easily available.
Tracking and storing items is made easier by modern warehouse technologies like barcode scanners and computerised inventory systems.
Integrated systems further enhance efficiency by easing data interchange between categorization databases and warehouse management systems. This lowers the possibilities of errors by bridging the gap between warehouse operation and goods classifications.
Adoption of robust data digitisation, Artificial Intelligence, Machine Learning, and advanced warehouse control systems creates a digital audit trail that allows for easier verification and improved Customs compliance.
This intelligent fusion of various systems transforms customs procedures, improving precision and minimizing the risk of errors in global trade.
In summary, these technology solutions aim to pre-emptively address challenges in Customs administration by transforming administrative procedures, improving efficiency, and minimizing the risk of errors in global trade.
The deliberate and strategic implementation of these technologies enhances precision, compliance, and transparency. Additionally, adoption of technology solutions instils confidence and fortifies businesses against potential setbacks in the Customs arena.
Maureen Maina is a Tax and Regulatory Associate with KPMG Advisory Services Limited ([email protected]). The views and opinions are those of the author and do not necessarily represent the views and opinions of KPMG.
