Blockchain, Bitcoin, and VAT in the GCC: The Missing Trader Example
18 Pages Posted: 17 Feb 2017
Date Written: February 16, 2017
Blockchain is coming to tax administration and will cause fundamental change. This article considers the potential for blockchain technology as it applies to the introduction of a value added tax in the Gulf Cooperation Council.
Blockchain technology disrupts centralized ledgers. Blockchain improves efficiency, security and transparency. Perhaps no centralized ledger system presents more challenges than that of the modern tax administration. The central data storage system of a modern tax authority contains all return, payment, and audit activity for all taxpayers arranged tax-by-tax for three years or longer periods of time.
It is likely that blockchain will come first to jurisdictions like the GCC, where there is no pre-existing tax system to be “disrupted.” This is the familiar technological “leap-frog” effect where jurisdictions without an established infrastructure in place can quickly move to new technologies without needing to pass through the entire development process. This is a common occurrence in African economies.
For those who are attentive to the coming blockchain disruption there are some precursor developments already visible. In the restaurant sector, Quebec mandates encryption of transaction data, requires the monthly submission of a digital summary report, performs AI-base risk analysis on the aggregate data streams to identify fraud patterns, and completes most audits remotely. Rwanda has gone further. It implemented a DICE compliance regime for all businesses, and requires full transactional data transmission daily (not just summary reports submitted monthly). Rwanda performs the same AI-based risk analysis for fraud detection. In addition, Rwanda appears ready to adopt a cross-border DICE system with neighboring Tanzania.
Keywords: Bitcoin, Blockchain, GCC, Gulf Cooperation Council, Missing Trade Fraud, MTIC, DICE, Digital Invoice Customs Exchange, VAT, VATCoin, Artificial Intelligence
JEL Classification: F10, K10, K14, K34, K39
Suggested Citation: Suggested Citation