27
6.3 EXPANDED SARS MODERNISATION EXPERIENCE STATEMENT: ARCHITECTURAL AND DESIGN GUIDANCE FOR THE INTELLIGENT TAX ADMINISTRATION PLATFORM
1. Unique Digital Identity (UDI) and Secure Access Layer: » Implement a federated identity system drawing from EU EES biometrics (fingerprints, facial scans) and multi-factor authentication (2FA), integrated with national registers (e.g., Department of Home Affairs for population data, Companies and Intellectual Property Commission for business entities, Master of the High Court for trusts, Deeds Office for title deeds, etc). The single digital identity must reveal beneficial ownership to pierce corporate veils and prevent fraud. » Architecture: Use “OpenID Connect” protocols such as via API gateways for secure, role-based access. Taxpayers access a unified dashboard (similar to IRAS myTax Portal) for self-service views of accounts, updates, and query resolutions, and compliance actions. Staff similarly to gain mirrored views with appropriate delegated authority,
As the Chief Architect of Product and Process at the South African Revenue Service (SARS), this expanded experience statement builds upon the original modernisation vision to provide a unified, actionable blueprint for transforming the Tax Administration Platform into an intelligent, AI-infused digital ecosystem. Drawing from global best practices—such as Singapore’s Inland Revenue Authority of Singapore (IRAS) myTax Portal for seamless digital taxpayer services, Australia’s Australian Taxation Office (ATO) AI-driven compliance models for risk assessment and transparency, the International Monetary Fund’s (IMF) Compliance Risk Management (CRM) frameworks for data-driven revenue optimisation, the European Union’s (EU) Smart Borders Entry/Exit System (EES) for biometric-enabled seamless border management, and Singapore’s TradeNet for single-window trade facilitation—this statement integrates architectural principles, design guidelines, and an overarching programme to foster trust, efficiency, transparency, and voluntary compliance. The platform will shift SARS from a declaration-dependent model to a proactive, entity-based ecosystem that anticipates taxpayer needs, minimises compliance burdens, and ensures responsible and ethical enforcement. Taxpayers (including individuals, businesses, traders, intermediaries, and representatives) will experience intuitive, self-reliant interactions where obligations are clear, efforts are minimal, and resolutions are timely and proactive. SARS will assume the majority of the compliance workload through automation, while maintaining a credible threat of detection for non-compliance. 6.3.1 ARCHITECTURAL GUIDANCE: CORE PRINCIPLES AND COMPONENTS The architecture adopts a modular, cloud-native design inspired by countries like Singapore’s IRAS, which emphasises scalable APIs for digital integration and user-centric portals. It will be built on a hybrid cloud infrastructure (e.g. AWS/Azure equivalents) for high availability >99.9% uptime, with micro-services for flexibility, ensuring compliance with South African legislation like the Tax Administration Act, Customs & Excise Acts, and Protection of Personal Information Act (POPIA), etc. Key architectural pillars include:
supported by effective audit trails for governance, accountability and performance management
2.
Entity-Based Compliance Engine: » Shift to real-time risk profiling inspired by best-in-class frameworks, where economic activities (structured data from transactions, unstructured from social media) trigger risks to compliance and increasingly provide auto- assessments rather than declarations to reconcile a tax account. Embed big data analytics and AI to go beyond individual taxes, to also auto-assess VAT and minor taxes, connecting to trusted third party data sources (stocks and flows), as well as the economic value-chain points like point-of-sale (POS) systems. » Architecture: A central “engine” using event-driven micro-services and graphic databases to model entity relationships, enabling proactive compliance checks and fraud detection with >90% accuracy, drawing from examples such as the ATO’s AI risk models.
SARS Modernisation White Paper 2025/26 – 2029/30
Made with FlippingBook - PDF hosting