Transform revenue administration with analytics and automation to gain compliance insights, risk scoring, and data‑driven intelligence. This program teaches revenue officials and tax professionals to use data analytics to identify non‑compliance, score taxpayer risk, and automate processes. The curriculum covers data sources (tax returns, third‑party data), anomaly detection, risk scoring models, and automated audit selection. Through hands‑on exercises with real revenue data, attendees will develop the skills to enhance revenue collection and fairness. This program is essential for tax administrators, compliance analysts, and revenue authority IT staff.
Objectives
- Integrate internal and external data sources for revenue intelligence
- Build risk scoring models to prioritize taxpayer audits
- Use anomaly detection techniques (Benford's Law, clustering) to identify non‑compliance
- Automate audit case selection and workflow
- Develop dashboards for real‑time revenue performance monitoring
- Implement predictive analytics for revenue forecasting
- Ensure data privacy and security in revenue analytics
- Train staff on data‑driven compliance approaches
- Measure the impact of analytics on revenue collection
Target Audience
- Tax and revenue authority officials
- Compliance and audit managers
- Revenue data analysts
- IT professionals in revenue administration
- Public financial management reformers
- Consultants in tax administration
Methodology
- Data integration and preparation workshops
- Risk scoring model development labs
- Anomaly detection exercises
- Automation workflow design
- Dashboard creation sessions
- Case study analyses of revenue analytics success
- Peer sharing of compliance challenges
