Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Duration 14 hours
Course Outline
Introduction to WrenAI for Financial Analytics
- Core features and value propositions for finance teams.
- Comparative analysis with traditional BI tools.
- Specific use cases within the finance domain.
Financial Data Modeling in WrenAI
- Defining KPIs for financial performance.
- Standardized metrics for FP & A and risk analysis.
- Management of financial data sources.
Regulatory and Audit Considerations
- Compliance frameworks in financial reporting.
- Dashboard design principles that support auditing.
- Ensuring data integrity and traceability.
Designing Regulatory-Aware Dashboards
- Constructing dashboards for risk management.
- Incorporating compliance checks and annotations.
- User roles and access control mechanisms in finance dashboards.
Integration with Finance Systems
- Connecting WrenAI to ERP and accounting platforms.
- Real-time data updates for financial reporting.
- Management of data refresh cycles.
Advanced KPI Modeling
- Scenario-based financial modeling.
- Forecasting using AI-driven metrics.
- Stress testing for risk assessment.
Monitoring and Governance
- Usage tracking and audit logging.
- Regulatory reporting workflows.
- Best practices for governance in financial analytics.
The Future of WrenAI in Financial Analytics
- AI-assisted regulatory reporting.
- Emerging compliance requirements.
- Expanding financial use cases for WrenAI.
Summary and Next Steps
Requirements
- Foundational knowledge of financial reporting and KPIs.
- Proficiency with data analysis or BI tools.
- Understanding of regulatory compliance in the financial sector.
Target Audience
- Finance analytics teams.
- FP & A professionals.
- Risk analysts.
