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Course Outline
Introduction to WrenAI for Financial Analytics
- Key features and benefits for finance teams
- Comparison with traditional BI tools
- Finance-specific use cases
Financial Data Modeling in WrenAI
- Defining KPIs for financial performance
- Standardized metrics for FP and A and risk analysis
- Managing financial data sources
Regulatory and Audit Considerations
- Compliance frameworks in financial reporting
- Audit-friendly dashboard design
- Ensuring data integrity and traceability
Designing Regulatory-Aware Dashboards
- Building dashboards for risk management
- Incorporating compliance checks and annotations
- User roles and access control in finance dashboards
Integration with Finance Systems
- Connecting WrenAI to ERP and accounting platforms
- Real-time data updates for financial reporting
- Managing data refresh cycles
Advanced KPI Modeling
- Scenario-based financial modeling
- Forecasting with AI-driven metrics
- Stress testing for risk assessment
Monitoring and Governance
- Usage tracking and audit logs
- Regulatory reporting workflows
- Best practices for governance in financial analytics
Future of WrenAI in Financial Analytics
- AI-assisted regulatory reporting
- Emerging compliance requirements
- Expanding financial use cases for WrenAI
Summary and Next Steps
Requirements
- An understanding of financial reporting and KPIs
- Experience with data analysis or BI tools
- Familiarity with regulatory compliance in finance
Audience
- Finance analytics teams
- FP and A professionals
- Risk analysts
14 Hours
회원 평가 (1)
제가 매우 감사한 점은 강사가 모든 내용을 얼마나 잘 설명했는지입니다. Finance이 제 전공 분야는 아니지만, 모든 참가자가 동일한 페이지에 있도록 했으며, 남은 시간을 유지했습니다. 연습은 적절한 간격에 배치되었습니다. Communication는 참가자들과의 소통은 항상 있었습니다. 자료는 너무 많지도, 적지도 않았습니다. 그는 복잡한 주제를 더 잘 설명하여 모든 사람이 이해할 수 있도록 했습니다.
Diana
Course - ChatGPT for Finance
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