Data Insights
1. Data Insights & Business Answers
User Input
- “What’s the current multiple for NVIDIA?”
- “How much liquidity does Fund X have, and when is the next redemption window?”
AI Actions
- Identify key financial concepts
- Search structured (e.g. Snowflake) and unstructured (e.g. PDFs) sources
- Apply business logic and interpretation rules
- Return synthesized, calculated response
Why This Is Revolutionary
- Query Any Source: Ask natural language questions across data lakes.
- Contextual Understanding: Recognize business intent and deliver precise answers.
- Metric Calculation On-the-Fly: Combine data and compute custom metrics instantly.
- One Interface: Eliminate data digging and siloed workflows.
Reporting
2. Executive Reporting
User Input
- Report type (e.g. NAV, compliance summary)
- Portfolio, timeframe, audience
AI Actions
- Generate report using templates
- Format for internal or external use
- Schedule delivery or automate distribution
- Preserve audit trail and versioning
Why This Is Revolutionary
- No More Manual Reporting: Eliminate spreadsheet workflows.
- Instant Distribution: Deliver to executives or regulators with one click.
- Template-Based Output: Ensure formatting and language consistency.
- Fully Auditable: Retain history of all versions and recipients.
Data Quality
3. Data Quality Audits
User Input
- Vendor name or domain
- Sample dataset or data dictionary
- Coverage expectations
AI Actions
- Run automated DQR (Data Quality Report)
- Benchmark vendor coverage and highlight anomalies
- Document compliance-ready reports
- Compare vendors side-by-side
Why This Is Revolutionary
- Standardized Evaluation: Replace manual reviews with automated workflows.
- Faster Procurement: Reduce vendor onboarding time drastically.
- Compliance-Ready: Generate audit documentation automatically.
- Compare at Scale: Evaluate multiple vendors with consistent metrics.
Backtesting
4. Instant Backtesting
User Input
- Test Strategy A across the last 3 years
- Compare Dataset X vs. Dataset Y on signal strength
- Visualize alpha decay or Sharpe changes over time
AI Actions
- Select timeframes, benchmarks, and parameters
- Build and execute backtest logic
- Visualize returns, drawdowns, signal decay, and more
- Explain results in plain language
Why This Is Revolutionary
- Instant Backtesting: Validate signals or datasets in seconds—no coding required.
- Compare Alternatives: Evaluate multiple datasets or strategies at once.
- Explain the 'Why': Understand logic behind results, not just output.
- Visual + Narrative Output: Get clear charts and explanations together.
Strategy Generation
5. Strategy Generation
User Input
- Risk Tolerance (e.g., conservative, balanced, aggressive)
- Asset Classes or Products (equities, ETFs, options, etc.)
- Technical Preferences (momentum, volatility filters, trend indicators)
AI Actions
- Select relevant datasets
- Interpret the inputs
- Assemble strategy logic with constraints
- Recommend strategy components (entry/exit signals, sizing rules, etc.)
Why This Is Revolutionary
- Design and Refine Trading Strategies: Generate and iterate prototypes with real-time feedback.
- Suggest Enhancements Based on Context: Analyze historical and real-time data to evolve strategies.
- Incorporate Learnings From Past Trades: Recommend improvements based on performance patterns.
- Set Alerts: Track execution and highlight risks or new opportunities.
Collaboration
6. Team Collaboration
User Input
- Research prompt or reporting task
- Collaboration request between teams
AI Actions
- Secure prompt sharing inside Symphony
- Role-based access to data and outputs
- Preserve version history and approvals
- Trigger alerts or workflow actions
Why This Is Revolutionary
- Unified Workspace: Central hub for collaboration across research, compliance, data.
- Custom Access Levels: Control who sees what—by role or department.
- Built-In Alerts: Notify stakeholders at key milestones.
- Full Traceability: View who contributed what, when, and why.