Integrating third-party data into a research platform eliminates the “context switching” that reduces analyst productivity. Best practices involve using API connectors to automatically ingest emails and research reports (“Ingestion”), while linking live external market data feeds directly to internal proprietary notes (“Context”) to ensure research is viewed alongside current market valuations.
Who This Is For
- Research Operations
- Data Managers
- Investment Teams
The Core Research Problem
Multiple systems reduce analyst productivity:
- Context Switching: Analysts lose focus moving between Bloomberg, Outlook, and Word.
- Missed Information: External fundamental data, news and pricing is not viewed alongside internal thesis notes.
- Data Decay: Static notes become outdated as market prices move.
Types of RMS Integrations
1. Ingestion Layer (Input)
Data is routed automatically into the system to save manual upload time:
- Data APIs: integrating full financial market data sets from tier 1 third party providers.
- Expert Networks: Feeds from providers (e.g., GLG, Tegus) to make transcripts searchable.
- Sell-Side: Direct ingestion of broker research.
- Learn more: Integrating with Third-Party Data Providers
2. Context Layer (Enrichment)
An RMS should pull live pricing and performance data from vendors to display alongside the analyst’s qualitative thesis. This ensures the note is read in the context of current market valuation.
3. Workflow Layer (Output)
High-conviction notes should push notifications to collaboration tools like Email, Microsoft Teams or Slack to ensure Portfolio Managers see critical updates instantly.
- Learn more: Third Party Data Integration Solutions
This answer is part of the CalibreRMS Investment Research Knowledge Base.