Integration Details

Access FactSet's comprehensive financial data platform through flexible integration methods tailored to your infrastructure. Our FactSet integration provides seamless connectivity to market data, fundamentals, estimates, ownership, and real-time pricing across global markets. Whether you need end-of-day analytics or streaming real-time data, we support integration via:

1. FactSet APIs: Direct programmatic access to 100+ FactSet APIs covering fundamentals, pricing, estimates, ownership, portfolio analytics, and entity mapping
2. Snowflake Data Share: Secure, zero-ETL access to FactSet datasets updated hourly with instant availability
3. Databricks Integration: Delta Sharing for both structured and unstructured content including news, transcripts, and filings
4. Custom Data Feeds: SFTP, S3, or direct cloud delivery with flexible formatting options

Our integration maps FactSet identifiers to your existing security master (Bloomberg IDs, CUSIP, SEDOL, ISIN, internal IDs) ensuring seamless data flow across your entire technology stack.

Key Data Categories

Fundamentals & Financials: Access 750+ fundamental data items including income statements, balance sheets, cash flows, derived ratios, and segment data across 80+ years of history

Market Data & Pricing: Real-time and delayed quotes, end-of-day prices, returns, volume, corporate actions, and splits across global equities and fixed income

Estimates & Analytics: Consensus estimates, earnings forecasts, price targets, and analyst recommendations from global research providers

Ownership Data: Institutional ownership, stakeholder positions, float analysis, and 13F filings for equities and fixed income worldwide

Entity & Security Master: FactSet Concordance for identifier mapping and entity resolution, supporting bulk reconciliation of thousands of securities

Portfolio Analytics: Pre-built attribution, risk decomposition, and performance analysis engines accessible via API

FAQs

1. How does the API integration work?

We integrate directly with FactSet's developer APIs, which provide RESTful endpoints for all major data categories. Authentication uses OAuth 2.0 or API keys depending on your FactSet subscription. Data flows directly into your Hedgineer environment where we normalize and map it to your security master. We handle rate limiting, error handling, and automatic retries to ensure reliability. The APIs support both real-time streaming and batch retrieval, so we can optimize for your use case.

2. What's the difference between API, Snowflake, and Databricks integrations?

The API integration is ideal for real-time workflows, custom queries, and interactive applications. Snowflake Data Share provides instant access to large historical datasets without ETL processes—perfect for analytics and backtesting with hourly updates. Databricks integration via Delta Sharing is best for advanced analytics, ML workflows, and processing both structured data and unstructured content like news and transcripts. Many clients use all three: APIs for live trading systems, Snowflake for research, and Databricks for AI/ML initiatives.

3. How do you handle identifier mapping between FactSet and other systems?

We leverage the FactSet Concordance API to map FactSet entity IDs to industry identifiers like Bloomberg Global IDs, CUSIP, SEDOL, ISIN, and your internal security IDs. This service uses machine learning to match entities with high accuracy. We can process bulk mappings of thousands of securities or perform real-time lookups as needed. The mapping persists in your Hedgineer security master, so once a security is mapped, all FactSet data automatically links to your existing positions, orders, and analytics.

4. Can you integrate both real-time and historical data?

Yes, absolutely. For real-time data we use the Real-Time Quotes API which provides streaming prices, quotes, and market data with sub-second latency from 200+ global exchanges. For historical data, we pull from FactSet's time-series APIs or Snowflake shares depending on volume and use case. This allows you to backtest strategies on decades of history while also running live trading systems on current market data—all from a single integrated platform.

5. What happens when FactSet updates or corrects historical data?

FactSet maintains point-in-time data integrity and publishes correction notices when data is revised. We monitor for these updates and can automatically refresh affected datasets in your environment. For critical workflows like performance attribution or compliance reporting, we can configure alerts to notify you when corrections impact your portfolios or analytics. We maintain audit logs of all data updates so you have full transparency into what changed and when.

6. How is data delivery and latency optimized?

We deploy integrations closest to your infrastructure—whether that's co-located servers, cloud regions (AWS, GCP, Azure), or directly within your Snowflake or Databricks instance. For real-time data, we maintain persistent connections to minimize latency. For bulk data, we use parallel processing and incremental updates to reduce load times. FactSet's normalized data structure across 200+ exchanges means we can efficiently cache and index data for fast retrieval. Typical API response times are under 500ms, and Snowflake queries execute in seconds even on billions of rows.