Overview
Everything you need to know about Fundamentals.
The Finvera Fundamentals API delivers structured financial statement data for public companies worldwide. It’s designed for developers building investing tools, financial dashboards, screeners, or analytics platforms that require access to historical and current company financials.
Finvera offers two tiers of coverage:
Fundamentals Lite API
The Fundamentals Lite API delivers clean, standardized financial statement data—income statement, balance sheet, and cash flow statement—for U.S. public companies, parsed directly from SEC XBRL filings. It is optimized for low-latency queries and lightweight integration into financial dashboards, analytics tools, and backtesting environments.
Normalized Output: Maps complex us-gaap XBRL tags into intuitive, flat field names (e.g., us-gaap:Revenues → revenue) for ease of use.
Three Statement Coverage: Returns structured values for ~80 commonly used GAAP fields across income, balance, and cash flow.
JSON Format: Lightweight, developer-friendly payloads with clear period tagging (e.g., fiscal_period, end_date, fiscal_year).
Fast Query Performance: Sub-200ms response targets via PostgreSQL indexing and optimized fact-table schema.
Tickers + CIK Support: Query data by ticker symbol or company CIK.
Example Use Cases
Building investment research dashboards
Financial model backtesting
Time-series visualization for earnings analysis
Mobile portfolio apps with lightweight statement display
Fundamentals Enhanced API
The Fundamentals Enhanced API extends the Lite dataset with derived financial metrics and textual insights extracted from 10-K/10-Q filings. It blends numeric and NLP-enriched fields into a single response—designed for advanced modeling, risk analysis, and machine learning applications.Key Features
Derived Metrics: Includes calculated ratios and performance metrics like ROIC, free cash flow yield, working capital days, revenue per employee, and more.
Text Analysis from Filings:
Risk Factors: Theme extraction, sentiment scoring, and risk count from 10-K risk sections.
MD&A: Tone, forward-looking language ratio, and keyword themes from management commentary.
Litigation Mentions: Surface recent litigation headings from legal disclosures.
Unified JSON Response: Combines Lite fundamentals, derived metrics, and text signals per fiscal period.
Scalable NLP Pipeline: Text sections parsed and scored using deterministic and ML-based methods.
Example Use Cases
Alpha modeling with alternative financial signals
ESG and litigation risk factor screening
Earnings tone and sentiment analysis at scale
Derived metric-based stock screening
API Endpoint Examples:
In conclusion, this API returns structured financial data directly from source filings, without the overhead of parsing raw XBRL. They offer strong performance, scalable architecture, and developer-first schema design.
Schema
Note: Some fields and objects are replaced with ... to improve the readability of the responses in this document.
Perform a search for securities using a symbol or other search criteria.
