Financial Market Data: Examples, Providers & Datasets to Buy
On This Page:
- Overview
- Datasets
- Providers
- Use Cases
- Attributes
- Guide
- FAQ
On This Page:
- Overview
- Datasets
- Providers
- Use Cases
- Attributes
- Guide
- FAQ
What is Financial Data?
Financial data is any numeric information or metric that helps you evaluate and research current economic conditions, so that you can make informed decisions regarding investments, business expansion, private stock trading, product pricing, and more.
These financial insights include consumer data that can help your business monitor quarterly performance and adjust marketing strategies, real-time stock data that helps you determine investments and predict trends, and economic performance data showing past and present market performance.
Many financial data providers support API integration, making it simple to incorporate it into your existing systems and customize the way the data is displayed.
What Are Examples of Financial Data?
Financial data plays a pivotal role in analyzing and understanding market dynamics, enabling businesses, investors, and analysts to make well-informed decisions. Key examples include:
- Stock Market Data: Includes stock prices, trade volumes, and market indices, providing insights into equity markets.
- Currency Data: Tracks exchange rates and currency values, essential for international trade and forex trading.
- Economic Data: Macro-level insights such as GDP, unemployment rates, and inflation, which shape economic strategies.
- Corporate Data: Data related to company operations, governance, and financial performance for business insights.
- Alternative Data: Non-traditional data sources like web traffic, satellite imagery, or social sentiment, offering unique market insights.
- ESG Data: Environmental, Social, and Governance metrics for sustainable investing and corporate responsibility analysis.
- Commodity Data: Insights into raw materials like oil, gold, and agricultural products, crucial for trading and market analysis.
Editor's Pick
Best Financial Databases & Datasets
Datarade offers a wide range of financial datasets, from mortgage and homeownership data to ESG investing data, as well as broader historical financial data. While some data products are designed for a specific use case, others serve multiple purposes—for example, an ETF dataset can facilitate portfolio analysis, stock valuation, and corporate financial analytics.
Datasets with multiple applications simplify financial due diligence in both current and future markets. The more use cases a dataset offers, the better it can be tailored to your operations. For instance, some datasets may cover physical and cryptocurrencies alongside equity and stock data.
Company Financial Data | European Financial Professionals | 170M+ Professional Profiles | Verified Accuracy | Best Price Guarantee
Car Ownership Data, (Income, Financial Data, etc), USA, CCPA Compliant
Historical Financial Data For 230M Companies Worldwide
HitHorizons | Company Financial Data | API | CSV | JSON | 80M+ Companies | 50 European Countries | Data Enrichment | GDPR-Compliant | Monthly Updated
Mortgage Data | Homeownership Data | Financial Services | Lender Data
Coresignal | Company Financial Data | Alternative Data | Global / 1B+ Records / Largest Professional Network / Updated Daily
Snapbizz FMCG Financial Data| POS Transaction Data
Company Financial Data | Multi-Source Docs | Extraction & Structuring (100+ Languages, 5K Docs/Hour) | Standardized Outputs | Compliance & Analysis
Overhead Costs | Expenditures | Company Financial Data | Cost Optimization | Budget Planning | Benchmarking | Operations | Controlling | Finance
Transact Consumer Financial Data for Hedge Fund Investors | USA Data | 100M+ Cards, 12K+ Merchants, 800+ Parent Companies, 600+ Tickers
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Top Financial Data Providers & Companies
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Smart Insider
CoverageUSAUK+247Smart Insider: Global leader in Insider Data. We cover 90% of global market cap for over 55,000 listed stocks. Our investment-grade data, scrutinised by our analysts, ensures accuracy, and includes derived fields for in-depth analysis, on insider trades, corporate buybacks, and director changes.95%Global Coverage25 yearsHistoric DataReal TimeData Reporting -
FIDA
CoverageUKGermany+49FIDA is a technology driven Italian company with offices in Torino, Milano and Paris, that develops applications for wealth managers, private bankers, asset managers and Fintech companies. The company provides extensive Fund and ETF data as well as ESG portfolio analysis and global market data.FlexibleAccess the data that you needReactivityAdress data questions promptlyFair priceNo unexpected data bills -
Kaiko
CoverageUSAUK+248VKaiko has an excellent product offering across exchanges and derivative exchanges such as deribit which set it apart from other data providers. Their customer service is top tier, and I can't thank the team enough for helping me debug or help me pull data i was looking. The ability to slack them anytime with questions really set them apart in my mind
Popular Use Cases for Financial Data
Financial data is universally relevant; every industry benefits from access to it. Access to these figures is integral to asset management, consumer insights, and researching fellow market players.
The most common uses of financial market data are:
- Account-based marketing — prioritizing leads to focus on based on their financial profile.
- Hedge fund management.
- Investor research.
- Business credit scoring, as a form of risk analysis.
- Currency and stock trading.
- Asset portfolio analysis.
- Performing financial due diligence to assess ESG or other business risks before an acquisition.
- Identity resolution — linking different sets of customer data together to find relationships between them.
Main Attributes of Financial Data
Data attributes refer to the types of information included in the datasets you purchase. This can be demographic or descriptive information, such as:
- Company name
- Contact first/last name
- Company email address
- Industry
- Credit scores
- Address/city/state
The more attributes are included in datasets, the easier it is to draw conclusions about relationships between different factors. Your financial data should always include the names and locations of data points, as well as a point of contact.
Then you’ll need attributes directly reflecting whichever use case the data applies to; for example, credit score and reporting year for credit reporting data.
| Attribute | Type | Description | Action |
|---|---|---|---|
| String | The name of a country. | View 81 datasets | |
| String | The name of a company or business, might be the legal or brand name. | View 75 datasets | |
| String | The last name (surname) of a contact. | View 72 datasets | |
| String | The first name of a contact. | View 71 datasets | |
| String | The email address of a company or contact. | View 59 datasets | |
| String | The name of a state. | View 55 datasets |
Why Is Financial Market Data Important?
In addition to the specific use cases for financial market data already discussed, having access to a wide repository of financial information is essential for driving business success.
Competitive Analysis
Access to credit, investment, and economic performance data for competitors in your target market is invaluable for understanding your business’s position. Combining historical and real-time financial data enables more accurate market forecasting and strategic planning. Data related to consumer behavior and trends can also reveal what customers in your niche are searching for, helping you tailor your offerings effectively.
Business intelligence and reporting datasets keep you informed about competitor activity and market shifts, allowing you to respond quickly. Targeted economic data ensures you stay updated on key trends and helps you prioritize company initiatives.
Financial data can also strengthen your internal operations. Datasets related to job markets, diversity, equity, inclusion, and hiring trends provide insights into attracting top talent and building a competitive workforce.
Risk Assessments
Risk assessment data is critical when evaluating investments, partnerships, or acquisitions. ESG (environmental, social, and governance) data, for example, has become increasingly important in ensuring that investments align with ethical and societal values. Aligning with businesses that are both socially and fiscally responsible protects your company’s reputation and promotes sustainable growth.
More broadly, financial risk modeling data can provide a clearer picture of potential partners’ financial health, reducing the risk of overextending resources. It supports more secure investment decisions and effective asset management.
By leveraging financial datasets for competitive analysis and risk assessment, you can position your business for both short-term gains and long-term success.
Frequently Asked Questions
How is the Quality of Financial Data Maintained?
The quality of Financial Data is ensured through rigorous validation processes, such as cross-referencing with reliable sources, monitoring accuracy rates, and filtering out inconsistencies. High-quality datasets often report match rates, regular updates, and adherence to industry standards.
How Frequently is Financial Data Updated?
The update frequency for Financial Data varies by provider and dataset. Some datasets are refreshed daily or weekly, while others update less frequently. When evaluating options, ensure you select a dataset with a frequency that suits your specific use case.
Is Financial Data Secure?
The security of Financial Data is prioritized through compliance with industry standards, including encryption, anonymization, and secure delivery methods like SFTP and APIs. At Datarade, we enforce strict policies, requiring all our providers to adhere to regulations such as GDPR, CCPA, and other relevant data protection standards.
How is Financial Data Delivered?
Financial Data can be delivered in formats such as CSV, JSON, XML, or via APIs, enabling seamless integration into your systems. Delivery frequencies range from real-time updates to scheduled intervals (daily, weekly, monthly, or on-demand). Choose datasets that align with your preferred delivery method and system compatibility for Financial Data.
How Much Does Financial Data Cost?
The cost of Financial Data depends on factors like the datasets size, scope, update frequency, and customization level. Pricing models may include one-off purchases, monthly or yearly subscriptions, or usage-based fees. Many providers offer free samples, allowing you to evaluate the suitability of Financial Data for your needs.
What Are Similar Data Types to Financial Data?
Financial Data is similar to other data types, such as Telecom Data, Environmental Data, Weather Data, B2B Data, and AI Training Data. These related categories are often used together for applications like Account-Based Marketing (ABM) and Hedge Funds.
