Top 10 Questions to Ask Before Selecting a Financial Data Provider

By Intrinio
June 2, 2025

The Hidden Risk in Picking the Wrong Data Partner

Financial data is the backbone of your fintech application, trading platform, research product, or investment strategy. But not all data providers are created equal. Choosing the wrong one can lead to outages, poor performance, regulatory risk, and wasted development time. In today’s market — where agility, speed, and precision are everything — your choice of data partner can make or break your product.

Before signing a contract or integrating an API, it’s critical to dig deeper. Ask the right questions, and you’ll save your team from costly surprises down the line.

What Questions Should You Ask to Evaluate a Potential Financial Data Provider?

1. Do You Offer Real-Time Data, and How “Real-Time” Is It?

“Real-time” can mean a lot of things. Some providers deliver sub-second updates via WebSockets. Others push updates every few seconds or delay feeds by design. Ask for latency benchmarks, delivery methods (REST vs. WebSocket), and whether the provider is redistributing exchange data or calculating their own.

The distinction matters. A delay of just a few seconds could be the difference between capturing an opportunity or missing out. Financial platforms that depend on speed, such as trading terminals and algorithmic systems, need data that updates as close to real-time as possible.

2. What Types of Financial Data Are Included?

Financial professionals need more than just prices. Ask whether the provider includes:

  • Equities
  • Options
  • ETFs
  • Fundamentals
  • Macroeconomic indicators
  • Alternative data
  • News or sentiment feeds

The breadth of data access affects your flexibility and growth potential. Relying on one provider that covers many asset types can eliminate the need for expensive, hard-to-integrate secondary feeds.

3. What’s Your Historical Data Coverage?

You may need real-time data now — but what about historical data for backtesting or training machine learning models? Check for:

  • Depth of history (days, months, years)
  • Granularity (tick-level, minute, daily)
  • Continuity and data integrity

The quality of your models depends on the quality and depth of your historical data. A provider with gaps or inconsistencies in their archives can undermine your analysis and forecasting accuracy.

4. How Reliable and Accurate Is Your Data?

Bad data leads to bad decisions. Ask:

  • What is your data QA process?
  • How do you handle corrections and updates?
  • What’s your historical uptime?

Also ask if the provider sources their data directly or depends on resellers — each extra link in the chain increases the risk of errors or outages.

Accuracy is non-negotiable. One missed split or mispriced option can cascade into misinformed decisions across your platform.

5. How Easy Is It to Integrate Your API?

Developers need clean documentation and tools to move quickly. Ask for:

  • Open API documentation
  • SDKs in Python, R, JavaScript, etc.
  • Sample code
  • Interactive tools like Postman collections or GraphQL sandboxes

A developer-friendly API reduces time to market. You want your engineers building core functionality — not spending weeks figuring out how to parse data feeds.

6. Do You Throttle, Cap, or Limit Access in Real-Time?

Some data providers severely limit how many API calls or concurrent connections you can make. This could throttle your application’s performance. Ask:

  • Is there rate limiting?
  • Are there concurrency limits?
  • How are spikes in usage handled?

If your application is high volume — like a real-time trading dashboard — you’ll need a partner who can support growth without penalizing success.

7. What Is Your Support and Onboarding Process Like?

Great data is worthless if you can’t use it. Ask:

  • Do you have a dedicated account manager?
  • Is onboarding hands-on or self-serve?
  • Do you offer SLAs for uptime and support response time?
  • What support channels are available (chat, email, phone)?

A responsive support team can be the difference between shipping in a week or spinning your wheels for months.

8. Can You Scale with Our Needs?

Your needs today may not reflect your growth tomorrow. Ask:

  • Can we upgrade or downgrade as needed?
  • Do you support multiple environments (dev/test/prod)?
  • Do you work with startups and institutions?
  • What’s your largest customer using today?

Scalability isn’t just technical — it’s also contractual and financial. Look for flexible terms and infrastructure that will grow with you.

9. How Do You Handle Corporate Actions and Symbol Changes?

Financial data isn’t static. Splits, mergers, ticker changes, and delistings create chaos unless handled correctly. Ask:

  • How do you normalize for corporate actions?
  • Do you offer mapping tables for tickers?
  • Are these updates in real time or delayed?

This is especially important if you rely on historical analysis or backtesting. Proper normalization ensures data continuity and prevents inaccurate modeling.

10. What’s Your Pricing Structure, and What’s Not Included?

Transparent pricing is rare in the data world. Watch out for:

  • Exchange fees
  • User-based pricing tiers
  • Display licensing
  • Hidden API overage charges

Ask for clear, upfront pricing and a full list of what's included — and what isn’t. Surprise fees can destroy budgets, especially when scaling.

Pro Tip: Test Before You Commit

The best way to evaluate a financial data provider is to try before you buy. Look for providers that offer:

  • Free trials
  • Pilot programs
  • Limited-scope testing environments
  • Month-to-month contracts

This reduces risk, allows for technical validation, and ensures the data fits your needs — before you’re locked into a long-term agreement.

Many top-tier vendors now offer no-cost testing periods because they understand that the true value of data is in its implementation. Don’t just look at marketing materials — get your hands on the data, run your workflows, and simulate your most critical use cases.

Choose a Scalable, Strategic Data Partner with Intrinio

At Intrinio, we’ve built our platform around transparency, speed, and flexibility. Whether you’re an early-stage fintech or a multi-billion-dollar institution, we help you:

  • Access real-time and historical market data via powerful APIs and WebSockets
  • Get support from a real team of data and developer experts
  • Avoid the red tape and fine print that plague legacy vendors
  • Scale your pricing and licensing to fit your business model

Our clients range from algorithmic trading startups to global investment firms. They choose Intrinio because we provide clean, reliable data that integrates quickly and grows with them.

Need real-time data without the hassle? Start your free trial today by requesting a quick consultation.

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