Data Provider Disaster: A Financial Modeling Prep API Review & Alternatives
- Bryan Downing
- Jun 26
- 4 min read
In the world of quantitative finance, reliable data is paramount. But what happens when a data provider, once dependable, takes a nosedive in quality?
The Red Flag: No Refunds
The speaker emphasizes a critical warning sign: FMP's strict "no refunds" policy. The speaker quotes FMP's policy: "All sales are final and the company does not offer any money back guarantees. You recognize and agree that you shall not be entitled to a refund for any purchase under any circumstance."
The speaker states that enforcing this policy alongside unsatisfactory service is a major red flag. This lack of accountability raises serious concerns about the company's commitment to customer satisfaction.
Trustpilot Troubles: A Sea of One-Star Reviews
While the speaker acknowledges potential biases in online review platforms, the overwhelming number of negative reviews on Trustpilot paints a concerning picture. With a rating below 3.5 stars, FMP falls below the speaker's personal threshold for trustworthy services. A staggering 23% of reviews are one-star, indicating widespread dissatisfaction.
The speaker highlights specific complaints from other users, echoing his own experiences:
Bandwidth Limitations: Imposed bandwidth limitations are so restrictive that users can't even download basic datasets.
Account Freezes: Accounts are frozen, rendering the service unusable.
Lack of Support: Support is unresponsive and unhelpful, especially when complaints are involved.
Inaccurate Data: Users report inaccurate data, making it unreliable for decision-making.
One user's experience highlights the frustration: "They imposed a bandwidth limitation which is so tight I can't even download once the full set of NYSE stocks history data. They freeze my account usage. Cannot do anything. No refund and keep sending me notifications to review my usage. Totally garbage service."
The speaker notes that the fastest responses from FMP seem to occur when addressing negative reviews, suggesting a focus on damage control rather than genuine problem-solving.
The Bandwidth Bait-and-Switch?
Users report that bandwidth limitations weren't present when they initially subscribed, leading to suspicions of a deliberate change in policy. FMP's response, claiming these limitations have always been in place, is met with skepticism. The speaker suggests this may be a tactic to upsell users to higher-priced plans.
One user stated that they were well within their usage limits, but downloads consistently stopped at the same point. FMP's response was to suggest checking the user's configuration or internet connection, deflecting responsibility for the issue.
Inaccurate Data and Unresolved Issues
Multiple users report inaccurate data, rendering the service unreliable for backtesting or making informed trading decisions. Despite reporting these issues to support, users often receive generic responses or no resolution at all.
One user shared their code with support to demonstrate the data inaccuracies, but the issue remained unresolved. The user's request for a fix or explanation was met with silence and, of course, no refund.
FMP's response to these complaints often involves claiming that their database includes a certain number of stocks, including delisted ones, which may explain the discrepancies. However, users argue that this doesn't address the core issue of inaccurate or missing data.
Cancellation Nightmares and Automatic Renewals
Several users report difficulties canceling their subscriptions, with FMP allegedly ignoring cancellation requests and continuing to charge their accounts. One user reported being "ghosted" for an entire year after requesting cancellation.
The speaker highlights FMP's automatic renewal policy, which automatically renews subscriptions each year. The speaker argues that this practice may be illegal, as it requires explicit consent each year.
One user reported being charged for a high-tier plan without confirmation and being denied a refund despite contacting FMP immediately. The speaker emphasizes the recurring theme of "no refunds" and the company's apparent disregard for customer satisfaction.
FMP's Responses: Lip Service and Deflection?
Throughout the review, the speaker expresses skepticism towards FMP's responses to complaints, often labeling them as "BS" or "absolute garbage." He criticizes the company's tendency to deflect responsibility, offer generic solutions, and ultimately fail to resolve the underlying issues.
The speaker highlights the contrast between FMP's claims of valuing feedback and their unwillingness to provide refunds or address legitimate concerns.
Alternatives to FMP: EODHD and Tiingo
Given the negative experiences with FMP, the speaker offers two alternative data providers:
EODHD (End-of-Day Historical Data): EODHD offers historical data at a competitive price. The speaker highlights a plan similar to FMP's starter plan, offering a certain number of API requests per minute and 30 years of historical data. EODHD boasts a 4.6-star rating based on 6,111 reviews, significantly higher than FMP's rating.
Tiingo: Tiingo offers a free starter plan with access to a wide range of securities, including US and China stocks and ETFs. The free plan includes historical and real-time data, going back five years.
The speaker encourages viewers to test out both EODHD and Tiingo to determine which best suits their needs.
Conclusion: Avoid FMP and Explore Alternatives
Based on the speaker's experience and the numerous negative reviews, he strongly advises viewers to avoid Financial Modeling Prep. The combination of poor data quality, unresponsive support, and a strict "no refunds" policy makes FMP a risky choice for those seeking reliable financial data.
Instead, the speaker recommends exploring alternative data providers like EODHD and Tiingo, which offer competitive pricing, better data quality, and more responsive support.
The speaker concludes by reiterating the importance of reliable data in quantitative finance and urging viewers to choose their data providers carefully.
(Disclaimer: Readers are encouraged to conduct their own research and due diligence before making any decisions regarding financial data providers.)
Comments