Perplexity vs Fintool Chat

In this comprehensive study, we evaluate how Perplexity and Fintool handle complex financial questions regarding public equity securities. The benchmark leverages the FinanceBench top 100 questions - an industry-leading standard developed by AI researchers at Patronus and Stanford in collaboration with financial domain experts.

The FinanceBench dataset was created through collaboration between AI researchers and 15 financial industry domain experts, comprising high-quality questions and answers derived from public financial documents including SEC filings (10-Ks, 10-Qs, 8-Ks), earnings reports, and earnings call transcripts. While the original benchmark includes document context, we modified the testing methodology to better reflect real-world usage by finance professionals: questions are presented to the AI assistants without any supporting documents, requiring them to provide accurate answers in a single interaction - similar to how professionals would use these tools in practice.

Perplexity's Data Quality Issues

Our testing revealed that while Perplexity performs better than some other AI assistants, achieving a 45% accuracy rate, it still faces significant challenges in providing reliable financial information. While Perplexity does attempt to cite its sources, it often relies on a mix of authoritative and non-authoritative sources, leading to inconsistent accuracy in its responses.

For instance, in one case, Perplexity confidently cited an annual 10-K report while providing a figure that was off by $400 million from the actual value. This type of error, even when accompanied by authoritative source citations, highlights the risks of relying on AI systems that may misinterpret or incorrectly extract financial data.

Retail Investor Sources Lead to Accuracy Issues

Like other AI assistants, Perplexity sometimes relies on retail investor websites and third-party sources instead of going directly to SEC filings. While it does a better job of citing sources compared to other AI assistants, the quality of these sources varies significantly. This can lead to outdated or incorrect information being presented to users, even when citations are provided.

Particularly concerning is Perplexity's frequent reliance on websites like Seeking Alpha, Statista, and Stock Analysis. These platforms, while popular among retail investors, often present incomplete or misleading data points that can significantly impact investment decisions. For instance, these sources may report adjusted figures without proper context, use inconsistent calculation methodologies, or present outdated information that hasn't been updated to reflect recent company restatements. This creates a dangerous situation where institutional investors might unknowingly base their analysis on retail-focused data that doesn't meet professional standards.

Limited Financial Calculation Capabilities

Even when Perplexity successfully locates the correct numbers, it lacks the infrastructure to accurately compute complex financial metrics and ratios. This limitation becomes particularly apparent when dealing with sophisticated financial calculations that require precise methodology and multiple data points.

Fintool Excels Where Perplexity Falls Short

Verifiable Sources, Zero Hallucinations

Unlike search-web-based solutions, Fintool provides complete transparency by showing you exactly where information comes from in source documents. Every response is backed by direct citations to SEC filings, ensuring 100% verifiability and eliminating the risk of hallucinations.

Comprehensive Revenue Breakdowns

Fintool excels at providing detailed segment and quarterly revenue breakdowns. Our advanced extraction capabilities can parse complex financial statements to give you granular insights into business performance across different segments and time periods.

Complete Data Coverage

With access to all public company filings and the ability to process them in real-time, Fintool offers comprehensive coverage across companies, metrics, and time periods. Our system can analyze any publicly available financial information, ensuring you never hit a coverage gap.

Conclusion

Our comprehensive analysis of Perplexity and Fintool using the FinanceBench top 100 questions reveals a significant performance gap between the two platforms. While Perplexity achieved a 45% accuracy rate, showing better performance than some other AI assistants, Fintool demonstrated superior performance with 98% accuracy on the same test set.

The key differentiator lies in their fundamental approaches. While Perplexity makes an effort to cite sources and provide more reliable information, its reliance on a mix of sources, including retail investor websites, leads to accuracy issues. These limitations become particularly problematic when dealing with complex financial metrics, where precision and verifiability are crucial.

In contrast, Fintool's direct engagement with authoritative SEC filings and earnings reports provides a more robust and reliable solution for financial analysis. The ability to verify every data point against original source documents, combined with proper citations and comprehensive coverage, makes it a more suitable tool for professional financial analysis where accuracy and auditability are paramount.

This study underscores the importance of specialized tools in financial analysis. While Perplexity represents an improvement over general-purpose AI models, the complexity and precision required in financial analysis demand purpose-built solutions that prioritize accuracy, verifiability, and direct access to authoritative sources.