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Felo Leads AI Search Engines in Financial Data Accuracy

· 7 min read
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An in-depth test of AI search engine performance in financial data retrieval reveals accuracy gaps. Learn why Felo delivers better investment data.

Felo Leads AI Search Engines in Financial Data Accuracy.png

Introduction: Performance Disparities Revealed by Identical Queries​

The evolution of AI search engines has been remarkable. ChatGPT, Perplexity, Genspark, Manus, and Felo—diverse platforms are ushering in a new era of information retrieval. But can we truly trust these tools? In this investigation, we posed an identical financial query to multiple AI search engines: "List 20 Japanese stocks under 1000 yen with the highest investment value." The results we obtained were extraordinarily revealing about the current state of AI search technology.

Experimental Design: Fair Comparison Through Unified Prompts​

This study employed a standardized prompt across all platforms:

List 20 Japanese stocks under 1000 yen with the highest investment value.
1. Display in table format
2. Provide investment rationale
3. Consider carefully
4. Include current prices

This prompt doesn't simply request information retrieval—it simultaneously demands structured data presentation, logical investment justification, and real-time price information, creating a multi-dimensional challenge. Since the accuracy of financial information directly impacts investment decisions, this test served as an ideal litmus test for measuring the practical utility of AI search engines.

Verification Results: An Unexpected Performance Hierarchy​

The Hidden Weakness of AI Search Engines An Empirical Analysis of Accuracy Gaps in Financial Data Retrieval.png

Test example:

>> https://felo.ai/search/HhNt6PT3zaQPvCffoHzVoX?invite=dO3X4xv4Rxy18
>> https://chatgpt.com/share/6916e6d2-3888-8009-8637-7e2804372e27#main
>> https://www.genspark.ai/agents?id=86eeea83-48e6-4980-aa22-7859b4b81323
>> https://www.perplexity.ai/search/1000yuan-yi-xia-nozui-motou-zi-O.ZkCmrGRtOX5BMrJXt65w#0
>> https://manus.im/share/U7ksn2TB5AKF79fyd3YBqF?replay=1

Felo: 65% Investment-Worthy Data Delivered​

Felo demonstrated the most superior performance, with 65% of provided data being investment-worthy information—significantly outpacing other platforms. Felo exhibits clear technological advantages in accessing financial databases and integrating real-time information.

Felo's Strengths:

  1. High freshness of stock price information
  2. Specific and logical investment rationales
  3. Clear table-format presentation
  4. Transparent data sourcing

ChatGPT: Reasonable Approach, but 60% Investment-Ineligible​

While ChatGPT took a reasonable approach to stock price management, 60% of its recommended stocks turned out to be unsuitable for investment. This suggests that ChatGPT's strength in language generation doesn't necessarily translate to real-time financial data accuracy.

ChatGPT's Challenges:

  1. Temporal constraints of training data
  2. Limited access to real-time market data
  3. Opaque criteria for investment eligibility assessment
  4. Overly conservative or optimistic evaluations

Genspark, Manus & Perplexity: Only 10% Reference Value​

The most shocking finding was that Genspark, Manus, and Perplexity all provided only approximately 10% usable data, failing to retrieve accurate stock price information for the remainder. While these platforms receive high marks for general information retrieval, they demonstrate clear limitations when it comes to specialized financial data.

Factors Behind Low Performance:

  1. Insufficient integration with financial databases
  2. Limited access to Japan-market-specific information sources
  3. Absence of real-time data feeds
  4. Inadequate capacity for processing structured financial information

Comparative Analysis Matrix​

Evaluation CriteriaFeloChatGPTGensparkManusPerplexity
Investment-Worthy Data Rate65%40%10%10%10%
Stock Price Accuracy◎ High Precision○ Reasonable but Dated△ Inaccurate△ Inaccurate△ Inaccurate
Investment Rationale Quality◎ Specific & Logical○ Generic△ Insufficient△ Insufficient△ Insufficient
Table Format Presentation◎ Clear○ Capable△ Incomplete△ Incomplete△ Incomplete
Real-Time Capability◎ Excellent× Limited× Limited× Limited× Limited
Data Source Transparency◎ High○ Moderate△ Low△ Low△ Low
Japanese Market Support◎ Excellent○ Capable△ Insufficient△ Insufficient△ Insufficient
Overall RatingABDDD

Table adapted from comparative analysis

Technical Analysis: Why Such Dramatic Differences?​

1. Data Source Architecture Variations​

The primary reason for Felo's superiority likely lies in its direct integration with financial data providers. ChatGPT, by contrast, depends on its large language model's training data, creating inherent real-time constraints. Genspark, Manus, and Perplexity are designed primarily as general-purpose search engines, likely having limited access to specialized financial databases.

2. Japan Market-Specific Information Barriers​

Japanese stock market information presents higher access difficulty compared to English-language markets. Many AI search engines are optimized for English data and face challenges accessing Japanese financial information—particularly real-time stock prices. Felo appears to possess a clear technological advantage in this regard.

3. Structured Data Processing Capability Gaps​

Financial information is highly structured data. It requires accurate retrieval and presentation of numerical data including stock prices, market capitalization, P/E ratios, and dividend yields. While Felo excels at processing this structured data, other platforms lean heavily toward natural language processing, potentially resulting in inadequate numerical data accuracy management.

4. Presence or Absence of Verification Mechanisms​

Providing investment information necessitates data verification and fact-checking. Felo presumably implements some form of verification mechanism, while other platforms likely have insufficient accuracy validation for generated information.

Practical Implications​

Recommendations for Investors​

This study's findings demonstrate that platform selection is critically important when using AI search engines for financial information retrieval. Pay particular attention to:

  • Verify platform specialization: General-purpose AI search engines aren't necessarily strong in financial information
  • Rigorously cross-verify with multiple sources: Never take information from a single AI tool at face value
  • Confirm real-time accuracy: Always verify whether presented stock prices are current
  • Evaluate investment rationale logic: Verify that AI-generated investment reasons are grounded in concrete data

Insights for AI Developers​

This investigation highlights the following challenges in AI search engine development:

  • Integration with domain-specific databases: Depth in specialized fields matters as much as versatility
  • Implementation of real-time data feeds: Freshness is lifeline for financial information
  • Strengthening multilingual and multi-market support: Global market coverage is essential
  • Incorporation of verification mechanisms: Systems for automatically validating generated information are necessary

Conclusion: Discerning AI Search's Strengths and Weaknesses​

This empirical analysis clearly demonstrates that AI search engine performance varies dramatically depending on use case. While Felo's 65% investment-worthy data rate is impressive, we must not forget that 35% remains ineligible. ChatGPT's 60% ineligibility rate and the 90% ineligibility rates of Genspark, Manus, and Perplexity vividly illustrate the limitations of current AI technology in financial information retrieval.

The crucial lesson is the obvious truth: "AI is not omnipotent."

Especially in domains requiring high precision like financial information, platform selection dramatically influences outcomes. Users must understand each tool's characteristics and employ them for appropriate purposes. AI technology developers, meanwhile, should focus not only on pursuing versatility but also on implementing deep specialization in specific domains.

While AI search engines are indeed revolutionizing information access, their true value is measured not just by "what they can do" but by "whether they understand what they cannot do." The surprising results revealed by this study point to the next critical step in AI technology evolution: the pursuit of specialization, accuracy, and transparency.

About This Research​

This comparative analysis was conducted using identical query conditions across five major AI search platforms to evaluate their performance in retrieving accurate, investment-relevant financial data for the Japanese stock market. The findings underscore the importance of choosing specialized tools for domain-specific information needs.

Interested in experiencing superior financial search capabilities? Try Felo Search for accurate, real-time financial data retrieval that delivers investment-worthy results.

This blog post presents findings from an independent comparative study of AI search engine performance in financial data retrieval. All data represents results obtained from testing conducted with standardized prompts across multiple platforms.