Unwittingly, default natural language processing has become a critical component of the qualitative investment process and improving this natural language processing is not appropriately prioritized.

Most qualitative investors, unsurprisingly, think their investment strategies are built completely on human analysis. That is a false assumption.

While you are collecting data for your investment research — think news, web mentions and corporate filings — the data you find has already been curated by natural language processing search algorithms.  

Your current investment process is littered with systematic natural language processing analysis. Is it working to your advantage?

Moving beyond manual search engine results

Think about the daily searches you conduct on news outlets like Google or Bloomberg, or the secondary market research you purchase. The articles and research displayed on your computer screen are being filtered through natural language processing search algorithms formulated by other companies. And these algorithms are not even close to perfect.

Default NLP algorithms are varied and biased because they choose their order of results based on priorities tangentially related to your investment process. In the worst case, the research and findings you scroll through may be filtered based on advertising dollars and click rates. Other engine results may be based on the number of keywords that match, with little to no context. They are not designed to consistently display the content you desire or need to find. And to top it off, these results mirror the results shown to your competitors. That is, your competitors are consuming the same basic information for their investment research and analysis.

When every analyst uses the same search engine that filters the same search results, there is no room for competitive advantage. But by putting customized NLP to work, you can create algorithms specifically designed for your investment process. Those algorithms can provide you with relevant, real-time data curated from sources that go beyond search engine results alone and matter more to your specific investment process.

Natural language processing: The untapped key to qualitative research

The latest NLP techniques integrate advanced search methods and word pattern recognition through various combinations to learn contextually and provide specific conclusions. NLP algorithms tailored to your investment universe, prospectus, and investment process are possible and necessary to do your best.

Custom NLP solutions aren’t a shift away from traditional, qualitative research methods. Rather, it is the evolution of qualitative research. Fund-specific NLP will one day be the standard, but today it will be your differentiator over using basic, default search algorithms.

Advantages of custom natural language processing:

  1. Access to more relevant, real-time news sourced from both general outlets and specific, niche outlets.
  2. Delivery of targeted data, customized to the way you enjoy working.  
  3. Adaptive, learned insights from the breadth and depth of data collected and tailored to your process.
  4. Improved productivity via pre-analyzed content, allowing you to read up to 3x faster.

What’s next?

Natural language processing is not new to the investment research process, just relatively disguised. Unwittingly, default NLP has become a critical component of the qualitative investment process. Improving this NLP is not appropriately prioritized.

You can improve your own productivity and leap above your competition by integrating NLP into your current investment research strategy.

Even with custom NLP solutions, you still drive your investment strategy. But now you have the ability to analyze greater volumes of more relevant information, at an otherwise impossible rate.

These insights can be structured and segmented into various categories, giving you a complete view of the data collected through time. And with that view, you can create a more successful investment strategy than ever before.

If great qualitative investments could still hinge solely on meeting with company executives and drawing personal conclusions about the business, there would be no need for this article. But individual data gathering is only one component  of the modern qualitative investment process.

The best financial investment decisions come from combining the power of both human insights and technological insights. It’s time to get ahead of the competition by transforming your investment research process, or risk falling behind.

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