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Frequently Asked Questions (FAQ)

We answer the most common questions that Hudson Labs trial users and new customers are asking.


How many stocks does Hudson Labs cover?


Universe: We cover U.S. public issuers.

  • Investment background memo: We provide coverage for all companies with a market capitalization of $300M or more that have filed a 10-K in the last year, approximately 2,800 companies. Need micro cap coverage? Get in touch for a quote. 

  • Risk assessment coverage: We provide red flag detection for over 8,000 companies, all EDGAR issuers that have filed a 10-K, 10-Q, 8-K, S-1 or 20-F since 2019. We do not cover Asset-Backed Securities (SIC 6189).

  • Earnings call coverage: We cover all companies listed on a U.S. exchange that hold earnings calls, over 3,000 companies

Content Library:

  • Earnings call transcripts

  • Conference & presentation transcripts

  • Press releases

  • EDGAR filings including S-1s (prospectus precursor), 10-Ks, 10-Qs, 20-Fs (annual and quarterly reports), 8-Ks (SEC-mandated news releases), NT forms (non-timely filing notifications) and SEC comment letters (UPLOAD) and more. 

We’re always adding coverage so check back for updates.


How quickly does Hudson Labs process data and post results?

Earnings call summaries and related data generally posted within two hours of the end of the call. SEC filings are processed once every three hours. To see new results, hit refresh on your browser. During peak filing times, processing times may be longer. 


Is there human review in the Hudson Labs process?

Summaries, memos, red flags, and risk scoring are all auto-generated, without human intervention. 


How long is the Hudson Labs trial?

Trial the Hudson Labs platform for 10 days for free. To trial Hudson Labs, you must first book a demo here. Trials are available to institutional investors and enterprise customers. 


We offer extended trials to MBA students, academics, and journalists. 


How much does Hudson Labs cost?

Book a demo or reach out to your account executive for pricing. 


Can students and journalists access Hudson Labs?

Contact us at info@hudson-labs.com to find out if you qualify for our program for students and journalists.


I’m already a Hudson Labs subscriber, where do I login?

Login to our market intelligence platform at platform.hudson-labs.com/login


How is Hudson Labs different from the common generative chat bots and other AI models?

Hudson Labs leads the market on factuality and repeatability in capital markets. Learn how we do it here - A Comparison of Generative Chatbots to Hudson Labs


 


Hudson Labs Risk Assessment FAQ


How does Hudson Labs detect red flags?

Hudson Labs uses language models to find content that has empiric associations with fraud and related outcomes. Learn more about our approach to financial artificial intelligence in our post - Financial NLP & LLMs - The Hudson Labs Advantage


What types of red flags are detected by Hudson Labs’ algorithms?

Hudson Labs detects any and all text in securities filings that has an association with fraud, earnings management or malfeasance, regardless of the specific wording used. That means we’re extracting generally any information that would be highlighted by a forensic equity analyst. 


Popular red flags types include accounting policy changes and restatements, management turnover, related party transactions, internal control issues and much more. Red flags are categorized/tagged after extraction, as part of a separate process. 



How is the Hudson Labs risk score calculated and what does it measure?

We discuss our proprietary forensic risk scoring here - The Hudson Labs Forensic Risk Score


Why doesn’t this red flag make sense to me?

Hudson Labs covers hundreds of types of red flags/risk areas, some of them are somewhat niche. If you’re ever confused about why a red flag matters, don’t hesitate to reach out and ask.  Or you can find our red flag guides here: Red Flag Guide Part I, Red Flag Guide II.


Language models are great at many things but they have a few failure modes. (Artificial intelligence isn’t magic.) Expect about five percent of red flags to be false positives. Most of these will be in the “yellow flag” section. Lower confidence flags can be filtered out using in-platform filtering.  20-Fs and S-1s have slightly higher false positive rates compared to other filing types. One possible failure mode is materiality - large language models are great at understanding content and context but bad at math. This means they sometimes mistake a $1 transaction as almost as important as a $1B transaction.


Why doesn’t Hudson Labs incorporate financial ratios into the risk assessment process?

One of the reasons that auditors are bad at detecting fraud is that it's hard to reliably identify through ratio analysis. Financial reporting is manipulated to look normal in many fraud or fraud-like situations. When ratios start to unwind, it’s often already too late.


Predictions based on qualitative risk factors (related party transactions, aggressive/frequent accounting policy changes, poor governance, off-balance sheet risk etc.) have much higher accuracy rates AND are much earlier signals, compared to traditional forensic financial ratio analysis. 


Why does this risky company have a lower Hudson Labs risk score?

Our risk scores measure earnings quality and fraud risk, not generalized risk. Other types of risk are not incorporated into our scoring. Refer to the Hudson Labs Summary View for a more comprehensive view of risk in the platform. 


Note that we also optimize for precision not recall when we train our models. This means that missing a few risky companies is inevitable. However, even when the risk score is low, we will identify relevant and informative red flags. Here are a few examples of red flags detected at low risk companies that helped us predict earnings outcomes - “Accounting policy changes boost tech earnings”.


If we haven't answered your question here, reach out by booking a demo or contacting your account executive.

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