Generative AI and large language models (AI) have finally broken into the mainstream. LLM-driven tools are transformational. They’ve revolutionized consumer products (auto-suggest, Google Translate, Grammarly) and now LLMs are coming for the investment research industry.
Artificial intelligence is an extremely powerful and effective tool for equity research. However, there’s no denying that we’re in the midst of a hype cycle. We made this list to help our friends, partners and users cut through the noise, and focus on what matters. Below you will find a list of the AI tools on the market with notes on their strengths and limitations.
[October 2024] We have created a new and updated version of this tool compilation. Read more here.
Finance-specific tools using generative AI
Hudson Labs is an artificial intelligence-driven investment research software platform. Their core models are highly specialized, trained specifically to read/understand complex financial disclosure. For context, the company's base models were trained on 65 times more SEC filings than BloombergGPT.
Unlike generalist chatbots, Hudson Labs breaks down finance-specific tasks and tackles them with multiple specialist models. This allows Hudson to provide industry-leading accuracy and reliability by ensuring that their models are never put in a position where they are likely to fail. Learn about our in-house AI research breakthroughs here.
Compare AI performance on financial disclosure:
Read more here.
A fellow Toronto fintech, FinChat uses a combination of ChatGPT and langchain/llamaindex, similar to the tools above but is building for a much broader use case.
What we like:
FinChat is a great Q&A tool for pulling up financial information. FinChat pulls financial data and metrics from Strastephere.io and therefore, has more complete and accurate answers in this domain than the tools listed above.
The team seems to be iterating quickly so we expect improvements coming soon.
The cons:
Qualitative question answering suffers from error and hallucination.
Call transcripts could take 2 days to appear.
An “equity research co-pilot” that provides company-specific insights based on filings and earnings transcripts. It can easily export outputs to tables or CSV. It also provides custom alerts based on AI searches
The cons:
The search can only be done on a per-ticker basis, not across multiple companies.
Look out for occasional AI hallucination errors.
hebbia is an AI platform built for “any data/any task”, beyond finance, into legal, lending, real estate, and corporate admin. It can integrate with user data. It has extensive live use cases, including activist trends, fees, due diligence, RFP, and deal memos.
The cons:
Aimed at enterprise users and hence the sign-up and integration might be lengthy for smaller teams (plus a higher price tag).
Not specialized for investment and equity research.
rogo is a purpose-built financial AI that is connected to all user data. It offers search, Q&A, and workflow automation. It can integrate users’ documents like pitch decks and meeting notes with its own library and has use cases for investment banking and private equity.
Similar to Hebbia, rogo is aimed at enterprise users with a lengthy sign-up process and is more expensive.
A note of caution on generative artificial intelligence
While generative AI tools have grown popular in automating a variety of tasks within investment analysis workflow, anyone who has used ChatGPT, BingChat etc. for financial research will know that "hallucination" issues get worse with technical topics. Hallucination means that these tools invent plausible-sounding answers that have no grounding in reality. Generative AI hallucinations are hard to fix. Learn more about the limitations of generative AI and how they can be ovecome - A Comparison of Generative Chatbots to Hudson Labs.
More equity research tools using AI, natural language processing (NLP) and machine learning
Arteria AI uses AI to help with process documentation workflows and automation in financial services. Its AI platform unlocks operational speed and efficiency in areas like trading, lending, and asset management, among others.
Alkymi unlocks your investment and market data and gives you the tools to understand, transform and leverage it in your business.
Aiera AI is powering equity research with advanced earnings transcript tools such as one-click live audio access, real-time transcription, keyword search, AI-powered Q&A, and advanced summarization.
Amenity Analytics provides an NLP platform that can be customized to extract and classify the information most relevant to you, capturing key business events, sentiment, context, and temporal relevance consistent with your research strategy. It is now part of Symphony, a large IT solution provider.
Hudson Labs (formerly Bedrock AI) built by leading AI researchers and domain experts, Hudson Labs' proprietary finance-specific language models power earnings summaries, automated investment memos and more. Hudson Labs boasts industry-leading accuracy and reliability.
BlueFire AI combines financial statement analysis, behavioural profiling, market data analytics and NLU to provide signals of underperformance in the listed assets of public companies. They also use data visualisation to contextualize information.
Uptrends.ai uses language models to detect bullish vs. bearish sentiment indicators across stocks, topics, and market-wide. We’ve been known to call other financial sentiment tools ‘purveyors of useless bullshit’ but we love Uptrends. Uptrend’s founders are computational linguists and computer scientists. They aren’t pretending to do lie detection (phew) and generally abstain from the insane claims that we’ve seen from other sentiment tools.
280First is the granddaddy of financial NLP tools, having been around since 2016. It is a financial services platform that analyzes unstructured data from various sources and produces insights from financial documents for investment professionals. There may be a human-review step in their process but we’re not sure about this.
Docalysis can process your uploaded PDFs and respond to prompts like ‘list all risk factors’ or ‘summarize all legal issues.’ It pre-loaded some 10-Ks but doesn’t cover earnings call transcripts or other SEC filings. It has a free plan.
Nosible AI makes it easy to demonstrate what your portfolio looks like and how it’s different/unique. They have visualization and data libraries.
Roic.ai provides ten years of financial statement data on one easy-to-use screen. No clue how they use AI but, let’s be real, who cares.
New Constructs uses forensic accounting and technology to provide research, tracking and alerts for an unlimited number of tickers across 50 portfolios as well as screening and direct access to their databases. They also offer API & Excel Add-Ins.
AlphaSense uses machine learning and NLP to offer finance-specific smart search as well as a number of linguistic and sentiment scoring offerings.
Sentieo (owned by AlphaSense) provides a searchable database of public and private company data, documents, and news from relevant sources, along with integrated modeling tools.
Boosted.ai uses finance-specific machine learning algorithms to identify patterns based on your unique inputs. They also highlight which features drove the machine learning decisions and outcomes. Another Toronto fintech!
Bloomberg, FactSet, CapIQ, Refinitiv: All of the major capital market research platforms use AI, ML and NLP, to some extent, in order to do information extraction. FactSet and Bloomberg also provide various sentiment and linguistic indicators. These tools use a human-in-the-loop methodology for information extraction, which improves accuracy and reliability. Bloomberg recently published a paper on their generative LLM, “BloombergGPT” which isn't yet being used in production. Learn about how Hudson Labs models compare to BloombergGPT here (towards the bottom of the article).
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