Ever since generative AI entered the financial and business zeitgeist, concerns have run rampant about the technology’s potential to hallucinate. In simple terms, hallucination is when a genAI model provides inaccurate or misleading information, usually with total confidence and conviction. And while there are various guardrails genAI tools can employ to combat hallucination, the majority of tools on the market today do not take adequate measures to prevent it.
While hallucinations in consumer AI use carry different consequences than in the enterprise, it can be catastrophic for organizations using generative AI for market or investment research. In recent years, financial firms and corporations have been ramping up their usage of genAI tools — speeding up time to insight, helping uncover buried information, and saving time on repetitive, manual tasks, among others. However, many companies have run into significant issues with these tools, particularly when they are not employing adequate guardrails against misinformation.
That’s why, when selecting the right genAI tool for their business and investment needs, it’s crucial for firms to ensure that the tool has procedures in place to mitigate hallucinations. Furthermore, your tool should ideally be trained to understand financial and business language, as well as the nuances of your research process, so that it can truly support and accelerate, rather than hinder, your workflow.
Below, we cover the steps to combating genAI hallucination, as well as why this is critical for businesses and financial institutions. Finally, we discuss the AlphaSense genAI approach and how it effectively mitigates hallucinations and ensures that you get the most high-quality answers to your research queries.
Risks of GenAI Hallucination
For enterprise organizations and investors, the risks of genAI hallucination cannot be overstated, both from a strategic and regulatory standpoint.
Picture this: you are a professional conducting market research and decide to ask your genAI tool for specific market insights relevant to your research area. A tool prone to hallucination can confidently provide you with completely false or misleading information, and if you don’t confirm the answer’s accuracy, you run the risk of making a poor strategic decision or missing a key opportunity. This could have catastrophic implications both in the short-term and the long-term.
For an investor, hallucinations can produce erroneous analyses of a company's financials, such as incorrect revenue projections, distorted valuations, or fabricated stock price trends. Acting on such false information can lead to misguided allocations, bring risk to your portfolio, and break due diligence protocols.
Relying on hallucinated data can also result in reputational damage if the unvetted information is utilized in publicly disclosed or client-facing presentations or reports. This can lead to eroded trust between your company and stakeholders or clients. Furthermore, using incorrect AI-generated information in filings, financial reports, or investment recommendations can lead to regulatory penalties, compliance violations, or lawsuits, particularly in heavily regulated industries like finance.
GenAI hallucinations can also reinforce bias, if inaccurate or skewed data is used to make generalized assumptions. This can result in distorted market research or misled investment evaluations and ultimately negatively affect business outcomes.
Finally, relying on a genAI model that hallucinates will eventually put you at a disadvantage, relative to competitors who are using more accurate tools — over time, this means losing market share and your competitive edge.
In order to mitigate all these risks, it’s important to select a generative AI tool that follows specific steps to address the risk of hallucination and ensures the utmost accuracy in the data it generates.
Ways to Mitigate GenAI Hallucination
Prioritize a Model That Integrates RAG
Retrieval-augmented generation (RAG) grounds a large language model in authoritative content by asking it to only pull from a specified dataset, rather than the entire dataset it was trained on. For enterprise organizations or investment firms, RAG is a methodical way to fine-tune the LLM of whatever genAI tool they are using. Not only does it ensure that the answers being pulled are coming from the most relevant data sources for the research at hand, but it can also be fine-tuned to reason like an analyst or corporate professional would.
For example, AlphaSense employs a RAG model in its LLM that pulls from our extensive library of premium business and financial content, including equity research from leading Wall Street brokers and transcripts of analyst-led interviews with industry experts. Furthermore, the model is trained on specific tasks that our customers have to do daily, such as earnings analysis, SWOT analysis, competitive landscaping, and more.
Incorporate Citations or Other Verification Features
All generative AI models are capable of hallucination, but the ability to track the generated answer straight back to the source enables you to instantly verify the information and get additional context if needed.
Many genAI models lack citations or verification for their answers altogether — which should be a strong deterrent for enterprise organizations or investors who need to be able to verify their information. Some tools do provide citations, but they only cite the full documents from where they sourced the answer, which means you will need to dig through pages and pages of content to find the context you are looking for.
AlphaSense provides citations to exact snippets of text from where an answer is sourced, so that you can instantly get smart on the topic at hand and ensure that the answer came from a valid and reliable source.
Input Structured and Specific Queries
Sometimes, the easiest way to prevent hallucination in a genAI model is simply being as specific and prescriptive with your query as possible. Hallucination can sometimes be an effect of the model misunderstanding your question, so it’s important to be clear in your prompts.
When you give the model specific parameters, like time frames, industries, or particular data points, it reduces the likelihood of the AI straying into unsupported or fabricated information.
The more ambiguous a query is, the more likely the model is to generate hallucinated responses to fill gaps in understanding. By inputting structured queries, you narrow down the scope of what the model is supposed to address, minimizing the chances of misinformation. Clear, detailed questions make it easier for the AI to stay on track with factual information.
AlphaSense makes this easy with our semantic search that understands the intent behind your keyword search and eliminates the need to search for specific long-form phrases or to search for multiple iterations of your keyword. Additionally, you can ask the model to explain how it arrived at an answer, with clear citations to underlying sources. This transparency provides full traceability and makes insights more trustworthy.
How AlphaSense Mitigates GenAI Hallucination
AlphaSense is a secure, end-to-end market intelligence platform that enables business and financial professionals to centralize their proprietary internal content alongside an out-of-the-box collection of 500+ premium external documents. By layering cutting-edge AI and generative AI features over this content, AlphaSense enhances and accelerates market research, resulting in increased team productivity and collaboration.Our industry-leading generative AI tools are purpose-built to deliver business-grade insights, leaning on 10+ years of AI tech development. Our suite of tools currently includes:
Generative Search
Generative Search is a conversational search experience that allows users to ask natural-language questions and source intelligence at scale from across premium external content, internal knowledge, and quantitative data sources. Each answer provides citations to the exact snippet of text from where the information was sourced, so that it can always be referenced back. Our users leverage Generative Search for everything from getting quick, trusted answers to questions they’re fielding live, to analyst-grade reports and full slide decks with Deep Research mode.
Workflow Agents
AlphaSense offers a full library of pre-built automations for your most common and time-consuming research workflows and deliverables — including company primers, meeting prep briefings, earnings analysis, and more. Users can also build custom agents personalized to their specific needs, data sets, or evaluation criteria — and even schedule them to run on a daily or weekly cadence. For example, an investment banker can build a custom workflow agent that understands and finds the specific deal criteria needed to build a buyer profile. Rather than doing this manually for each new deal, they can simply run their customized agent with one click.
Workspaces
Workspaces are dedicated project spaces that enable users to organize conversations, files, instructions, and outputs around a specific initiative, goal, or body of work. Rather than treating AI as a one-off prompt interface, Workspaces offer a persistent, context-aware work environment where you can integrate your deal rooms, ingest internal meeting notes, and add external context to ask questions, automate analysis, and create deliverables — all in one place.
Generative Grid
Generative Grid applies multiple genAI prompts to many documents at the same time to quickly provide organized answers to research questions at scale, in an easy-to-read table format. This enables clients to summarize documents using pre-built criteria to save time when executing repeatable workflows.
Here’s how AlphaSense stands apart from its competitors and prevents genAI hallucination:
Purpose-Built to Deliver Business-Grade Insights
AlphaSense has spent over a decade building out its AI tech stack and creating AI tools that are uniquely positioned to radically reduce research time and manual effort for knowledge workers.
At the core is our data engine, grounded in over 500 million premium documents. We utilize superior data ingestion to structure this massive library, but what sets it apart is our search-first AI architecture.
By leveraging a high-fidelity knowledge graph and proprietary context management, the system understands the nuanced relationships between global markets and industries. We apply an advanced multi-step filtering process and a multi-LLM approach, using the best model for each specific task. By the time an insight reaches you, it has been vetted, contextualized, and grounded in a verifiable source. This eliminates the 'hallucination' risk and gives you a foundation of truth you can actually build a strategy on.
AlphaSense’s original collection of AI tools includes:
- Smart Synonyms – An intelligent search feature that captures language variations by sourcing all applicable synonyms and applying them only in the correct contexts based on the intent of your search.
- Theme Extraction – A method of extracting and ranking the most important trending topics and themes affecting companies and industries. AlphaSense processes millions of documents in real-time to alert you to what’s happening.
- Sentiment Analysis – A feature that enables users to identify, quantify, and analyze levels of emotion in human language. AlphaSense performs sentiment analysis at the phrase-level to enable sentiment search and aggregates those scores at the document and company level to enable macro trend analysis.
- Company Recognition – a home-grown solution for recognition, inter-company disambiguation, and salience classification of company mentions across AlphaSense content.
- Relevancy Scoring – A multi-factor model that takes into account semantics, source, document structure, recency, and entity aboutness to deliver the most relevant documents to the top of the results list.
Having this foundation of AI tools, purpose-built for financial and business insights, has enabled us to create generative AI that is specifically designed to enhance and accelerate knowledge workers’ workflows.
Verifiable Down to the Exact Snippet
Unlike the opacity of most other generative AI tools, AlphaSense links to the exact snippets of text within documents that drive summarized insights, allowing users to instantly validate any information generated and gain trust in the model.
Our generative insights are sourced only from high-quality external documents within the platform, as well as your internal data if you choose to upload it — meaning that each insight can be verified. Clearly labeled citations create total transparency, and users are able to quickly “check the work” of the AI summaries and gain additional context for their research.
High-Quality, Premium Content
Language models rely entirely on high-quality content to generate good information. While most genAI models on the market today pull data from the public web — containing information that is often biased, inaccurate, or untrustworthy — generative AI tools within AlphaSense parse exclusive and coveted content sources from our proprietary content universe.
Our library of content includes high-value, premium sources such as broker research reports and expert transcript interviews, as well as company documents, regulatory filings, and government publications. Since our genAI pulls from these premium sources when generating output you can be sure that every summarization is high-quality, credible, and business-grade.
Finally, our platform enables you to securely sync your organization’s internal content into AlphaSense, so that our genAI model can produce insights that are uniquely tailored to your company and industry.
Safe and Responsible AI
Our platform protects customer information with encryption at rest and in transit, robust access controls, and flexible deployment options. Our secure cloud environment complies with industry-leading security standards — SOC 2 Type II and ISO 27001 certified — and we conduct regular third-party penetration testing. We also support SSO to streamline enterprise user authentication.
Our genAI tools were built with security and privacy-conscious companies in mind. Customer queries and data are never used to train AI models, and we exclusively partner with LLM providers that enforce zero data retention policies, ensuring your sensitive information is never retained or repurposed. Because our models are trained on premium financial and business data, companies can be confident they're working with a purpose-built platform designed to minimize the risk of irrelevant or low-quality outputs
Generative AI You Can Trust For Your High-Value Research
In today’s age of fast-moving markets and information overload, a genAI market research solution is integral for organizations to stay efficient, competitive, and confident in their research. But genAI tools are not all created equal, and it’s important to select a tool that does not put your organization or your data at risk.
AlphaSense is your one-stop solution for premium business and financial content — which includes everything you need for holistic market research — and the generative AI technology to help you maximize the value you get from the data. Our platform goes above and beyond to ensure that your data is safe and secure, and that you reap all the benefits of generative AI technology with minimal risk.
Discover the power of genAI-fueled market research, and see how AlphaSense can help you conduct research with unparalleled confidence and speed.
