Wall Street's Next Misinformation Crisis May Come From Black-Box AI

New Constructs CEO David Trainer says the firm's data and expertise behind FinSights, built with Google Cloud technology, show why AI-driven investment research needs transparent source data to prevent biased, unverifiable outputs from becoming market-moving misinformation.

NASHVILLE, Tenn., June 10, 2026 /PRNewswire/ -- The next wave of market misinformation will not come from fake stock tips, but from AI-generated analysis that sounds credible while using weak, biased and incorrect data. This New Constructs warning is important for investors and financial advisors as artificial intelligence tools move from answering questions to influencing decisions.

The concern rises as regulators are scrutinizing AI claims in finance. In 2024, the SEC charged two investment advisers with making false and misleading statements about their use of AI, which resulted in $400,000 in total civil penalties.

According to New Constructs CEO David Trainer, the biggest misconception investors have about AI-driven stock valuations is that they are always based on reliable analysis. "AI can be biased depending on your location or how you ask the question. If you do not know what data the AI is using, you are taking the risk that the analysis may be based on bad data."

Confident Answers Without Verifiable Sources

AI tools are increasingly used to summarize companies, screen stocks, and generate investment ideas, but investors can face problems verifying the data and methodology behind outputs. The first question investors should ask any AI stock tool is whether it can prove where that answer came from. "If a system doesn't present its sources, investors should ask why," Trainer said.

That lack of visibility is especially dangerous in finance, where a small error in source data can distort a valuation, a rating, or an investment recommendation. Trainer calls this the 99% rule. "You can't rely on any of it if you do not know which 1% is bad," Trainer said. "That 1% could be critical to the answer the AI provides. If you cannot verify the inputs, you cannot rely on the outputs."

The warning comes as regulators and investor-protection groups continue to raise concerns about AI-related investment claims, AI-washing, and the use of artificial intelligence to promote financial products or strategies without adequate transparency. Financial AI creates a different level of risk because investment decisions depend on the accuracy, completeness, and interpretation of complex and nuanced financial data.

Why Raw Financial Data Is Not Enough

One of the biggest myths about AI is that companies can feed broad financial information into any language model and expect it to produce valuable investment insight. "Financial filings are like crude oil, it can't go straight into the engine," Trainer said. "It must go through the refinement process before it becomes fuel. That refinement process is where the value is created and where most generic AI tools fall short."

New Constructs' research platform is built around forensic accounting, proprietary financial models, and a proprietary ontology that delivers proven-superior research on the profitability and valuation of public and private companies. The company's patented Robo-Analyst technology automates data collection, financial modeling, and investment ratings across more than 10,000 securities, including stocks, ETFs and mutual funds.

That process is designed to turn raw Securities and Exchange Commission (SEC) filings and financial disclosures into auditable and reliable investment research. Their system shows the source data, assumptions, and logic behind its analysis.

Google Cloud Built FinSights on New Constructs' Data

Google Cloud retained New Constructs to build FinSights, an AI agent for investing powered by New Constructs' proprietary data and research expertise. Their goal is to demonstrate how well an AI agent performs when it is supported by structured, auditable investment research rather than broad, unverifiable internet inputs. "Google Cloud's decision to build FinSights with New Constructs' data and expertise is a powerful validation of the work we have spent years building," Trainer said. "We are proud to help show what AI can become when advanced technology is paired with financial intelligence investors can trust."

Rather than producing generic market commentary, FinSights is able to answer complex questions like "which companies are most likely to miss EPS estimates?" or "what are the best stocks in the tech sector?" because New Constructs' research system has a proven track record of answering those questions correctly. The distinction between general commentary and real investment solutions becomes more important as AI tools move deeper into financial workflows and investors demand answers they can verify, not just answers that sound convincing.

Out of The Black Box

AI investing tools fall into two categories: systems that generate fast financial commentary and systems that produce verifiable analysis. New Constructs' system allows users to trace investment conclusions back to source SEC filings, review key assumptions, and understand how insights are produced.

As AI becomes deeply embedded in investing, the company believes investors should know which category their tools fall into. "An AI tool can give an answer instantly, but that does not mean the answer is right or safe to act on," Trainer said. "If you cannot see the data or source behind a recommendation, you are not meeting fiduciary standards. You are trusting a black box."

About New Constructs

New Constructs is an independent financial technology firm bringing transparency and accountability to investment research. Combining accounting expertise with patented AI technology, the company analyzes SEC filings and financial disclosures to uncover the true profitability and valuation of public companies. Its Robo-Analyst platform automates financial modeling and investment ratings across more than 10,000 securities, while FinSights, built with Google Cloud technology, demonstrates how AI can support investment analysis when grounded in trusted, auditable data. For more information, visit www.newconstructs.com.

References

• Google Cloud Events. (2026, April 24). Finsights: Financial insights and analysis using AI agents [Conference session]. Google Cloud Next 2026. googlecloudevents.com/next-vegas/session/3908823/finsights-financial-insights-and-analysis-using-ai-agents 
• Investor.gov. (2024, January 25). Artificial intelligence (AI) and investment fraud: Investor alert. U.S. Securities and Exchange Commission. investor.gov/introduction-investing/general-resources/news-alerts/alerts-bulletins/investor-alerts/artificial-intelligence-fraud 
• New Constructs. (2025, November 6). New Constructs partners with Google Cloud to launch FinSights. Newswire. newswire.com/news/new-constructs-partners-with-google-cloud-to-launch-finsights-22669374
• Salt, H. (2026, January 26). How to teach AI to pick stocks. New Constructs. newconstructs.com/how-to-teach-ai-to-pick-stocks/
• Trainer, D. (2025, July 21). Forget Chips, AI Firms Need Higher Quality Data to Win. New Constructs. newconstructs.com/forget-chips-ai-firms-need-higher-quality-data-to-win/
• U.S. Securities and Exchange Commission. (2024, March 18). SEC charges two investment advisers with making false and misleading statements about their use of artificial intelligence [Press release]. sec.gov/newsroom/press-releases/2024-36
• U.S. Securities and Exchange Commission. (n.d.). Search filings. sec.gov/search-filings

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SOURCE New Constructs