Using ChatGPT to plan investments? Here's what AI gets wrong - and how finance teams can use it safely
AI is useful, but it isn't risk-free. Fidelity International reports that a quarter of Gen Z and millennials use AI to learn about investing. Yet some tools still miss the mark - one review found ChatGPT got roughly one in three finance questions wrong, or incomplete.
As a finance professional, you can't outsource judgment. Think of general-purpose AI as a bright intern: fast, confident, and sometimes wrong in exactly the way that costs money.
The accuracy gap you can't ignore
- Investing In The Web tested 100 personal finance questions. Results: 65% accurate, 29% incomplete or misleading, 6% wrong.
- Indulge found around a quarter of AI-generated Google overviews for finance queries were inaccurate. The punchline: they used ChatGPT to fact-check them, with human review planned next. One researcher put it bluntly - anything below 100% accuracy is a failure for this use case.
Why the misses? Flawed prompts, stale or biased training data, and a habit of sounding confident without showing working or sources. It's a smooth pitch, not audited research.
Humans aren't perfect either
The Financial Ombudsman received 1,459 complaints about advisers last year and upheld 57% of those related to mis-selling or suitability. It's a small slice of the industry, but it shows the bar you're held to - and why unchecked AI outputs won't fly.
How to invest responsibly (and keep AI in its place)
1) Set risk first, not returns
- Define risk tolerance (what you can stomach) and risk capacity (what you can afford to lose without derailing plans).
- Hold 3-6 months of essential expenses in easy-access cash before investing, so you're not a forced seller in a drawdown.
- Your age, liabilities, and dependents matter. Document this before any product decision.
2) Use FCA-authorised platforms
- Verify firms on the FCA Register. If an authorised firm fails and can't return your assets, the FSCS may cover up to £85,000 per person, per firm for eligible claims - it does not cover market losses.
- Read the fine print at the FSCS investments page.
- Apps like Trading212 can be convenient. For new investors, diversified funds and ETFs are often a cleaner starting point than stock-picking.
3) Do the groundwork
- Learn the basics: shares, bonds, funds, gilts, ISAs, fees, rebalancing, tax wrappers. MoneySavingExpert has a solid beginner overview.
- If you need regulated advice, use independent or restricted advisers who are authorised by the FCA. Verify authorisation - every time.
This is general guidance, not personal financial advice. If you're unsure, speak to a qualified adviser.
Why AI shows up in client workflows anyway
Most people can't get affordable advice. A Schroders poll suggests three-quarters of advisers won't onboard clients with less than £50,000, as percentage fees make small pots uneconomic. Banks and pension providers often can't give advice due to regulation. No surprise AI is filling the gap - with mixed results.
Regulators are adapting. The FCA is pushing for "targeted support" so firms can flag risks and cheaper options without full advice - sometimes via AI. Think: warning a customer who's drawing down a pension too quickly, or nudging investors toward lower-cost funds when appropriate.
There are real wins already. A major firm stopped a pension cash-out after spotting regular gambling on the linked current account and urged the client to get help. That's the kind of intervention AI can help surface - with a human making the final call.
What's working right now
- Advice firms are automating admin to cut costs and serve smaller clients.
- Octopus Money blends AI-generated suggestions (from a proprietary algorithm) with human money coaches.
- Cleo's chatbot "hype" and "roast" modes show how tone can drive engagement. Most users pick roast mode. Tough love works.
How to use ChatGPT for finance without getting burned
Prompt with context or don't bother
- State the objective, constraints, time horizon, fees, tax wrapper, and jurisdiction (UK) upfront.
- Ask for assumptions, sources, and alternatives. Request pros/cons and edge cases.
- Force structure: "Show calculations, list data sources, highlight regulatory considerations, and call out where information may be out of date."
Build a verification loop
- Cross-check against primary sources (FCA, FSCS, HMRC, provider docs). Don't act on a single AI response.
- Use AI for drafts, summaries, and idea generation - not final recommendations.
- Document prompts and outputs for audit. Treat it like any other tool subject to QA.
Protect client and firm data
- Don't paste personal data, account numbers, or sensitive docs into public models.
- Check privacy controls and opt-out settings if available. Use enterprise versions with data controls for client work.
- Assume prompts can be retained. Redact aggressively.
What AI should never do
- Pick products for a client without disclosure, suitability checks, and a human sign-off.
- Give tax or pension guidance that isn't verified against current UK rules.
- Replace your investment policy statement, rebalancing rules, or risk controls.
A simple playbook for teams
- Define use cases: research summaries, fee comparisons, document drafting, client education.
- Standardise prompts and checklists. Bake in UK context, sources, and risk warnings.
- Ring-fence data. Use approved tools. Log everything.
- Pilot, measure error rates, and only then expand.
Bottom line
Specialist financial AI could meaningfully improve consistency and access. But right now, treat general-purpose models as capable assistants that need supervision. You wouldn't let a smooth-talking chancer run a portfolio - don't let the robot version do it either.
If you want to explore vetted tooling that's actually useful for finance workflows, see this curated list: AI tools for finance.
Disclaimer: This content is for general information only and does not constitute personal financial advice. If you need advice based on your circumstances, consult a qualified, FCA-authorised adviser.
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