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by paulpauper·15d ago·view on hn ↗
AI financial advice encourages people to save more, diversify their investing, and take on less risk as they age.

sounds like pretty generic advice. I thought they meant it gives good stock picks or trading strategies. That would be noteworthy. This is just "meh".

6 comments
> I thought they meant it gives good stock picks or trading strategies

Sadly, Gemini Flash fails to demolish individual stock picking as a strategy.

Its response included a very lukewarm note picking the few winners is hard, but no further warnings about just how hard (essentially impossible).

Thinking mode didn’t produce any better caveats.

I guess I’ll read the article, but this doesn’t sound like advice that is going to put financial planners out of business.

You need to feed it high quality data. Try Gemini Notebook, but this time load up a spreadsheet of fundamentals information for all US stocks or ETFs. The answer will differ and be much more nuanced.

I dont think you can rely on an out of book chat agent today to have all the necessary information at its disposal - even if you can pull a stock quote in ChatGPT, it doesn't mean it's going to look at PE multiples on 5000 stocks...

I have to assume that there are hedge funds or someone like that, already investing extensive effort into trying to get AI to beat the market. I assume that it can't, but if I'm wrong then whoever figures this out stands to get extremely rich.
Though almost a year old (may be too long in LLM age), just sharing a meta-article on LLM applications in different areas of finance.

Large Language Models in equity markets: applications, techniques, and insights, Frontiers in Artificial Intelligence, A. Jadhav and V. Mirza, 27 August 2025, DOI: 10.3389/frai.2025.1608365.

Personally, I am using LLM, mostly for analyzing and shortlisting companies for in-depth analysis, for investing in Japanese equity market for over a year with relatively decent results.

well, we find a material difference when using defined inputs to constrain and optimize agent responses. For example, there are some things that a generic ai couldn't do well out of the box, but is essential to long term household stability: constant monitoring, financial synchronization, and deterministic calculators and data retrieval subsystems. mostly, memory, of users' decision points and financial history. memories are built over time and far outlive a generic AI's chat context.
It is mentioned in the article that without context, it does give generic fail safe advice, but as the prompts get better it would also lead you to the right direction.
I also think it is actually most challenging to change peoples behavior and neither YT gurus nor static AI models can (maybe an agent with appropriate tools could)
Not just Generic. Any of the finance guys on YouTube that aren't grifters will say this. Post-train on a single one of them and boom AI is a financial guru.