How to analyze my stock portfolio with AI

Portfolio analysis is not just “am I up or down?”, that is a glance, not analysis. Useful portfolio analysis answers:

• Concentration. What percent is in any single name, sector, or theme? See how to check portfolio concentration.
• Attribution. Which positions drove gains? Which dragged?
• Exposure vs intent. If you said “I am investing in AI infrastructure,” does the portfolio actually reflect that?
• Benchmark. Are you actually beating a simple index, or just tracking it? See how to compare your portfolio to the S&P 500.
• Cash and liquidity. How much dry powder do you have, and how fast could you raise more?
• Risks you have not named. Currency, interest-rate, single-customer, regulatory.

Each of these is a question your broker's default dashboard rarely answers cleanly. The right AI tool can answer all of them.

Under the hood, every one of these tools does the same three things in some form. Understanding the mechanism helps you tell a real analyzer from a chatbot with a finance skin.

• It reads your holdings. Either you link an account through a regulated data aggregator (Plaid or a broker API), or you upload a CSV, or you paste positions into a chat. Account linking is read-only by default and keeps your credentials at the broker. Without your real positions and weights, any “analysis” is generic.
• It computes the numbers deterministically. Concentration, sector and theme rollups, benchmark-relative return, and drift are arithmetic, not opinions. Good tools calculate these with code, not by asking a language model to do mental math, then hand the results to the AI.
• The AI explains and prioritizes. The language model turns those numbers into plain-English findings, ranks what matters, and answers follow-up questions (“why is this risky?”, “what would I sell?”). This is where Claude or ChatGPT earns its place: synthesis and conversation, not the raw math.

Dashboards like Empower and PortfolioPilot present the output as charts and alerts. Conversational tools like Magnifi and Walnut present it as a back-and-forth you can interrogate. Scoring tools like Danelfin, Seeking Alpha, and TipRanks skip the account entirely and rate individual stocks you then map onto your holdings by hand.

There is no single best tool; it depends on whether you want a dashboard, a stock score, a backtest, or a conversation. Here is the field, with what each is best for.

Empower

Best for: a free dashboard that tracks every account in one place. Empower (formerly Personal Capital) links your accounts read-only and shows allocation, fees, and concentration, with retirement planning on top. It is a tracker with analytics rather than a conversational AI.

PortfolioPilot

Best for: an AI second opinion across your linked accounts. PortfolioPilot connects your holdings and produces portfolio-level risk analysis, diversification scoring, and rebalancing ideas, framed as an AI investing coach.

Magnifi

Best for: conversational fund and stock discovery. Magnifi is a chat-driven assistant that lets you research, compare, and screen investments in natural language, and can connect accounts for context.

Danelfin

Best for: quantitative AI stock scores. Danelfin assigns each stock an AI Score from 1 to 10 based on thousands of features and shows the drivers behind it. It rates stocks; it does not manage or connect your portfolio.

Seeking Alpha

Best for: crowd research paired with quant grades. Seeking Alpha combines analyst and contributor articles with quant ratings and factor grades on individual stocks, useful for pressure-testing a position.

TipRanks

Best for: aggregating Wall Street analyst ratings. TipRanks rolls up analyst, blogger, and insider activity into a Smart Score per stock, so you can gauge sentiment on your holdings quickly.

Koyfin

Best for: deep fundamental data and dashboards. Koyfin gives near-institutional data, charts, and comparisons, strong for fundamental analysis of the names you already own.

Portfolio Visualizer

Best for: backtesting and optimization. Portfolio Visualizer runs factor analysis, Monte Carlo simulations, and optimizer models against historical data, ideal for stress-testing an allocation.

TrendSpider

Best for: automated technical analysis. TrendSpider detects chart patterns and backtests technical strategies, aimed at traders rather than long-term portfolio review.

Walnut

Walnut is the AI investing assistant that talks to the broker you already have and places the trades you approve. Best for: analyzing your real holdings by chatting through Claude or ChatGPT and, when you choose, acting on the answer. It is read-only by default, thematic-basket oriented, and not an investment adviser. More on how it fits below.

Features and availability change; verify the current specifics on each provider's site. For the wider category, including robo-advisors and brokerage-built assistants, see the best AI investing apps.

Since this is our site, here is the step-by-step using Walnut. The same shape (connect, ask, pressure-test, repeat) works with any tool that can read your real holdings.

1. Connect your brokerage

Sign up for Walnut and link your broker through a regulated connection, so your credentials never touch Walnut. Your positions, balances, and recent performance sync automatically, read-only by default.

2. Connect Claude or ChatGPT

Use Walnut's built-in assistant, or generate an API key on the Connections page and paste it into Claude Desktop or ChatGPT through the MCP connector. Now the AI can see your real portfolio when you ask it questions, with row-level security keeping data scoped to you.

3. Start with the four questions

Run these four prompts in sequence. They take less than five minutes and surface most of what matters:

• “Summarize my portfolio: total value, top 5 holdings by weight, top 5 by absolute gain or loss.”
• “What is my concentration risk? Any single position over 10% of the portfolio?”
• “Which of my baskets is performing best and worst over the last 30 days versus the S&P 500?”
• “If I had to sell 20% of the portfolio to raise cash, what would you suggest selling, and why?”

4. Pressure-test the bear case for each big position

Pick your top three positions by weight. For each, ask: “What is the strongest bear case here, and what would make me sell?” Write the answer down. If something the AI flagged comes true later, you will know to act faster.

5. Schedule a recurring check-in

Block 10 minutes every Friday. Open the AI tool and ask: “What changed in my portfolio this week, and is any of it worth acting on?” Most weeks the answer is no, and that is fine.

Say you own a 15-stock portfolio built around three themes: AI infrastructure, aging demographics, and clean energy. You connect Walnut to Claude and ask:

“Break down my portfolio by theme and show me which one is contributing most to year-to-date returns.”

The AI reads your basket assignments via Walnut, pulls each position's YTD return, weights it, and gives you an attribution table. You discover that AI infrastructure is 60% of the portfolio but 85% of gains, meaning a single theme is doing most of the work. That is an actionable insight you cannot get from a broker dashboard.

• Analyzing positions the AI cannot actually see. Pasting a few tickers into ChatGPT is not portfolio analysis. If the tool cannot read your real weights, its answer is a guess.
• Trusting AI math on totals. Language models are weak at arithmetic. Prefer tools that compute concentration and returns with code and let the AI explain the result.
• Confusing a stock score with portfolio analysis. Danelfin or TipRanks rate individual names; they do not tell you whether your overall allocation is sound.
• Treating AI output as a prediction. Use it for synthesis and discipline, not crystal-ball calls. No tool can promise it beats the market.