How to Build an AI Financial Advisor With Just a Few Prompts

The New Age Of Financial Advice Is Robot Powered

Imagine having your own financial advisor, a tool that tracks every penny, analyzes your spending, and even suggests smarter investment strategies.

Now imagine it works 24/7, doesn’t charge a fee, and adjusts to your needs in real time.

That’s the power of an AI financial advisor.

With basic AI tools and a bit of planning, you can set up a system that handles your finances like a pro.

You just let the AI process the heavy data and sit back as it highlights missed opportunities and actionable insights.

But to make this work, you need the right tools, the right data, and the right strategy.

Gather and Organize Your Financial Data

Before you can build an AI that works for you, you need to give it something to work with, your financial data.

This includes everything from your bank statements to investment portfolios, credit card expenses, and even your utility bills. The more comprehensive the dataset, the better the AI’s insights will be.

Here’s a list of what you should put together, ideally putting each in a CSV or JSON format so it’s easy for the AI to read.

• Investment Portfolios: Share data on your stocks, bonds, mutual funds, or ETFs. Include purchase dates, current values, and any performance metrics. This allows the AI to evaluate your diversification, risk exposure, and potential growth areas.
  

• Bank Statements: Include detailed transaction histories from your checking and savings accounts. Look for recurring patterns, subscription fees, and unusual expenditures that the AI can flag for budgeting improvements.
  

• Credit Card Expenses: Upload detailed credit card statements highlighting categories of spending. AI can identify excessive interest charges, unused subscriptions, or opportunities to maximize reward points.
  

• Utility Bills: Provide monthly bills for electricity, water, internet, and more. This helps the AI detect seasonal fluctuations or areas where you can reduce costs by switching providers or adjusting usage.
  

• Loan and Debt Information: Include data on student loans, mortgages, personal loans, or car payments. Ensure the dataset includes interest rates, outstanding balances, and payment schedules. This enables the AI to suggest strategies for faster repayment or refinancing options.
  

• Income Records: Add pay stubs, freelance payments, or other income sources. The AI can then provide advice on optimizing savings contributions or aligning expenditures with your earnings.
  

• Recurring Subscriptions: Gather data from streaming services, gym memberships, or software subscriptions. The AI can identify redundant or underused subscriptions and recommend cancellations.
  

• Insurance Policies: Include health, auto, home, or life insurance details. With this, the AI can suggest coverage adjustments or identify overlaps in policies.

Start by exporting all your financial data from wherever it’s stored.

Most banks, credit card companies, and investment platforms allow you to download transaction history in CSV or Excel formats.

If you’re using budgeting tools like Mint or YNAB, you can export consolidated reports from there, too.

Next, make sure this data is clean and organized. Remove duplicate entries, format the dates consistently, and categorize expenses in a way that makes sense for your goals.

For example, separate "groceries" from "dining out" or "fixed expenses" like rent from "variable expenses" like subscriptions. This clarity will help the AI make more accurate suggestions later.

If you’re overwhelmed by messy data, don’t stress. Tools like OpenRefine or Google Sheets can help you clean it up quickly.

And if you’re dealing with PDFs, use converters like Adobe Acrobat or free online tools to turn them into spreadsheets the AI can process.

Once everything is ready, save your files into a single folder and name them clearly: “BankTransactions_Jan2024.csv,” “CreditCardExpenses_2024.xlsx,” and so on. This way, when you upload them, the AI can understand the context better.

Now that your data is ready, it’s time to feed it to the AI. Let’s look at how to make this process seamless.

Feeding Your Data to the AI

Now that your financial data is organized, it’s time to load it into the AI. The goal is to create a streamlined process so you can upload your files in bulk and let the AI handle the heavy lifting.

Start by selecting an AI platform that supports document processing and natural language querying. Tools like ChatGPT with Code Interpreter, Google Colab with Python scripts, or specialized platforms like Tableau GPT are excellent for this purpose.

If you’re looking for something simpler, tools like Zapier AI can help automate the data upload process.

Here’s how to make it seamless:

1. Upload Files Directly: Start by dragging and dropping your CSVs, Excel files, or PDFs into the platform’s interface. For example, if you’re using ChatGPT, simply upload your cleaned-up financial files. The AI will parse the information and convert it into usable data.
   

2. Automate File Reading: If you’re dealing with recurring data, set up a system where your files are auto-uploaded from a cloud storage service like Google Drive or Dropbox. This way, every time you export your financial statements, they’ll sync with the AI automatically.
   

3. Define Data Context: Once uploaded, you’ll need to help the AI understand the structure of your files. For example, you might say:
   

   • “Column A contains transaction dates, Column B lists amounts, and Column C categorizes expenses.”
     

   • If you’ve already categorized your data, let the AI know so it can focus on higher-level analysis rather than sorting expenses.
     

4. Verify Data Parsing: Run a quick check to make sure the AI has understood your files correctly. Ask it questions like:
   

   • “What’s the total expenditure for January?”
     

   • “What are the top 3 categories I spent on last month?” If the results don’t look right, double-check your file formatting and re-upload if necessary.

Once the data is fully loaded and verified, your AI financial advisor is ready to start working. Let’s move on to how to extract valuable insights and set specific goals.

Setting Your Financial Goals

Before diving into analysis, define the purpose of your AI financial advisor.

What do you want it to achieve for you?

Clear goals will ensure the AI tailors its recommendations to your specific needs.

For instance:

• Are you trying to save for a house? Set a savings target, like $20,000 in 18 months, and let the AI map out how much you need to save monthly.
  

• Do you want to reduce unnecessary expenses? Instruct the AI to highlight recurring charges or high spending categories.
  

• Are you building an investment portfolio? Ask the AI to identify areas where you can allocate funds for maximum growth.

To set these goals effectively, use prompts like:

• “Analyze my spending and identify areas where I can cut back.”

• “Based on my current income and expenses, how much can I save monthly?”

• “Suggest an investment strategy for a conservative risk profile.”

The AI can then cross-reference your goals with your uploaded financial data and provide actionable advice.

Extracting Actionable Insights

Now that your financial data is loaded and your goals are clear, it’s time to let the AI do what it does best: analyze and provide insights.

This step transforms raw data into a roadmap for achieving your financial objectives.

Start by asking the AI targeted questions about your financial situation. The more specific you are, the better the insights will be.

For example:

• “What’s my average monthly spending on dining out over the past six months?”

• “Which subscriptions can I cancel to save money?”

• “What percentage of my income am I currently saving?”

The AI will sift through your data and present concise answers or even detailed breakdowns.

Optimizing for Savings

Let’s say you want to cut unnecessary spending. The AI might point out recurring expenses you’ve overlooked, like unused gym memberships or redundant streaming services.

Once identified, you can take immediate action to cancel or renegotiate those costs.

Pro Tip: Use prompts like “Identify expenses under $20 that repeat monthly” to catch small charges that add up over time. These are often overlooked but can be significant contributors to overspending.

Tracking Spending Habits

If your goal is to budget more effectively, the AI can categorize your spending into buckets like housing, groceries, and entertainment. It can also highlight categories where you’re exceeding your targets.

For example:

• “You’ve spent 15% more on dining out this month compared to last month. Adjust to save $150.”

This granular insight makes it easy to adjust your habits in real-time.

Investment Opportunities

If your focus is on building wealth, the AI can analyze your savings and suggest how much you can allocate toward investments. It might even recommend specific asset classes based on your risk tolerance and financial goals.

For instance:

• “You have $5,000 in unused cash flow. Consider putting $2,500 into a diversified ETF portfolio and $2,500 into a high-yield savings account.”

By regularly extracting insights, you create a feedback loop that ensures you stay on track and make data-driven decisions.

Scaling Your AI Financial Advisor

Once you’ve mastered the basics, it’s time to scale your AI financial advisor for even greater efficiency and functionality.

This involves integrating advanced features, handling more complex financial tasks, and broadening its capabilities to suit long-term goals.

Adding Multi-Account Management

If you’re juggling multiple bank accounts, credit cards, or investment portfolios, scaling your AI to handle these can simplify everything.

Start by linking all your accounts through APIs provided by financial institutions or aggregators like Plaid. This allows the AI to pull data from various sources into one unified dashboard.

Use prompts like:

• “Analyze spending patterns across all accounts and provide a consolidated report.”

• “Identify the best-performing investments across my portfolios.”

By consolidating data, the AI can identify redundancies, such as overlapping fees, and optimize your financial strategy.

Advanced Budgeting and Forecasting

Leverage the AI to create multi-year financial forecasts. This is particularly useful for major life events like buying a home, starting a business, or planning retirement.

For example:

• “If I save $1,000 per month, how long will it take to afford a $20,000 down payment for a house?”

• “What’s my projected net worth in five years if my investments grow at 7% annually?”

These forecasts empower you to plan strategically and adjust for unexpected expenses.

Tax Optimization

Tax season can be a headache, but your AI financial advisor can make it much smoother. By analyzing your income, expenses, and investments, it can suggest ways to minimize tax liability.

Prompts for this include:

• “List all deductible expenses from the past year.”

• “How much should I contribute to my IRA to lower taxable income?”

You can even program the AI to generate reports that streamline filing with your accountant.

Best Financial Advisor Prompts to Use

1. "Using the past six months of transaction data, identify spending patterns and predict future expenses for specific categories like groceries or entertainment. Recommend how to allocate funds dynamically based on predicted needs."
   
   This advanced prompt enables the AI to forecast your spending trends and suggest real-time adjustments, making budgeting a proactive process rather than a reactive one.

2. "Analyze this CSV file of my portfolio's transaction history. Calculate metrics like weighted average return, Sharpe ratio, and diversification levels. Based on the data, recommend the top three reallocation strategies to optimize for risk-adjusted returns."
   
   By feeding the AI detailed data, this prompt generates high-level insights typically offered by professional portfolio managers.

3. "Evaluate my subscription services from this itemized list and cross-check similar services for cheaper alternatives or bundled discounts. Rank them by importance and return on value to prioritize potential cancellations."
   
   This goes beyond simply identifying wasteful subscriptions, it seeks out better deals and provides a ranked framework for decision-making.

4. "Given this breakdown of my monthly income and expenses, simulate three different savings scenarios with varying levels of risk: conservative, balanced, and aggressive. Include detailed projections for each scenario over a 10-year period."
   
   This prompt creates long-term financial roadmaps tailored to different risk appetites, helping you plan smarter and diversify strategies.

5. "Assume I have $10,000 to invest and provide a tailored asset allocation strategy using historical data. Focus on a 5-year horizon with a target annualized return of 8%. Justify each recommendation with data-backed rationale and potential risks."
   
   Instead of generic advice, this prompt forces the AI to provide calculated strategies and back them up with detailed reasoning.

Pro tip: Begin each prompt with “act as a financial advisor” to put your AI in the best “headspace” for the task and. get even better results.

The BMM Takeaway

The beauty of AI is its adaptability. As you refine your inputs, such as feeding it more comprehensive transaction data or portfolio metrics, the advisor becomes smarter and more personalized.

But remember, the real power lies in how you act on the insights it provides. AI can show you the map, but the journey is yours to take.

Here’s an advanced way to level up: Continuously refine your prompts as your goals evolve.

If you notice gaps in the AI’s analysis, tweak your inputs or add new dimensions of data, such as historical market trends or peer comparisons. Use its feedback not just as answers but as fuel for better questions.

Disclaimer: AI tools, including financial advisors built with platforms like ChatGPT, are only as reliable as the data and instructions you provide. While they can offer valuable insights and recommendations, they are not a substitute for professional financial advice. Always double-check critical decisions with a licensed financial advisor or conduct your own independent research.