AI in Finance — Overview

Finance used to take time and was expensive. But now AI will become your financial analyst.

The smartest people are now using AI for financial advice. To efficiently use AI, you need the right prompts and tools solving the right problems.

Follow these 10 use-cases — each includes the use-case summary and a prompt placeholder you can copy and use in your preferred AI platform.

1. Automated Risk Assessment

Benefits: Scores client risk in seconds, adapts to new market conditions, reduces manual underwriter workload.

Example scenario: Assess credit risk for a mid-size business applying for a $500,000 loan.

Prompt


Assess the credit risk of a mid-size business applying for a $500,000 loan. Use financial statements (income statement, balance sheet), cash flow data, industry risk factors, and non-traditional signals (payment history for utilities and phone). Provide a risk score (0-100), key drivers of the score, and recommended lending terms (interest rate, collateral suggestions, monitoring triggers).

2. AI-Driven Credit Scoring

Benefits: Uses non-traditional data for scoring, improves lending to underserved markets, speeds up approval decisions.

Example scenario: Build a credit scoring model using utility and phone payment data for people in the US.

Prompt


Design a credit scoring model for US consumers using utility and phone payment data alongside traditional credit bureau data. Describe features to extract, model architecture suggestions, fairness checks, and how to validate performance on a holdout set. Provide sample feature engineering steps and evaluation metrics.

3. Portfolio Management

Benefits: Rebalances portfolios based on live data, suggests asset allocations per goals, alerts clients to re-investment opportunities.

Example scenario: Propose a moderate-risk portfolio mix for a retiree wanting 5% returns.

Prompt


Propose a diversified, moderate-risk portfolio targeting a 5% annual return for a retiree aged 65. Include suggested allocations (equities, bonds, alternatives), rationale, expected volatility, rebalancing cadence, and tax-aware considerations. Provide example ETF or fund categories (not specific tickers unless requested).

4. Compliance Monitoring and Reporting

Benefits: Scans transactions against AML rules, generates regulatory reports on schedule, flags non-compliant activities immediately.

Example scenario: List all the AML compliance checkpoints for international wire transfers.

Prompt


List and explain AML compliance checkpoints for international wire transfers. Include customer due diligence steps, sanctions screening, AML scoring thresholds, recordkeeping requirements, and reporting triggers. Provide examples of suspicious patterns and recommended automated responses.

5. Algorithmic Trading Strategies

Benefits: Backtests trading ideas at scale, executes trades based on defined rules, optimizes strategies continuously.

Example scenario: Backtest a mean-reversion trading strategy on forex pairs.

Prompt


Backtest a mean-reversion trading strategy on selected forex pairs. Describe entry/exit rules, risk management (position sizing, stop loss), performance metrics to track, and steps to validate robustness (walk-forward analysis, Monte Carlo). Provide pseudocode or algorithm outline.

6. Personalized Financial Advice

Benefits: Creates advice based on individual goals, uses life-stage and income data, scales one-to-one coaching.

Example scenario: Draft retirement planning advice for a 35-year-old with $100k saved.

Prompt


Draft a retirement plan for a 35-year-old with $100,000 saved, annual income of $90,000, and a target retirement age of 65. Include recommended savings rate, asset allocation over time, projected balances under conservative/moderate/aggressive scenarios, and suggested tax-advantaged accounts.

7. Automated Document Processing

Benefits: Parses documents, models cash flow scenarios automatically, alerts to potential shortfalls early, informs funding decisions.

Example scenario: Parse a batch of loan applications and extract key fields.

Prompt


Parse the attached batch of loan application PDFs and extract these fields: applicant name, business name, requested loan amount, annual revenue, net income, credit history flags, collateral description. Return as structured JSON and flag missing or suspicious fields.

8. Predictive Analysis for Forecasting

Benefits: Models cash flow scenarios automatically, alerts to shortfalls early, informs strategic funding decisions.

Example scenario: Forecast next quarter’s cash flow for a SaaS lender with 1,000 clients.

Prompt


Forecast next quarter's cash flow for a SaaS lender with 1,000 clients. Use subscription data (MRR, churn, upsell), typical payment delays, and historical seasonality. Provide best/worst/most-likely scenarios and recommended action items if shortfall risk exceeds X%.

9. Wealth Management Optimization

Benefits: Identifies tax-efficient investment paths, suggests portfolio tweaks for growth, monitors market shifts continuously.

Example scenario: Recommend three tax-efficient strategies for a high-net-worth client.

Prompt


Recommend three tax-efficient investment strategies for a high-net-worth client based in the US. Include pros/cons, implementation steps, and considerations around estate planning, tax-loss harvesting, and charitable giving vehicles.

10. Market Research and Insights

Benefits: Summarizes quarterly earnings calls, highlights sector trends, provides executive summaries for boards.

Example scenario: Analyze Q1 earnings from top six banks and extract three key trends.

Prompt


Analyze Q1 earnings reports from six major banks (provide PDFs or URLs). Summarize the three most significant trends across the sector, list risks mentioned by management, and provide a 3-point executive summary suitable for a board presentation.