Financial modeling is building a spreadsheet that predicts a company's future financial performance. Analysts build models using historical data, assumptions about growth, margins, and capital expenditure, and project income statements, balance sheets, and cash flow statements into the future. It is the core technical skill in investment banking and corporate finance.
Key model types: DCF model (intrinsic valuation), LBO model (PE deal analysis), merger model (M&A impact), and three-statement model (linked financial statements). Investment banking interviews invariably include model-building tests. Excel is the primary tool, though Python is increasingly used for complex models.
The famous saying: "All models are wrong, but some are useful". A model is only as good as its assumptions — change revenue growth by 2% and the valuation can shift by 30%. This is why sensitivity analysis (testing different assumptions) is critical. Top investment banks like Goldman Sachs and Morgan Stanley hire analysts specifically for their modeling skills.