Financial analysis is the examination of the details of a business’s financial performance. This may begin with a relatively simple analysis of a company’s balance sheet, cash flows and liabilities, and other accounting data from its operating history, along with research on the larger economic and regulatory context in which it must compete. However, this examination of historical data is often just a first step; more in-depth analysis seeks to project the likely future performance of a company.

This financial analysis of a company is important for internal stakeholders looking for ways to improve performance, as well as for potential lenders or investors trying to ascertain whether it is wise to give the business money. Regardless of whether they’re working in a company’s finance department or at a private equity firm, analysts must apply a mix of complex financial modeling tools to develop a robust picture of the company’s financial health to inform decision-making on investments worth millions or even billions of dollars.

For example, linear programming (LP) techniques seek to optimize financial problems such as debt/equity ratio or portfolio construction, typically using spreadsheet programs like Microsoft Excel and Solver. For predicting future performance, regression analysis techniques are typically used, as well as probabilistic modeling using Monte Carlo methods of simulation to identify areas of potential risk. These more complex statistical approaches may use Excel, but increasingly rely on more powerful programming tools such as Python.