M&A Analytics

When companies buy or merge with other companies, they need to know what the target is worth, whether the deal makes financial sense, and what the combined business will look like. M&A analytics projects provide this analysis. The goal is to give decision-makers a rigorous and clear view of the financial implications of a transaction, based on available data and clearly stated assumptions.

The work involves building financial models, gathering data on the target company, and preparing materials for investment decisions. You build models to value the target, estimate synergies, and test assumptions about future performance. Due diligence work involves checking whether the target's financial data is accurate and identifying risks that could affect the value of the deal.

The main tools are Excel and Python. Key methods include discounted cash flow analysis, comparable company analysis, and scenario modelling. Understanding accounting and corporate finance is important, as is the ability to work with incomplete or uncertain data and communicate findings to senior stakeholders under time pressure.

M&A analytics work appears in investment banking, private equity, and corporate finance teams at large companies. It connects to the Strategist and Data Analyst roles. In the Netherlands, M&A transactions involving listed companies are supervised by the AFM, and large deals may require approval from competition authorities.