The automatic analysis of financial reports and regulatory disclosures published by international banks is a complex task, due to the size, structure, and technical language of these documents. This thesis presents a system that uses artificial intelligence to answer questions about such documents in natural language, helping extract important financial information such as CET1 ratios, total assets, and classifications of assets and liabilities. The approach follows a two-step strategy. First, each document is divided into smaller parts, called "chunks", which are turned into numerical representations and stored in a database. When a user asks a question, the system searches this database to find the most relevant chunks.