The Riksbank (Sweden’s Central Bank) releases the minutes of the Monetary Policy Meetings every two months. SEB Bank, as most of the players in the market, analyzes and creates reports about the opinion of each board member of Riksbank, to know how market changes. The goal of this work was to create automatic tools to help the Research Team of SEB. Two text mining techniques have been used: Sentiment analysis, to uncover the position (Hawkish or Dovish) of each Board Member, and Summarization, to analyze the most important statements in the minutes. In particular, a human-based topic summarization algorithm isused to summarize beliefs for each board member on different topics.