Credit ratings convey credit risk information to participants in financial markets, including investors, issuers, intermediaries and regulators. This paper proposes an automatic text analysis system for financial news and analyzes the effects of news coverage and sentiment factors on credit ratings. Our experiment results show that firms with higher news coverage received worse ratings in the next quarter. The effect is especially stronger for speculative grade firms. We have also found that news polarity is linked to credit rating in the following quarter for investment grade firms. These results suggest that news data are useful in credit rating modelling and should not be omitted in this type of research.