For financial institutions, it is important to monitor the performance and performance factors of corporate customers. Financial institutions accumulate large amounts of data to monitor customer information including their performance. It is relatively easy to extract information on performance from structured data, while it is difficult for non-structured data like text data. In this research, we tried to extract sentences that represent customer's performance factors from text data created by financial institutions. Our proposed method using deep learning extracts sentences similar to sentences prepared as correct examples in advance. Due to the difference in properties of text data, our method showed better performance than the prior research.
