Nowadays, a limited amount of Credit Default Swap data stops the improvement of Credit Management capability. A more outstanding risk simulator is able to help the financial institution such as JP Morgan claim a dominant position in the market. The most important factor to build a great simulator is a sufficient amount of data. Thus, our goal is to tackle the problem of lacking sufficient supplementing data by applying the Generative Adversarial Network (GAN). One advantage of GAN is creativity. Creative GAN can be used to generate new data based on the input data.
