Mining Credit Interest Rate Data from Multiple Data Sources

By this research we provide description of developed web-application used for data mining of credit interest rates from different data sources. The application supports different formats of data such as xls, csv, xml, json. The project uses microservice architecture that structures the application as a collection of services. We have described in detail database acquisition that is easily scalable due to the use of an object-oriented paradigm. The application allows collecting useful data for credit interest rates, characterized by its significant role in decision-making.