OPTIMAL METHODS OF NEWS FLOW TOPIC MODELLING FOR INDICATING ARTICLES, WHICH INFLUENCE ON CREDIT RISKS
The objective of this research is to find an optimal filtering algorithm for the news stream, which may have an impact on the efficiency of the models used by financial institutions for assessing probability of Russian companies default. The scientific novelty of the research lies in the building first stage of news articles conveyor, which will allow assessing companies’ ability to pay on its obligations in an autonomous online mode that does not require human attention. As a result, there was found algorithm that allows assigning a predetermined topic to each article based on the words it contains.