Abstract:
This article provides a literature review and comparative analysis of methods for solving the problem of building a credit scoring model; gives definitions of the concepts of large volumes of data (Big Data); and provides an overview of existing tools for processing and storing large volumes of data. The main problems and tasks of building credit scoring are identified. The general statement of the problem is presented. Analysis of the actual problems of assessing bank credit risk, and predicting the credit worthiness of the borrower, etc. is given. The mathematical model of mortgage lending based on the processing of large amounts of data is studied. This article discusses various technologies, including forecasting using modern technologies. This contributes to the storage of big data, as well as the passage of a parallel process. We consider the problems that arise when working with big data, and identify the need for further research, to include the use of big data processing methods for real business processes in organizations that are faced with the need to process large amounts of data. In addition, further analysis of the problems associated with modeling the processing of big data is identified.
Page(s):
2659-2670
DOI:
DOI not available
Published:
Journal: Journal of Theoretical and Applied Information Technology, Volume: 98, Issue: 13, Year: 2020