Rebooting Business Processes of Banking Organizations When Working with Big Data

Currently, banks are beginning to embed big data in their business processes and at the same time do not optimize the business processes themselves. This leads to the fact that big data is involved in the business process and there is a good technological solution, but there are no expected effects. For example, such as: process automation, risk reduction, improving operational performance, improving process performance. The lack of expected effects when working with big data becomes a problem for the bank. The object of this work is to develop recommendations for optimizing existing business processes when working with big data. Research questions that needed to be addressed: 1. What big data implementation practices and big data development trends exist and are relevant today; 2. What problems do banking organizations face when using big data; 3. What are the business processes, metrics and business indicators in banking organizations working with big data; 4. What problems and risks exist in existing business processes. In the process of achieving the goal, the following tasks were completed: - questions on the construction of business processes in banking organizations are considered, the concept of reorganization is disclosed, qualitative and quantitative indicators of business processes are defined; - Identified and studied trends in the development of big data and the forced reorganization of banking business processes in a pandemic; - technologies for the use of large in banking organizations are considered, an analysis of experience in using big data technology in foreign and domestic banks is carried out, problems of banking organizations when working with big data are highlighted; - identified the main processes in the implementation and management of big data within business processes and the criteria for the success of their reorganization; - Developed recommendations for the reorganization of banking business processes when working with big data. The research methods used to implement these tasks include: analysis of the literature, methods for comparing the experience of applying big data technology, graphic analysis. Charts and flowcharts are used as a graphical analysis tool.