Intelligent System for Processing and Forecasting Financial Assets and Risks

Abstract

The article contains a description of the results of development and research of intelligent system for processing, accounting and forecasting financial assets and risks. An analysis of current problems and technical aspects related to the assessment of financial flows and risks of loss of assets in the context of modern market development in the field of accounting and forecasting of financial time series was carried out. A justification is given for the feasibility and effectiveness of using machine learning methods to automate the solution of operational and analytical problems in the field of accounting for financial assets. The proposed concept of using machine learning within the framework of the developed application software is described, the key aspects of its design and implementation of the software and modular structure are considered. The results of a comparative analysis of the created ACF and PACF models, assessment of the quality metrics of robotic models in different conditions when assessing financial flows and risks are presented, an analysis of the results obtained is carried out and further ways of developing the approach proposed in the article to improve its efficiency are considered.