Design of Financial Data Analysis and Decision Support System based on Big Data

Abstract

A cutting-edge Decision Support System (DSS) utilizing Deep Reinforcement Learning (DRL) for improved financial data analysis is the primary focus of the proposed research. In light of the prospering difficulties presented by large information in the monetary space, our creative methodology outfits the force of DRL to foster a powerful and versatile framework. By flawlessly incorporating DRL into the DSS structure, we mean to improve the framework’s capacity to break down huge and complex monetary datasets. This DSS not only provides financial professionals with intelligent decision-making support but also real-time insights into market trends and patterns. The collaboration between enormous information investigation and DRL works with a dynamic and responsive framework equipped for adjusting to the quickly developing financial scene. Our exploration adds to the headway of choice by tending to the particular requests of monetary information, consequently enabling clients with ideal and informed dynamic abilities. The proposed DRL-based DSS addresses a change in perspective in monetary information examination, offering a versatile and effective answer for exploring the intricacies of enormous information in the financial area. This examination holds huge potential for changing dynamic cycles, advancing monetary security, and at last adding to the progression of the more extensive monetary industry.