A STUDY ON BIG DATA APPLICATIONS IN FINANCIAL PREDICTION WITH REFERENCE TO TCS

Abstract

This paper investigates potential avenues for improving financial forecasting at Tata Consultancy Services (TCS) through the application of big data techniques. Also covered are methods for improving investment strategies, predicting market trends, and reducing risks through the use of AI, ML, and advanced analytics. Using a wide variety of financial data sources, TCS enhances the precision of forecasting and decision-making. The research reveals the data-centric approach the organization employs to gain real-time insights from both structured and unstructured data. Additionally, it examines the ways in which big data may improve portfolio management, fraud detection, and creditworthiness evaluation. Using TCS's big data infrastructure to manage intricate financial systems is the main focus of the research. It then goes on to demonstrate how predictive analytics can be useful for client communication and company strategy development. Operational flexibility and prediction accuracy both saw significant improvements as a result. The report goes on to detail how TCS is enhancing its continuous financial performance through innovative use of big data.