FINANCIAL STATEMENT ANALYSIS OF NTPC.

Abstract

In today’s data-driven environment, traditional methods of financial statement analysis are evolving rapidly with the integration of advanced software tools and automation. This study focuses on analyzing the financial performance of NTPC Ltd., one of India's largest energy conglomerates, through a software-assisted approach. By using tools such as Microsoft Excel, Python (Pandas, Matplotlib, Seaborn), and Power BI, the project automates the extraction, processing, visualization, and interpretation of financial data from NTPC's annual reports and balance sheets.The primary objective is to assess key financial indicators including profitability, liquidity, solvency, and efficiency using ratio analysis, trend analysis, and common-size statements. Python scripts are used to clean and transform raw financial data, enabling time-series analysis and forecasting models. Interactive dashboards created with Power BI allow dynamic visualization of NTPC’s revenue, expenses, and cash flow trends across multiple years, offering stakeholders a clear and concise view of the company’s financial health.Furthermore, the use of machine learning techniques such as linear regression and time-series forecasting models helps predict future performance metrics, giving deeper insights into financial sustainability and risk management. The integration of software tools not only increases accuracy and efficiency but also empowers users to make informed, realtime strategic decisions based on quantitative evidence.This project demonstrates that the application of financial technology (FinTech) significantly enhances the quality of financial statement analysis by reducing manual errors, improving data clarity, and supporting predictive insights. The results indicate that NTPC Ltd. maintains a stable financial position but highlights areas where optimization and cost control could further enhance shareholder value.