Article
FINANCIAL STATEMENT ANALYSIS OF HEROMOTOCORP
The financial statement analysis of a company serves as a vital instrument in assessing its performance, sustainability, and long-term value creation for stakeholders. In this research, we conduct a detailed financial statement analysis of Hero MotoCorp Ltd., the world’s largest manufacturer of two-wheelers, by integrating conventional ratio analysis with advanced software-enabled techniques, including machine learning (ML) and deep learning (DL). The purpose of this hybrid framework is to not only evaluate historical and current financial performance but to also develop models that can forecast future trends, detect anomalies, and support strategic decision-making. Traditional financial analysis is often constrained by human interpretation, limited dimensions, and backward-looking metrics. To counter this, we utilize intelligent systems that leverage historical data, industry variables, macroeconomic factors, and financial indicators to build predictive models. ML algorithms such as Random Forest and SVM assist in classification and regression tasks, while deep learning models like LSTM offer robust forecasting capabilities. The integration of NLP-based sentiment analysis further enriches insights drawn from financial news and earnings calls. This approach is novel in the Indian automotive context and provides Hero MotoCorp with a framework for automated financial monitoring, credit risk profiling, and strategic planning. Our results highlight how data science and financial expertise can converge to create intelligent platforms that reduce decision latency and increase financial accuracy, thereby setting a new benchmark in corporate finance.
Full Text Attachment
