Principal Component Analysis - Comparative Study on Performance of Axis Bank and Indian Bank

Abstract

Principal component analysis (PCA) is a technique for reducing the dimensionality of such datasets, increasing interpretability but at the same time minimizing information loss. In this article, we have applied PCA to analyse a range of financial indicators such as capital adequacy, asset quality profitability, liquidity and efficiency across Axis and Indian bank. This study has been carried out using the data from 2014 to 2023. In this article PCA analysis has grouped the both banks using thirteen years financial data into three major components such as operating Income Ratio, Net profit Ratio and Expenses ratio. The two banks Axis banks and Indian bank have been taken for analysis. Thirteen financial indicators have been taken for the study and it have been grouped into three components in AXIS bank such as Operating Ratio, Net profit Ratio and Expenses Ratio and two components in Indian bank like Operating Ratio and Net profit Ratio. The result of this analysis reveals the underlying dimensions of bank performance and highlight the most significant factors influencing bank efficient performance. Additionally, the study examines how these factors changed over time and the article provides valuable insights into complex dynamics of bank performance and contributes suggestions for efficient bank management