Financial Performance Analysis of Mergers and Acquisitions in the Indian Automobile and Banking Industries

Abstract

In the present dynamic and unpredictable business environment, both the automobile and banking sectors are undergoing intensified competition from both domestic and international markets. To address these challenges and achieve survival, growth, and competitive advantage in such environments, a firm must implement strategic initiatives, including mergers and acquisitions as well as corporate restructuring. These approaches enable organizations to consolidate resources, achieve economies of scale, and enhance operational efficiency, thereby strengthening their market position in an ever-evolving global environment. Like all other industries, the financial services industry is also experiencing merger waves; so as mergers of various Indian banks are also occurring, leading to the emergence of large banks as well as large financial entities. The automobile companies and bank mergers will help boost the Indian economy in present and future eras. In this study, Indian bank mergers that took place between 2007 to 2019 and automobile company mergers that took place between 2008 to 2016 have been used for analysis. Our objective in this paper is to assess the post-merger effect on financial efficiency resulting from automobile companies and bank mergers. We evaluate different financial information, such as return on equity, current ratio and profit margin ratios, which are calculated from the financial statements of the merged automobile firms and banks. This study also aims to determine the change in the profitability of automobile companies and banks after a merger and its effect on shareholder wealth. The effect will be studied by comparing the data of merged banks for example five years’ data before the merger and five years’ data after the merger. Data were collected from secondary sources such as the annual reports of banks, published research papers, and different websites. The research methodology includes application of non-parametric techniques, Grouped Malmquist Index Data Envelopment Analysis (DEA) and A Simple Method by Ratio Analysis. Data Envelopment Analysis (DEA) employs efficiency analysis by comparing decision-making units (DMUs) to their most efficient counterparts, known as the efficient frontier, rather than to average performers. This method is utilized to establish benchmarks for units that are identified as inefficient.