PurposeMergers and acquisitions (M&A) are increasingly being adopted as a strategic approach to consolidating financial institutions and banks, with a focus on enhancing capital strength, broadening business operations and maintaining financial stability. Operational efficiency within the banking sector is crucial for effective functioning and delivering quality services to customers. This study analyzes the efficiency of large-scale mergers involving several Indian public sector banks announced between 2016 and 2019.Design/methodology/approachThe study used Data Envelopment Analysis (DEA), Logistic Regression, Malmquist Productivity Index (MPI) and Stochastic Frontier Analysis for the analysis purpose.FindingsThe results from DEA indicate that the average efficiency of merged public sector banks improved post-merger, with four out of six banks achieving technical efficiency in the post-merger period. However, efficiency varied, with OTE scores ranging from 65.8 to 100%. The SFA analysis shows that loanable funds are key drivers of both interest and non-interest income, while significant inefficiencies, particularly in labor, require attention. Physical capital plays a secondary role in income generation. The Malmquist productivity index analysis reveals a 1.6% average productivity growth in the post-merger year Y+1, driven by technological change, with positive TFP in Y+1 and Y+2 and a decline in Y+3. Only four of the six merged banks, namely Bank of Baroda, Union Bank of India, Canara Bank and Punjab National Bank, achieved positive TFP growth, primarily due to improvement in technical efficiency. Additionally, the logistic regression analysis indicates that asset quality and size have statistically significant regression coefficients in predicting operational technical efficiency (OTE).Originality/valueThis paper will contribute to the existing literature of banking, mergers and acquisitions and financial economies.