Abstract: As with any other service industry, banking industry also faced critical change in tune with the shift in demand. In Post COVID period, demand for loans, credit cards and insurance increased and the role of private banks and Non-Banking Financial Companies in providing non-collateral loans like credit cards and personal loan increased. As the automation in the banking sector made the customers independent on branches, the customers visit branches for specific reasons like loans. Each dimension has five sub-dimensions with different component variables to measure them. The weighted average is used to consolidate the response for each bank. This research is based on expert opinion (Delphi method) and 108 experts from five categories of financial institutions, nationalized banks, scheduled banks, private banks, cooperative banks and Non-Banking Financial companies. They were selected from five functions, credit cards, banking, loans, and insurance. The results show that there is a difference in perception due to difference in service quality Keywords: Analytic Hierarchy Process (AHP), Multi-criteria Decision Analysis (MCDA), SEVQUAL, weighted average, Bank JEL Classification Number: G20, O16