Forecasting and Measuring Financial Performance in Banking Sector

Commercial banks, Data Envelopment Analysis; decision-making units, Efficiency.

Abstract

This study forecasts and measures financial performance in the banking sector using Grey Prediction and the DEA Malmquist model to assess the operational performance of 27 banks during the period 2020 to 2024. Output variables include operating costs, customer deposits, assets, liabilities, and output variables include loans and income. The results show an average Malmquist productivity index of 1.064 during the period 2020 to 2024, reflecting that most banks (13 entities: D3, 5, 6, 7, 10, 11, 13, 16, 19, 21, 22, 23, 25) achieved optimal performance throughout the study period. On average, DMU19-SHB had the lowest score, while DMU3-LDB had the best. Furthermore, Decision Units (DMUs) were divided into two groups based on their average performance during the years 2020 to 2024. Group 1 consisted of the top three banks with the best average performance: DMU3-LDB, DMU22-SCB, and DMU25-ICBC. Group 2 consisted of the three banks with the lowest average performance: DMU26-BOC, DMU18-VCOM, and DMU2-APB.

However, during the period 2025-2026, most large commercial banking units (DMUs) operated efficiently, with an MPI score above 1. Only 5 DMUs, namely DMU8-PSVB, DMU18-VCOM, DMU24-MB, DMU26-BOC, and DMU27-FCB, operated inefficiently, with an average score below 1. DMU15-KSB showed a slight improvement in its MPI score at 1.075 during this period. The average MPI of all DMUs was 1.066. Among the 27 banks, DMU7-JDB exhibited the most stable operational performance across all periods. Furthermore, it is noteworthy that from 2025 to 2027, most banks are expected to maintain their high level of efficiency.