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Journal of Applied Mathematics and Computation

DOI：http://dx.doi.org/10.26855/jamc.2023.06.013

# Bank Efficiency Evaluation and Bankruptcy Cause Analysis

Linhong Liu

Sichuan University of Science & Engineering, Zigong, Sichuan, China.

*Corresponding author: Linhong Liu

Date: July 31,2023　Hits: 286

### Abstract

In the country's economic and social development, banks play an important role in decision-making. The bankruptcy of banks will have varying degrees of impact on enterprises and individuals. For the five tasks given in the title, this paper uses PCA combined with optimization algorithm projection pursuit evaluation + hierarchical clustering, variance analysis, machine learning algorithm, FCM clustering and error inspection model to solve the problem, and achieved relatively good results. Good solution. In order to evaluate the bank's efficiency and solve the dividing line of bank failure efficiency, use MATLAB to first reduce the dimension of up to 19,720 lines of big data to 5 using the PCA algorithm, and then use the projection pursuit algorithm combined with simulated annealing to calculate the optimal index weight, and then Further weighted to calculate the evaluation value; then use hierarchical clustering to aggregate the data into two categories, the midpoint between the center points of the two categories, the corresponding data is the cut-off point, and the connection line of each indicator data is the bank failure efficiency score. boundaries.

### References

[1] Jan, A., Marimuthu, M., Shad, M. K., Ur-Rehman, H., Zahid, M., & Jan, A. A. (2019). Bankruptcy profile of the Islamic and conventional banks in Malaysia: a post-crisis period analysis. Economic Change and Restructuring, 52, 67-87.

[2] Yunita, P. (2020). The future of Indonesia Islamic banking industry: Bankruptcy analyzing the second wave of global financial crisis. International Journal of Islamic Economics and Finance (IJIEF), 3(2), 199-226.

[3] Wang, X., & Hasuike, T. (2020, December). Least-distance Data Envelopment Analysis Model for Bankruptcy-based Performance Assessment. In 2020 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) (pp. 235-239). IEEE.

[4] Chien, F., Pantamee, A. A., Hussain, M. S., Chupradit, S., Nawaz, M. A., & Mohsin, M. (2021). Nexus between financial innovation and bankruptcy: evidence from information, communication and technology (ict) sector. The Singapore Economic Review, 1-22.

[5] Surepno, S., & Swissa, E. M. (2021). Prediction of Bankruptcy in Islamic Banking in Indonesia: Modified Altman Z-Score Method Approach. Al-Masharif: Jurnal Ilmu Ekonomi dan Keislaman, 9(2), 152-167.

[6] ben Jabeur, S., Mefteh-Wali, S., & Carmona, P. (2021). The impact of institutional and macroeconomic conditions on aggregate business bankruptcy. Structural Change and Economic Dynamics, 59, 108-119.

[7] Mansouri Rad, H., & Bagherian, B. (2023). Importance-performance analysis (IPA) of banking factors affecting the improvement of business environment and prevention of corporate bankruptcy through the IPA model. International Journal of Nonlinear Analysis and Applications, 14(1), 459-471.

[8] Satyanarayana Puchakayala, N. V. V., & Veluchamy, R. (2023). Post-mortem analysis of dirty dozen companies referred by Reserve Bank of India to insolvency and bankruptcy code. SN Business & Economics, 3(4), 89.

### Full-Text HTML

Bank Efficiency Evaluation and Bankruptcy Cause Analysis

How to cite this paper: Linhong Liu. (2023) Bank Efficiency Evaluation and Bankruptcy Cause Analysis. Journal of Applied Mathematics and Computation7(2), 312-316.

DOI: http://dx.doi.org/10.26855/jamc.2023.06.013