A Multi-Algorithm AIoT Framework for Sustainable Performance Assessment in Rural Banks
DOI:
https://doi.org/10.47709/brilliance.v6i4.9802Keywords:
Artificial Intelligence of Things (AIoT), Rural Banks, Sustainability Assessment, Decision Support System, Analytic Hierarchy Process, Random ForestAbstract
Sustainability assessment in Rural Banks (RBs) remains challenging due to fragmented operational data, limited analytical capabilities, and inadequate integration of economic, social, and environmental indicators. This study aims to develop an Artificial Intelligence of Things (AIoT)-based decision support framework for comprehensive, data-driven sustainability assessment in rural banking. The proposed framework integrates Global Reporting Initiative (GRI) indicators, the Analytical Hierarchy Process (AHP), a Sustainability Index, and the Random Forest algorithm. Using a Design Science Research approach, the framework was evaluated using operational and organizational data from five Rural Banks in South Kalimantan, covering 2021–2025. The dataset comprised 100 quarterly observations and 31 sustainability indicators derived from sensor-based operational monitoring and non-sensor organizational disclosures. AHP assigned the highest weight to the environmental dimension (0.38), followed by the social (0.34) and governance (0.28) dimensions, with an acceptable consistency ratio of 0.073. The Random Forest model achieved an R² of 0.87, an RMSE of 0.18, and an MAE of 0.12, outperforming Linear Regression, Support Vector Machine, and XGBoost. Feature importance and SHAP analyses identified emissions and energy consumption as the dominant indicators, followed by workplace and customer safety. These findings demonstrate the potential of integrating AIoT monitoring, multi-criteria weighting, and machine learning to improve sustainability evaluation. Practically, the framework supports transparent performance monitoring, predictive analysis, and evidence-based strategic decision-making. Future research should expand the number of participating banks and improve automated monitoring of non-sensor indicators.
References
Aguado-Correa, F., et al. (2023). Evaluation of non-financial information and its contribution to advancing the sustainable development goals within the Spanish banking sector. European Research on Management and Business Economics, 29(2), 100211. https://doi.org/10.1016/j.iedeen.2022.100211
Bais, B., Nassimbeni, G., & Orzes, G. (2024). Global Reporting Initiative: Literature review and research directions. Journal of Cleaner Production, 471, Article 143428. https://doi.org/10.1016/j.jclepro.2024.143428
Bayar, J., et al. (2025). Artificial intelligence of things (AIoT) for precision agriculture: Applications in smart irrigation, nutrient and disease management. Smart Agricultural Technology, 12, 101629. https://doi.org/10.1016/j.atech.2025.101629
Bouteraa, M., Al-Daihani, M., Chekima, B., & Baddou, A. (2026). Empirical analysis of blockchain integration and ESG moderation in sustainable digital transformation: Evidence from the banking sector. Journal of Strategy & Innovation, 37, 200564. https://doi.org/10.1016/j.jsinno.2026.200564
Braga, C. M., Suarez-Bárcena, A., Serrano, M. A., & Fernández-Medina, E. (2025). TrustAIoT: A framework for building trustworthy AIoT platforms. Internet of Things, 34, 101751. https://doi.org/10.1016/j.iot.2025.101751
Chavosh Nejad, M., Mansour, S., & Karamipour, A. (2021). An AHP-based multi-criteria model for assessment of the social sustainability of technology management processes: A case study in banking industry. Technology in Society, 65, 101602. https://doi.org/10.1016/j.techsoc.2021.101602
Choo, Y., et al. (2026). AIoT image analysis for real-time dispatching of shipyard transport devices: A focus on trailers. Expert Systems with Applications, 296, 128947. https://doi.org/10.1016/j.eswa.2025.128947
Dhal, S. B., Kar, D., & Capareda, S. (2026). Intelligent valorization: Integrating AI, imaging, and sustainability for next-generation biofuel systems. Global Energy Interconnection. https://doi.org/10.1016/j.gloei.2025.10.009
Ding, M., & Li, C. (2026). Green banking and sustainable development: Exploring energy efficiency, environmental policy, and financial resilience in emerging economies. International Review of Economics & Finance. https://doi.org/10.1016/j.iref.2026.104988
Ecer, F., & Pamucar, D. (2022). A novel LOPCOW-DOBI multi-criteria sustainability performance assessment methodology: An application in developing country banking sector. Omega, 112, 102690. https://doi.org/10.1016/j.omega.2022.102690
Emara, E. I. R., Al-Saeed, A. M., & Hamed, L. M. M. (2026). AI-driven decision support system enhances productivity, water use efficiency, and soil sustainability of strategic crops in sandy soils. Agricultural Water Management, 325, 110198. https://doi.org/10.1016/j.agwat.2026.110198
Fernández-Arroyo, E. R., Area, A. C., & Peña, D. Q. (2026). Maximizing profits and sustainability in RoR hydropower: An AI-driven hydrogen decision support model (H2-DSM). Energy Conversion and Management: X, 30, 101660. https://doi.org/10.1016/j.ecmx.2026.101660
Fernández Fernández, J. A. (2025). The architecture of sustainable banking: Financial, institutional and technical pillars for the transition to a low-carbon economy. Borsa Istanbul Review, 25, 1558–1571. https://doi.org/10.1016/j.bir.2025.10.010
Friske, W., Nikolov, A. N., & Morgan, T. (2024). Making the grade: An analysis of sustainability reporting standards and Global Reporting Initiative adherence ratings. Corporate Social Responsibility and Environmental Management, 31(3), 2098–2108. https://doi.org/10.1002/csr.2686
Ghandehariun, S., & Faghihi, S. V. (2025). Dynamic decision-support for heritage-sensitive urban regeneration: An AI-driven framework integrating socio-cultural sustainability. Results in Engineering, 28, 108189. https://doi.org/10.1016/j.rineng.2025.108189
Gupta, M. (2026). Unveiling the impact of sustainability reporting on banking performance: Role of country-specific determinants. Journal of Economics and Business, 138, 106246. https://doi.org/10.1016/j.jeconbus.2025.106246
Han, X., Samad, S., Kim, W., & Wei, F. (2025). From corporate responsibility to green loyalty: How CSR initiatives shape customer identification and pro-environmental identity in banking. Acta Psychologica, 255, 104944. https://doi.org/10.1016/j.actpsy.2025.104944
He, J., Song, C., Hu, R., & Ren, Z. (2026). LogHGAD: A hypergraph-based log anomaly detection method for AIoT systems. Journal of Systems Architecture, 170, 103630. https://doi.org/10.1016/j.sysarc.2025.103630
Huang, J., Hsieh, S.-L., & Wang, J. (2026). Sustainability disclosure and bank liquidity risk: Evidence from global banking sector. North American Journal of Economics and Finance, 83, 102582. https://doi.org/10.1016/j.najef.2026.102582
Iqrar, W., Khurshid, K., Khan, S., & Saeed, N. (2026). The AIoT ecosystem for next-generation satellite systems. Physical Communication, 74, 102967. https://doi.org/10.1016/j.phycom.2025.102967
Isayev, M., & Gokmenoglu, K. (2024). The role of shadow banking towards a sustainable growth path. Renewable Energy, 228, 120640. https://doi.org/10.1016/j.renene.2024.120640
Karim, R., et al. (2026). Unveiling the roles of green tax, financial development, banking development, fintech adoption, and economic growth on sustainable development in Bangladesh. World Development Sustainability, 8, 100277. https://doi.org/10.1016/j.wds.2026.100277
Kavuran, G., et al. (2026). AI-supported decision framework for sustainable reconstruction: Case study on TOK? housing after the 2023 Kahramanmara? earthquake. Energy, 344, 139891. https://doi.org/10.1016/j.energy.2025.139891
Ketchoua, G. S., Wirajing, M. A. K., & Ketu, I. (2025). Advancing agro-environmental sustainability in Africa: The critical role of infrastructure development and banking sector stability. Sustainable Futures, 9, 100800. https://doi.org/10.1016/j.sftr.2025.100800
Konstantakis, K. N., et al. (2024). The interconnectedness of European banking and shadow banking for sustainable development goals: Insights from a network GVAR model. Research in International Business and Finance, 69, 102232. https://doi.org/10.1016/j.ribaf.2024.102232
Kuang, W., Tang, F., Liu, J., Hu, Y., & Li, K. (2026). FGAA: Enhancing adversarial robustness in AIoT-enabled smart systems via fine-grained activation alignment. Journal of Systems Architecture, 170, 103602. https://doi.org/10.1016/j.sysarc.2025.103602
Lau, C. K., & Wong, J. C. (2023). The integration of Sustainable Development Goals into businesses sustainability management: A reporting perspective. International Journal of Disclosure and Governance, 20, 490–505. https://doi.org/10.1057/s41310-022-00164-2
Le, T. D., et al. (2025). Exploring new frontiers: Current status and future research directions for AIoT application in shrimp farming in the Vietnamese Mekong Delta. Aquacultural Engineering, 111, 102559. https://doi.org/10.1016/j.aquaeng.2025.102559
Li, Y., et al. (2025). SDR: Stackelberg-based deep reinforcement learning for multi-skill spatiotemporal task allocation in AIoT systems. Computer Communications, 242, 108283. https://doi.org/10.1016/j.comcom.2025.108283
Liao, Y., Yu, N., Zhou, G., Wu, Y., & Wang, C. (2022). A wireless multi-channel low-cost lab-on-chip algae culture platform. Computers and Electronics in Agriculture, 193, 106647. https://doi.org/10.1016/j.compag.2022.106647
Liu, H. T., et al. (2026). An AIoT-based operations guidance system for constrained industrial processes. Journal of Industrial and Engineering Chemistry. https://doi.org/10.1016/j.jiec.2026.02.003
Liu, Q., Li, X., Tan, K. H., & Ah, K. H. (2026). A review of AIoT-enabled cyber-physical systems in building energy management: Towards intelligent operation. Applied Energy, 409, 127482. https://doi.org/10.1016/j.apenergy.2026.127482
Lu, H. L., et al. (2025). AIoT-based smart greywater reuse for urban irrigation: Energy saving, carbon reduction, and biodiversity enhancement. Smart Agricultural Technology, 12, 101288. https://doi.org/10.1016/j.atech.2025.101288
Mamun, M. A. A., et al. (2025). Enhancing banking performance through regulatory technology: Analyzing cost reduction, sustainability, and profitability in Bangladesh's banking sector. Sustainable Futures, 10, 101234. https://doi.org/10.1016/j.sftr.2025.101234
Mbaidin, H. O., Alsmairat, M. A. K., & Al-Adaileh, R. (2023). Blockchain adoption for sustainable development in developing countries: Challenges and opportunities in the banking sector. International Journal of Information Management Data Insights, 3(2), 100199. https://doi.org/10.1016/j.jjimei.2023.100199
Mills, S., & Sætra, H. S. (2025). Algorithms in the room: AI, representation, and decisions about sustainable futures. Technovation, 147, 103304. https://doi.org/10.1016/j.technovation.2025.103304
Nguyen, H. H., et al. (2025). Banking in the storm: How natural disasters influence non-performing loans. Journal of Climate Finance, 13, 100076. https://doi.org/10.1016/j.jclimf.2025.100076
Phan, A. C., Nguyen, N. H. Q., & Phan, T. C. (2026). AIoT-based drowsiness level detection system using a hybrid F-LSNN network. Egyptian Informatics Journal, 33, 100910. https://doi.org/10.1016/j.eij.2026.100910
Pu, G., et al. (2024). Asymmetric impact of natural resources, fintech, and digital banking on climate change and environmental sustainability in BRICS countries. Resources Policy, 91, 104872. https://doi.org/10.1016/j.resourpol.2024.104872
Quintiliani, A. (2025). Small and medium-sized enterprises and sustainable transition: Can FinTech increase the banks' ability to support the development of SMEs? Research in International Business and Finance, 73, 102625. https://doi.org/10.1016/j.ribaf.2024.102625
Rahim, A., Islam, M. F., & Rosid, M. H. O. (2026). From employee green behavior to sustainable competitive advantage: The role of fintech adoption and sustainable performance within banking institutions. Acta Psychologica, 264, 106449. https://doi.org/10.1016/j.actpsy.2026.106449
Rahman, M. A., et al. (2024). An AIoT-based hydroponic system for crop recommendation and nutrient parameter monitoring. Smart Agricultural Technology, 8, 100472. https://doi.org/10.1016/j.atech.2024.100472
Rahman, M. H., Rahman, J., Tanchangya, T., & Esquivias, M. A. (2023). Green banking initiatives and sustainability: A comparative analysis between Bangladesh and India. Research in Globalization, 7, 100184. https://doi.org/10.1016/j.resglo.2023.100184
Sajid, M. (2026). Measuring perceived sustainable banking: Scale development and its role in customer loyalty and brand advocacy. Strategic Business Research, 2, 100041. https://doi.org/10.1016/j.sbr.2025.100041
Sardianou, E., Stauropoulou, A., Evangelinos, K., & Nikolaou, I. (2021). A materiality analysis framework to assess sustainable development goals of the banking sector through sustainability reports. Sustainable Production and Consumption, 27, 1775–1793. https://doi.org/10.1016/j.spc.2021.04.020
Sari, M. P., & Faisal, F. (2022). The diffusion of sustainability reporting for higher education institution worldwide. IOP Conference Series: Earth and Environmental Science, 1048(1), Article 012010. https://doi.org/10.1088/1755-1315/1048/1/012010
Shi, Y., Charles, V., & Zhu, J. (2025). Bank financial sustainability evaluation: Data envelopment analysis with random forest and Shapley additive explanations. European Journal of Operational Research, 321(3), 614–630. https://doi.org/10.1016/j.ejor.2024.09.030
Wang, H., et al. (2025). HealthAIoT: AIoT-driven smart healthcare system for sustainable cloud computing environments. Internet of Things, 31, 101555. https://doi.org/10.1016/j.iot.2025.101555
Xia, Y., et al. (2026). Leveraging generative AI and circular innovation for equitable and resilient supply chains. Technological Forecasting and Social Change, 225, 124556. https://doi.org/10.1016/j.techfore.2026.124556
Yaqoob, S., et al. (2026). AIoT for human emotion recognition: Potentials, challenges, and healthcare applications. Computer Science Review, 60, 100859. https://doi.org/10.1016/j.cosrev.2025.100859
Zhang, J. (2025). AI-based data intelligence system for sustainable ecological governance and smart environmental management. Microchemical Journal, 219, 115850. https://doi.org/10.1016/j.microc.2025.115850
Zhang, P., Chen, R. P., Dai, T., Wang, Z. T., & Wu, K. (2021). An AIoT-based system for real-time monitoring of tunnel construction. Tunnelling and Underground Space Technology, 109, 103766. https://doi.org/10.1016/j.tust.2020.103766
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Muhammad Syaukani, Fitria, Yeffriansjah Salim, Muhammad Amin Paris, Surya Eka Priyatna
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
