Integration of Big Data Technology in Risk Management Strategies in the Banking Sector: A Systematic Literature Review
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This research explores the integration of Big Data technologies in risk management strategies within the banking sector through a systematic literature review. The study identifies the key methods and frameworks that enhance the ability of financial institutions to predict and mitigate risks more effectively. By leveraging predictive analytics, particularly with Machine Learning (ML) and Internet of Things (IoT) data, banks can anticipate potential risks with greater precision, improving decision-making speed and accuracy. The review highlights the significant benefits of Big Data, including reductions in financial losses, enhanced risk prediction accuracy, and improved operational efficiency. Case studies demonstrate how these technologies have contributed to more resilient and proactive risk management practices. However, challenges related to data privacy, cybersecurity, and infrastructure costs persist. This research provides insights into the transformative impact of Big Data on risk management in banking, while also suggesting directions for future research to overcome existing barriers and optimize integration. The findings underscore the importance of a strategic approach to Big Data implementation, which could lead to more robust risk management systems and greater financial stability in the banking sector.
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1. Agarwal, A. (2021). Challenges and opportunities in the adoption of Big Data analytics in banking. Journal of Financial Technology, 18((2)), 123–137. https://doi.org/10.1039/jft202123
2. Ali, Q., Yaacob, H., Parveen, S., & Zaini, Z. (2021). Big data and predictive analytics to optimise social and environmental performance of Islamic banks. Environment Systems and Decisions. https://doi.org/10.1007/s10669-021-09823-1
3. Augusta Heavens Ikevuje, David Chinalu Anaba, & Uche Thankgod Iheanyichukwu. (2024). Optimizing supply chain operations using IoT devices and data analytics for improved efficiency. Magna Scientia Advanced Research and Reviews, 11(2), 070–079. https://doi.org/10.30574/msarr.2024.11.2.0107
4. Big data at work: dispelling the myths, uncovering the opportunities. (2014). Choice Reviews Online. https://doi.org/10.5860/choice.51-6260
5. Blundell-Wignall, A., Atkinson, P., & Roulet, C. (2014). Bank business models and the Basel system: complexity and interconnectedness. OECD Journal: Financial Market Trends 2014.
6. Brock, T., & Lee, M. (2022). Enhancing Risk Mitigation Systems in Banks Through Big Data Integration: Evidence from European Banks. International Journal of Financial Studies, 10((2)), 2–145. https://doi.org/https://doi.org/10.3390/ijfs10020132
7. Brown, W., Wilson, G., & Johnson, O. (2024). Understanding the Role of Big Data Analytics in Enhancing CustomerExperience. https://doi.org/10.20944/preprints202408.0365.v1
8. Cantarelli, C. C., Flybjerg, B., Molin, E. J. E., & Wee, B. van. (2018). Cost Overruns in Large-Scale Transport Infrastructure Projects. Automation in Construction.
9. Chang, V., Valverde, R., Ramachandran, M., & Li, C. S. (2020). Toward business integrity modeling and analysis framework for risk measurement and analysis. Applied Sciences (Switzerland). https://doi.org/10.3390/app10093145
10. Choudhury, M., & Agarwal, A. (2021). Big Data in the Banking Sector: The Role of Skills and Training. International Journal of Banking Technology, 9((2)), 45–63. https://scholar.google.com/scholar?cluster=14608452803739523288&hl=en
11. COMPAGNONE, M. (2020). DART: A Data Analytics Readiness Assessment Tool for Use in Occupational Safety. Orphanet Journal of Rare Diseases.
12. Dicuonzo, G., Galeone, G., Zappimbulso, E., & Dell’Atti, V. (2019). Risk Management 4.0: The Role Of Big Data Analytics In The Bank Sector. International Journal of Economics and Financial Issues. https://doi.org/10.32479/ijefi.8556
13. Gudala, L., Venkataramanan, S., Kumar, A., & Sadhu, R. (2019). Distributed Learning and Broad Applications in Scientific Research Leveraging Artificial Intelligence for Enhanced Threat Detection, Response, and Anomaly Identification in Resource-Constrained IoT Networks. Distributed Learning and Broad Applications in Scientific Research Annual, 5, 23–54.
14. Haldibekova, A. (2022). Penerapan & Implementasi Big Data di Berbagai Sektor (Pembangunan Berkelanjutan Era Industri 4.0 dan Society 5.0). In Ilmu Pengetahuan dan Potensi Keilmuan: Landasan Pembangunan Masyarakat yang Inovatif Berkelanjutan.
15. Hernawati, E., Hadi, A. R. A., Aspiranti, T., & Rehan, R. (2021). Non-Performing Financing among Islamic Banks in Asia-Pacific Region. Cuadernos de Economia. https://doi.org/10.32826/cude.v1i126.501
16. Jameaba, M. S. (2020). Digitization Revolution, FinTech Disruption, and Financial stability: Using the Case of Indonesian Banking Ecosystem to highlight wide-ranging digitization opportunities and major challenges. SSRN.
17. Kasiewicz, S. (2017). New trends in the system regulating the market of bank services. Kwartalnik Nauk o Przedsiębiorstwie. https://doi.org/10.5604/01.3001.0010.7450
18. Ke, B., & Wel, C. A. C. (2024). Elevating Customer Relationship Management in Chinese Banking: A Synergy of Information Technology and Strategic Practices. Journal of Information Systems Engineering and Management, 9(2). https://doi.org/10.55267/iadt.07.14676
19. Khanna, P., Singh, A., & Gupta, S. (2022). Big Data adoption in risk management within banks: A case study analysis. Journal of Banking & Finance, 45((1)), 88–101. https://doi.org/https://doi.org/10.1016/j.jbf2022.05.008
20. Lacković, I. D., Kovšca, V., & Vincek, Z. L. (2020). A review of selected aspects of big data usage in banks’ risk management. In Journal of Information and Organizational Sciences. https://doi.org/10.31341/jios.44.2.7
21. Li, T., Xie, N., Zeng, C., Zhou, W., Zheng, L., Jiang, Y., Yang, Y., Ha, H. Y., Xue, W., Huang, Y., Chen, S. C., Navlakha, J., & Iyengar, S. S. (2017). Data-driven techniques in disaster information management. ACM Computing Surveys. https://doi.org/10.1145/3017678
22. Li, Y. (2019). Research on financial risk prediction and prevention countermeasures based on big data. Proceedings - 2019 11th International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2019. https://doi.org/10.1109/ICMTMA.2019.00130
23. Ma, S., Wang, H., Xu, B., Xiao, H., Xie, F., Dai, H. N., Tao, R., Yi, R., & Wang, T. (2018). Banking comprehensive risk management system based on big data architecture of hybrid processing engines and databases. Proceedings - 2018 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018. https://doi.org/10.1109/SmartWorld.2018.00310
24. Maroufkhani, P., Tseng, M. L., Iranmanesh, M., Ismail, W. K. W., & Khalid, H. (2020). Big data analytics adoption: Determinants and performances among small to medium-sized enterprises. International Journal of Information Management. https://doi.org/10.1016/j.ijinfomgt.2020.102190
25. Mashrur, A., Luo, W., Zaidi, N. A., & Robles-Kelly, A. (2020). Machine learning for financial risk management: A survey. In IEEE Access. https://doi.org/10.1109/ACCESS.2020.3036322
26. Minssen, T., Seitz, C., Aboy, M., & Corrales Compagnucci, M. (2020). The EU-US Privacy Shield Regime for Cross-Border Transfers of Personal Data under the GDPR. European Pharmaceutical Law Review. https://doi.org/10.21552/eplr/2020/1/6
27. Naveenan, R. V., & Suresh, G. (2023). Cyber Risk and the Cost of Unpreparedness of Financial Institutions. In Cyber Security and Business Intelligence: Innovations and Machine Learning for Cyber Risk Management. https://doi.org/10.4324/9781003285854-2
28. Noriega, J. P., Rivera, L. A., & Herrera, J. A. (2023). Machine Learning for Credit Risk Prediction: A Systematic Literature Review. Data. https://doi.org/10.3390/data8110169
29. Nuryati, T., Malik, A. F., Ernawati, F. A., & ... (2023). Increase Bussines Profits by Utilizing Bussiness Inteligence Functions. Journal Economi …, 4(5), 901–910. https://dinastirev.org/JEMSI/article/view/1513%0Ahttps://dinastirev.org/JEMSI/article/download/1513/940
30. Ozminkowski, R. J., Wells, T. S., Hawkins, K., Bhattarai, G. R., Martel, C. W., & Yeh, C. S. (2015). Big Data, Little Data, and Care Coordination for Medicare Beneficiaries with Medigap Coverage. Big Data. https://doi.org/10.1089/big.2014.0034
31. Putra, I., Sulistiyo, U., Diah, E., Rahayu, S., & Hidayat, S. (2022). The Influence Of Internal Audit, Risk Management, Whistleblowing System And Big Data Analytics On The Financial Crime Behavior Prevention. Cogent Economics and Finance. https://doi.org/10.1080/23322039.2022.2148363
32. Qian, X., & Liu, L. (2020). Management and Optimization of Enterprise Financial Risk under the Background of Big Data. https://doi.org/10.2991/assehr.k.201030.049
33. Richard, J., & Mccann, E. (2023). An extensible framework for the deployment and management of computer vision workloads on edge platforms.
34. Rofi’i, Y. U. (2023). Financial Risk Management in Indonesian Banking: The Integrative Role of Data Analytics and Predictive Algorithms. International Journal Software Engineering and Computer Science (IJSECS). https://doi.org/10.35870/ijsecs.v3i3.1823
35. Samuel Onimisi Dawodu, Adedolapo Omotosho, Odunayo Josephine Akindote, Abimbola Oluwatoyin Adegbite, & Sarah Kuzankah Ewuga. (2023). Cybersecurity Risk Assessment In Banking: Methodologies And Best Practices. Computer Science & IT Research Journal. https://doi.org/10.51594/csitrj.v4i3.659
36. Sari, P. R., Nugroho, R., & Hadi, S. (2020). Security and Privacy Issues in the Adoption of Big Data in Banking. Journal of Financial Technology, 12((3)), 87–101. https://doi.org/https://scholar.google.com/scholar?cluster=14612323234557869033&hl=en
37. Shamim, S., Zeng, J., Shariq, S. M., & Khan, Z. (2019). Role of big data management in enhancing big data decision-making capability and quality among Chinese firms: A dynamic capabilities view. Information and Management. https://doi.org/10.1016/j.im.2018.12.003
38. Sharma, P., & Barua, S. (2023). From Data Breach to Data Shield: The Crucial Role of Big Data Analytics in Modern Cybersecurity Strategies. International Journal of Information and Cybersecurity.
39. Shinta Dewi, F., & Dewayanto, T. (2024). Peran Big Data Analytics, Machine Learning, Dan Artificial Intelligence Dalam Pendeteksian Financial Fraud: a Systematic Literature Review. Diponegoro Journal of Accounting, 13(3), 1–15. http://ejournal-s1.undip.ac.id/index.php/accounting
40. Singh, N. (2022). Developing Business Risk Resilience through Risk Management Infrastructure: The Moderating Role of Big Data Analytics. Information Systems Management. https://doi.org/10.1080/10580530.2020.1833386
41. States, U. (2022). Optimizing Lending Risk Analysis & Management with Machine Learning , Big Data , and Cloud Computing. 6588(September), 172–184.
42. Wang, Y., Xu, L., & Li, J. (2019). Infrastructure Challenges in Implementing Big Data for Banking Institutions. Journal of Information Technology in Finance, 8((4)), 112–128. https://doi.org/https://scholar.google.com/scholar?cluster=14200973978596315783&hl=en
43. Wilhelmina Afua Addy, Chinonye Esther Ugochukwu, Adedoyin Tolulope Oyewole, Onyeka Chrisanctus Ofodile, Omotayo Bukola Adeoye, & Chinwe Chinazo Okoye. (2024). Predictive analytics in credit risk management for banks: A comprehensive review. GSC Advanced Research and Reviews. https://doi.org/10.30574/gscarr.2024.18.2.0077
44. Wirawan, P. (2023). Leveraging Predictive Analytics in Financing Decision-Making for Comparative Analysis and Optimization. Advances in Management & Financial Reporting, 1(3), 157–169. https://doi.org/10.60079/amfr.v1i3.209
45. Xiaoli, W., & Nong, N. B. (2021). Evaluating Big Data Strategies for Risk Management in Financial Institutions. Journal of Computational Social Dynamics, 34–45. https://vectoral.org/index.php/JCSD/article/view/44%0Ahttps://vectoral.org/index.php/JCSD/article/download/44/44
46. Zhou, H., Sun, G., Fu, S., Liu, J., Zhou, X., & Zhou, J. (2019). A big data mining approach of PSO-Based BP neural network for financial risk management with IoT. IEEE Access. https://doi.org/10.1109/ACCESS.2019.2948949
47. Zio, E. (2018). The future of risk assessment. Reliability Engineering and System Safety. https://doi.org/10.1016/j.ress.2018.04.020
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