Strategic Liquidity Risk Management in Global Banking: Insights and Challenges

Padmini Rajendra Bulani

Institute of Chartered Accountants of India

bulanipadmini@gmail.com

Kratika Jain

Teerthanker Mahaveer University

Delhi Road, NH9, Moradabad

Uttar Pradesh 244001 India

jainkratika.567@gmail.com

Abstract – Liquidity risk management is a cornerstone of stability in the global banking industry, underpinning the capacity of financial institutions to meet short-term obligations while ensuring long-term operational sustainability. This study examines the strategic dimensions of liquidity risk management within the framework of global banking, exploring both the systemic challenges and innovative approaches to mitigation. Key insights reveal that evolving market dynamics, stringent regulatory requirements, and technological advancements are reshaping traditional liquidity strategies. Challenges such as cross-border capital flows, geopolitical uncertainties, and the integration of decentralized financial technologies further compound the complexity of liquidity risk management. This paper underscores the importance of adaptive strategies, robust risk assessment frameworks, and dynamic stress-testing models to enhance resilience in the face of liquidity shocks. It also emphasizes the role of governance and global coordination in addressing interconnected financial risks, ultimately contributing to the stability and sustainability of the international banking system.

Keywords – Liquidity risk management, global banking, financial stability, regulatory compliance, cross-border capital flows, stress-testing models, decentralized finance, systemic risks, adaptive strategies, governance, financial resilience.

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• Hrishikesh Rajesh Mane, Vanitha Sivasankaran Balasubramaniam, Ravi Kiran Pagidi, Dr. S P Singh, Prof. (Dr.) Sandeep Kumar, Shalu Jain. “Optimizing User and Developer Experiences with Nx Monorepo Structures.” Iconic Research And Engineering Journals Volume 7 Issue 3:572-595. 
• Sanyasi Sarat Satya Sukumar Bisetty, Rakesh Jena, Rajas Paresh Kshirsagar, Om Goel, Prof. (Dr.) Arpit Jain, Prof. (Dr.) Punit Goel. “Developing Business Rule Engines for Customized ERP Workflows.” Iconic Research And Engineering Journals Volume 7 Issue 3:596-619. 
• Arnab Kar, Vanitha Sivasankaran Balasubramaniam, Phanindra Kumar, Niharika Singh, Prof. (Dr.) Punit Goel, Om Goel. “Machine Learning Models for Cybersecurity: Techniques for Monitoring and Mitigating Threats.” Iconic Research And Engineering Journals Volume 7 Issue 3:620-634. 
• Kyadasu, Rajkumar, Sandhyarani Ganipaneni, Sivaprasad Nadukuru, Om Goel, Niharika Singh, Prof. (Dr.) Arpit Jain. 2023. Leveraging Kubernetes for Scalable Data Processing and Automation in Cloud DevOps. Iconic Research And Engineering Journals Volume 7, Issue 3, Pages 546-571. 
• Antony Satya Vivek Vardhan Akisetty, Ashish Kumar, Murali Mohana Krishna Dandu, Prof. (Dr) Punit Goel, Prof. (Dr.) Arpit Jain; Er. Aman Shrivastav. 2023. “Automating ETL Workflows with CI/CD Pipelines for Machine Learning Applications.” Iconic Research And Engineering Journals Volume 7, Issue 3, Page 478-497. 
• Gaikwad, Akshay, Fnu Antara, Krishna Gangu, Raghav Agarwal, Shalu Jain, and Prof. Dr. Sangeet Vashishtha. “Innovative Approaches to Failure Root Cause Analysis Using AI-Based Techniques.” International Journal of Progressive Research in Engineering Management and Science (IJPREMS) 3(12):561–592. doi: 10.58257/IJPREMS32377. 
• Gaikwad, Akshay, Srikanthudu Avancha, Vijay Bhasker Reddy Bhimanapati, Om Goel, Niharika Singh, and Raghav Agarwal. “Predictive Maintenance Strategies for Prolonging Lifespan of Electromechanical Components.” International Journal of Computer Science and Engineering (IJCSE) 12(2):323–372. ISSN (P): 2278–9960; ISSN (E): 2278–9979. © IASET. 
• Gaikwad, Akshay, Rohan Viswanatha Prasad, Arth Dave, Rahul Arulkumaran, Om Goel, Dr. Lalit Kumar, and Prof. Dr. Arpit Jain. “Integrating Secure Authentication Across Distributed Systems.” Iconic Research And Engineering Journals Volume 7 Issue 3 2023 Page 498-516. 
• Vaidheyar Raman Balasubramanian, Nagender Yadav, Er. Aman Shrivastav. (2024). Streamlining Data Migration Processes with SAP Data Services and SLT for Global Enterprises. Iconic Research And Engineering Journals, 8(5), 842–873. 
• Jayaraman, S., & Borada, D. (2024). Efficient Data Sharding Techniques for High-Scalability Applications. Integrated Journal for Research in Arts and Humanities, 4(6), 323–351. https://doi.org/10.55544/ijrah.4.6.25. 
• Srinivasan Jayaraman, CA (Dr.) Shubha Goel. (2024). Enhancing Cloud Data Platforms with Write-Through Cache Designs. International Journal of Research Radicals in Multidisciplinary Fields, 3(2), 554–582. Retrieved from https://www.researchradicals.com/index.php/rr/article/view/146. 
• Sreeprasad Govindankutty, Ajay Shriram Kushwaha. (2024). The Role of AI in Detecting Malicious Activities on Social Media Platforms. International Journal of Multidisciplinary Innovation and Research Methodology, 3(4), 24–48. Retrieved from https://ijmirm.com/index.php/ijmirm/article/view/154. 
• Srinivasan Jayaraman, S., and Reeta Mishra. (2024). Implementing Command Query Responsibility Segregation (CQRS) in Large-Scale Systems. International Journal of Research in Modern Engineering and Emerging Technology (IJRMEET), 12(12), 49. Retrieved December 2024 from http://www.ijrmeet.org. 
• Jayaraman, S., & Saxena, D. N. (2024). Optimizing Performance in AWS-Based Cloud Services through Concurrency Management. Journal of Quantum Science and Technology (JQST), 1(4), Nov(443–471). Retrieved from https://jqst.org/index.php/j/article/view/133. 
• Abhijeet Bhardwaj, Jay Bhatt, Nagender Yadav, Om Goel, Dr. S P Singh, Aman Shrivastav. Integrating SAP BPC with BI Solutions for Streamlined Corporate Financial Planning. Iconic Research And Engineering Journals, Volume 8, Issue 4, 2024, Pages 583-606. 
• Pradeep Jeyachandran, Narrain Prithvi Dharuman, Suraj Dharmapuram, Dr. Sanjouli Kaushik, Prof. (Dr.) Sangeet Vashishtha, Raghav Agarwal. Developing Bias Assessment Frameworks for Fairness in Machine Learning Models. Iconic Research And Engineering Journals, Volume 8, Issue 4, 2024, Pages 607-640. 
• Bhatt, Jay, Narrain Prithvi Dharuman, Suraj Dharmapuram, Sanjouli Kaushik, Sangeet Vashishtha, and Raghav Agarwal. (2024). Enhancing Laboratory Efficiency: Implementing Custom Image Analysis Tools for Streamlined Pathology Workflows. Integrated Journal for Research in Arts and Humanities, 4(6), 95–121. https://doi.org/10.55544/ijrah.4.6.11
• Jeyachandran, Pradeep, Antony Satya Vivek Vardhan Akisetty, Prakash Subramani, Om Goel, S. P. Singh, and Aman Shrivastav. (2024). Leveraging Machine Learning for Real-Time Fraud Detection in Digital Payments. Integrated Journal for Research in Arts and Humanities, 4(6), 70–94. https://doi.org/10.55544/ijrah.4.6.10
• Pradeep Jeyachandran, Abhijeet Bhardwaj, Jay Bhatt, Om Goel, Prof. (Dr.) Punit Goel, Prof. (Dr.) Arpit Jain. (2024). Reducing Customer Reject Rates through Policy Optimization in Fraud Prevention. International Journal of Research Radicals in Multidisciplinary Fields, 3(2), 386–410. https://www.researchradicals.com/index.php/rr/article/view/135
• Pradeep Jeyachandran, Sneha Aravind, Mahaveer Siddagoni Bikshapathi, Prof. (Dr.) MSR Prasad, Shalu Jain, Prof. (Dr.) Punit Goel. (2024). Implementing AI-Driven Strategies for First- and Third-Party Fraud Mitigation. International Journal of Multidisciplinary Innovation and Research Methodology, 3(3), 447–475. https://ijmirm.com/index.php/ijmirm/article/view/146
• Jeyachandran, Pradeep, Rohan Viswanatha Prasad, Rajkumar Kyadasu, Om Goel, Arpit Jain, and Sangeet Vashishtha. (2024). A Comparative Analysis of Fraud Prevention Techniques in E-Commerce Platforms. International Journal of Research in Modern Engineering and Emerging Technology (IJRMEET), 12(11), 20. http://www.ijrmeet.org
• Jeyachandran, P., Bhat, S. R., Mane, H. R., Pandey, D. P., Singh, D. S. P., & Goel, P. (2024). Balancing Fraud Risk Management with Customer Experience in Financial Services. Journal of Quantum Science and Technology (JQST), 1(4), Nov(345–369). https://jqst.org/index.php/j/article/view/125
• Jeyachandran, P., Abdul, R., Satya, S. S., Singh, N., Goel, O., & Chhapola, K. (2024). Automated Chargeback Management: Increasing Win Rates with Machine Learning. Stallion Journal for Multidisciplinary Associated Research Studies, 3(6), 65–91. https://doi.org/10.55544/sjmars.3.6.4