Efficient Large-Scale Data based on Cloud Framework using Critical Influences on Financial Landscape
The financial industry has also been profoundly affected by the introduction of cloud computing. This research study delves into the effects of cloud computing on the financial sector, specifically looking at the pros, cons, and consequences for banks and other financial organisations. Starting with an introduction to the concept, the article goes on to describe cloud computing and its key features, including self-service capabilities, quick flexibility, measurable service, resource pooling, and widespread network access. After that, it explores the ways cloud computing has been used in the financial sector, specifically IaaS, PaaS, and SaaS. We take a look at the ways cloud computing can increase accessibility, cooperation, scalability, and cost reduction in the financial sector. In addition, the study delves into the difficulties linked to financial industry cloud adoption. Among the main topics covered are privacy and security worries, compliance with regulations, data sovereignty, vendor lock-in, and the difficulties of integration. The article delves into methods and recommendations for reducing the impact of these threats, including as encryption, authentication procedures, compliance frameworks, and hybrid cloud architectures. Additionally, the effects of cloud computing on innovation, customer experience, data analytics, risk management, and financial operations are examined. In addition to discussing how professionals' skill sets will need to adapt to a cloud-enabled world, the study delves into how financial institutions' roles will change over time. In its last section, the article reviews the results and stresses how cloud computing could revolutionise the financial sector. It stresses the importance of banks and other financial institutions thoroughly weighing the pros and cons of cloud adoption, creating strong security measures, and adjusting their business strategies to take full advantage of cloud computing.
Authors
- Rahul Vadisetty
Institutions
- Wayne State University (US)
Publication Details
- Published
- 2024-11-23
- DOI
- https://doi.org/10.1109/icec59683.2024.10837096
- Citations
- 10
- Primary Topic
- Stock Market Forecasting Methods
- Type
- article
- Field-Weighted Citation Impact
- 4.90