A Capgemini study reveals a dramatic increase in cloud adoption among financial firms, driven by the pandemic, yet challenges in AI and data management persist.
Financial firms across the globe are increasingly turning to cloud technologies, with a significant 54 percentage point rise in adoption over the past four years, according to a recent study by Capgemini. The report underscores the rapid shift within the financial sector towards embracing digital infrastructure, a change propelled by the COVID-19 pandemic which forced many businesses to re-evaluate their operational technologies and reliance on remote working solutions. As a result, 91% of the surveyed financial leaders—drawn from a group of 600 sector leaders and 120 executives—have integrated at least one cloud platform into their operations, a dramatic increase from the 37% reported back in 2020.
Despite this surge in cloud adoption, financial institutions, particularly banks, are grappling with significant challenges. Less than 40% of executives report high levels of satisfaction with the outcomes of their cloud implementations so far. One major hurdle identified is the sector’s struggle with adapting to advanced technologies such as artificial intelligence (AI), predictive analytics, and robotic process automation. Only a minority of organisations report any maturity in these areas, with just 15% in AI, 30% in predictive analytics, and 22% in automation.
In highly regulated industries like banking, there is a pressing need to conform to rigorous data protection and security standards, which has contributed to a delay in adopting AI technologies. The Capgemini report highlights significant concerns among industry executives over siloed legacy systems (noted by 71% of respondents), customer data protection (70%), and issues of data quality, which include inaccuracies and missing information (69%). Such challenges highlight the difficulties faced in establishing a robust data foundation necessary for the effective deployment of AI technologies.
Ravi Khokhar, Global Head of Cloud for Financial Services at Capgemini, pointed out the importance of these technologies, saying, “With generative AI now top of the boardroom agenda, a cloud-based technology foundation can also help the industry maximise investment in new technologies at scale.” This sentiment underscores the potential benefits for financial firms that can navigate these challenges effectively.
The report also categorises firms into ‘innovators’ and ‘non-innovators’, showing a stark contrast in performance. Innovators, comprising 31% of banks and insurers, exceed targets in areas such as cross-selling, upselling, and data monetisation, while only 10-12% of non-innovators achieve similar targets.
Looking ahead, financial firms are preparing for new regulatory frameworks such as Europe’s Digital Operational Resilience Act (DORA) and Section 1033 of the Dodd-Frank Act in the United States. Capgemini’s report suggests that these changes could offer an impetus for the financial sector to further embrace data-driven, cloud-focused strategies, aiming to enhance resilience and improve compliance in an increasingly digital landscape. The study provides a detailed snapshot of both the opportunities and ongoing challenges that financial firms face in transitioning to a more tech-centric approach.
Source: Noah Wire Services
- https://fintech.global/2024/03/09/financial-institutions-are-shifting-their-workload-to-the-cloud-in-2024 – This article supports the trend of financial institutions shifting their workloads to the cloud, highlighting the growing importance of cloud and edge computing in financial services.
- https://edgedelta.com/company/blog/how-many-companies-use-cloud-computing-in-2024 – This article provides statistics on the widespread adoption of cloud computing across various industries, including financial services, and the challenges associated with it.
- https://www.cloudzero.com/blog/cloud-computing-statistics/ – This article discusses the high adoption rates of cloud computing among organizations, including financial firms, and the challenges they face in managing cloud costs and adapting to advanced technologies.
- https://spacelift.io/blog/cloud-computing-statistics – This article highlights the rapid growth of the cloud computing market, the use of multiple cloud strategies, and the challenges in managing cloud spend, which are relevant to financial firms’ adoption of cloud technologies.
- https://www.auvik.com/franklyit/blog/cloud-migration-statistics/ – This article provides statistics on cloud migration and the adoption of hybrid and multiple public cloud strategies, which are pertinent to the challenges and opportunities faced by financial firms in cloud adoption.
- https://edgedelta.com/company/blog/how-many-companies-use-cloud-computing-in-2024 – This article mentions the importance of hybrid cloud architectures, which is relevant to the financial sector’s need for flexible and secure cloud solutions.
- https://www.cloudzero.com/blog/cloud-computing-statistics/ – This article discusses the plans of organizations to migrate more applications to the cloud, which aligns with the financial sector’s increasing adoption of cloud technologies.
- https://spacelift.io/blog/cloud-computing-statistics – This article highlights the challenges in achieving digital transformation without a robust hybrid cloud strategy, which is crucial for highly regulated industries like banking.
- https://fintech.global/2024/03/09/financial-institutions-are-shifting-their-workload-to-the-cloud-in-2024 – This article mentions the relevance of AI and next-generation software development in financial services, which is in line with the Capgemini report’s emphasis on these technologies.
- https://www.cloudzero.com/blog/cloud-computing-statistics/ – This article discusses the significant investments in cloud computing by SMEs and enterprises, which reflects the financial sector’s increasing investment in cloud technologies.
- https://spacelift.io/blog/cloud-migration-statistics – This article provides insights into the challenges of data quality and the need for a robust data foundation, which is critical for the effective deployment of AI technologies in financial firms.
