By monetizing artificial intelligence, the cloud is a strategic lever for banks and insurance companies


Banks and insurance companies now definitely entered the era cloudbut withoften limited adoption to secondary applications. Deploy the cloud though on a large scale is key to getting the most out of your investment in Artificial Intelligence. It reveals the first “Global Cloud Report – Financial Services”, created Capgemini Research Institute.

91% of global banking institutions and insurance companies have started their transformation journey to the cloud, with a significant increase compared to 2020, when only 37% of companies did so. However, more than 50% of the interviewed companies have moved only part of their core business applications to the cloud.

89% of financial industry executives believes the platform is cloud-enabled fundamental to guarantee agility, flexibility, productivity and the ability to innovatebut most companies are not yet cloud-ready and usually opt for a the “lift and move” approach, which makes it impossible to take full advantage of the cloud, including creating the foundation for monetization ofAccording to.

LCloud adoption is not just a technological changebut an effective catalyst to achieve new business goalswe read in a separate study, the second edition of Report “Cloud in Financial Services” by the author Answer.

A cloud for monetizing artificial intelligence in financial services

Capgemini’s report is based on global data and analysis from two major surveys, as well as more than 30 interviews with financial services executives, cloud and hyperscale technology providers, and input from Capgemini’s experts from multiple sources in 20 countries. The two investigations covered the financial services sector and the technology ecosystem. The report focused on four global regions and 14 markets within these regions: United States, Canada, United Kingdom, France, Germany, Spain, Netherlands, United Arab Emirates, Singapore, Hong Kong, Japan, China, India and Australia.

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Risk management and customer relations are among the top priorities for cloud migration. Furthermore, 62% interviewed financial companies started using artificial intelligence with the aim of being adopted along the entire value chain in the next two years. Despite its potential, AI, including technologies And generative and from machine learning, it is not yet widely accepted in the financial services sector and therefore its impact is limited.

The research found that so far most cloud investment has gone into modern, easy-to-use, AI-powered, customer-facing applications. However, less investment is being made in the underlying back-end systems, which provide input for consumer-facing front-end applications and consequently create a low-quality user experience.

Towards generative AI

According to Capgemini lMigrating internal core systems to cloud-enabled ecosystems and platforms is critical to fully harnessing the potential and effectiveness of AI and generative AI, which will translate into greater opportunities for the company’s growth in the coming years. Today, in banking and insurance, companies are testing Generative AI use cases for customer onboarding, credit analysis, financial planning, policy renewals and to support customer service models.

The report also highlights the central role of the cloud in the context of ESG, as it can provide essential tools for measuring ESG impact, as shown by the 51% of financial services firms reporting an improvement in transparency and reporting measures. Cloud service providers are also starting to develop solutions that can track and document the level of Scope 1, 2 and 3 emissions, offering a complete overview of a company’s carbon footprint.

“For a financial services organization, giving up the cloud is no longer an option. Moving to the cloud requires an approach that goes beyond cost savings and focuses on innovation as a tool for competitive advantage,” he stated Dario Patrizi, Director of Financial Services of Capgemini in Italy. “Companies rushing to implement generative artificial intelligence today must be aware that the future benefits of artificial intelligence will not be possible without cloud-enabled systems. Only through defining and creating effective large-scale cloud-based operating model in fact, it will be possible to fully exploit the transformative potential of these new technologies.”

Cloud implementation challenges in finance

Despite the benefits, executives interviewed by Capgemini express concern about the challenges associated with migrating to the cloud. Two thirds (68%) they actually consider it a problem data security as an obstacle to the adoption of cloud solutions, doc 51% indicates high cwork and transformation places. Further 45% lists them regulations, for example those on data sovereignty, as another potentially problematic factor.

Recently, the Digital Operational Resilience Act (Dora) required financial institutions subject to European Union regulations to rigorously implement, document and secure the systems, protocols and tools necessary to ensure sufficient levels of reliability, capacity and resilience. sovereign cloud, which provides countries with a secure and independent cloud computing infrastructure to help ensure data privacy and sovereignty, is therefore fast becoming a mainstream option. In response to this concern, 39% of executives said they preferred public cloud, 49% preferred private cloud, and 12% preferred hybrid cloud.

Focus on compliance and data sovereignty

Also the second edition of the report “Cloud in financial services” according to Answersemphasizes persistence challenges related to regulatory compliance and data sovereignty nin the context of cloud adoption in the financial sector. The report, produced in collaboration with the European Banking Federation, Insurance Europe and professors from Imperial College Business School and the University of California, Santa Barbara, reveals that for 81% of respondents see compliance and privacy aspects as the biggest challenges (compared to 73% in 2021). It is significant that 34% of respondents cite these issues as the main challenge to overcome when adopting cloud solutions in their financial institutions.

The study is based on the analysis of more 1200 projects in the cloud created Reply and further interviews with companies from the sector, plus the results of a pan-European survey conducted between December 2022 and March 2023 by professors at Imperial College Business School in London.

Banks remain cautious about machine learning

The research reveals, in particular, one a different view of machine learningdespite the general enthusiasm. 27% confirm that they do not use machine learning capabilitieswhile 34% and 16% report limited and moderate use, respectively. Only 10% indicate significant adoption and only 5% extensively integrate machine learning capabilities. This data offers a meaningful comparison between planned and actual implementation of cloud-enhanced machine learning.

Nelson Phillips, professor of technology management at the University of California, Santa Barbara, points out, “The report shows that while cloud adoption has become ‘business as usual’ in financial services, The benefits of moving tasks to the cloud vary significantly depending on the approach which companies adopt for implementation and readiness to do so look beyond cost savings.”

Freddy Gielen, managing partner at Reply, reiterates, “The report and survey show that the primary impact of cloud implementation on a financial institution’s profitability is more likely to be driven by increased revenue than simply reduced costs.”

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