Financial services firms are ramping up efforts to move away from traditional mainframe systems in favor of cloud services, according to new research from NTT Data.
In a study from the firm, 91% of respondents reported board level support for a shift to the cloud, with 87% highlighting increasing pressure to integrate AI technologies within their respective firms.
Why such a prominent shift in thinking is taking place can be attributed to a variety of factors, the most significant having its roots in the current generative AI boom.
Those surveyed described generative AI as being a key motivating factor in accelerating their shift to the cloud. Nearly two-thirds (63%) said that the emergence of the technology was “decisively facilitating” in their efforts to migrate workloads and applications to the cloud.
Another 33% see generative AI as a potential aid to data migration complexities, while 29% look to the new technology to help mitigate against risk factors.
Nearly half (45%) of respondents noted they were already integrating AI into their technology stacks, while a further 30% were in the early stages of adoption.
Cost was also a leading contributing factor in the decision to shift away from mainframes, respondents told NTT Data. Around 17% cited “cost reduction” as a key motivator in the shift to the cloud.
The flexibility and scalability of the cloud took greater precedence than cost, though, described by 36% of respondents as the key drivers towards migration.
The shift away from mainframes has been a long-running process
As NTT’s data shows, this movement towards the cloud has been in full force for some time and shows no signs of slowing.
94% of banks now currently use public cloud systems, with 48% opting for a multi-cloud approach and 32% focusing on hybrid cloud systems.
Enrique Ávila, IT transformation director at Banco Sabadell, said that while the mainframe is expected to remain in the foreseeable future, current industry trends are prompting a widespread rethink among financial services IT leaders, many of whom are eager to reap the benefits of technologies such as generative AI.
“While the mainframe and its associated applications are expected to remain relevant in the foreseeable future, it is undeniable that the advent of generative AI will have a profound impact on the delivery of technology services,” he said.
“This will enable the deployment of viable methods to modernize existing technology landscapes, facilitating the transformation and evolution towards more modular, cloud based components throughout the software value chain,” he added.
The banking sector will have its fair share of challenges to overcome
Though the industry is enthusiastic about the advantages of the cloud, significant hurdles still remain to achieve digital transformation success, the report warned.
Despite 89% of banking leaders describing themselves as innovators, for example, 63% still operate on the outdated mainframe system.
Not “a single respondent” out of the 650 decision-makers surveyed said that “all suitable applications” had been moved off the mainframe,” according to NTT.
A further 78% also described moving away from mainframe systems as “challenging.”
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To mitigate against the challenge, banks and financial service firms have been looking externally; the report found that 88% of banks had turned to “technology partners” to help in their cloud migration journeys.
Skills shortages are also a recurring challenge faced by IT leaders in the industry, the report added. NTT specifically highlighted a marked decline in the availability of seasoned mainframe experts has become apparent.
This created an environment in which banks have to ensure both the “continuous operation of their existing mainframe systems” while at the same time looking “to keep pace with the rapidly changing digital landscape.”
The result is a worrying lack of systematic training and skills in new technologies.
80% of those surveyed reported a lack of a strategic framework for generative AI adoption, for example, clearly expressing the need for a program of upskilling and training.
