Cloud

Cloud is a natural fit for the financial services industry, and the benefits – cost, flexibility, speed and the ability to scale on demand – are compelling. The new “rules” for using cloud are starting to take shape.

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How you can use the RetailTech Model

The first stage is Research & Development, when an innovation is not fully-fledged and has not yet been adopted beyond prototypes, trials or POCs.

New technologies typically go through 5+ years of R&D, though the timeframe will vary substantially depending on the degree of innovation entailed.

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Model Stages

The Leading Edge stage indicates when an innovation has moved out of R&D and into operation. Approximately 5% of the market adopts the innovation at this stage, usually start-ups and a few industry players known for being forward-looking.

Sometimes, an innovation is picked up from another sector. As indicated in the timeline below, it typically takes 1 to 3 years to move from the Leading Edge to Early Adopters stage.

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Model Timeline

At this stage organisations are more risk averse than those at the Leading Edge, but are still keen to be in the industry’s upper quartile and adopt a new technology.

The broad timeline for technologies to remain at this stage is 2 to 5 years at which point they will have reached around 25% market adoption.

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Model Origins

By this point a technology or business innovation can be considered as Mainstream since it will have been implemented by around 50% of the market.

2-5 years is the typical timeframe for this stage.

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Model Lenses

Technologies in the Late Adopters stage have been widely adopted across the industry with 80% - 100% of the market using them after a further 5+ years.

Not all technologies end up being adopted by everyone, with some 20% of technologies never reaching full adoption.

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R&D

The first stage is Research & Development, when an innovation is not fully-fledged and has not yet been adopted beyond prototypes, trials or POCs.

New technologies typically go through 5+ years of R&D, though the timeframe will vary substantially depending on the degree of innovation entailed.

. .
5+
Leading Edge

The Leading Edge stage indicates when an innovation has moved out of R&D and into operation. Approximately 5% of the market adopts the innovation at this stage, usually start-ups and a few industry players known for being forward-looking.

Sometimes, an innovation is picked up from another sector. As indicated in the timeline below, it typically takes 1 to 3 years to move from the Leading Edge to Early Adopters stage.

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5%
1-3
Early Adopters

At this stage organisations are more risk averse than those at the Leading Edge, but are still keen to be in the industry’s upper quartile and adopt a new technology.

The broad timeline for technologies to remain at this stage is 2 to 5 years at which point they will have reached around 25% market adoption.

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25%
2-5
Mainstream

By this point a technology or business innovation can be considered as Mainstream since it will have been implemented by around 50% of the market.

2-5 years is the typical timeframe for this stage.

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50%
2-5
Late Adopters

Technologies in the Late Adopters stage have been widely adopted across the industry with 80% - 100% of the market using them after a further 5+ years.

Not all technologies end up being adopted by everyone, with some 20% of technologies never reaching full adoption.

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80%-100%
5+

The first stage is Research & Development, when an innovation is not fully-fledged and has not yet been adopted beyond prototypes, trials or POCs.

New technologies typically go through 5+ years of R&D, though the timeframe will vary substantially depending on the degree of innovation entailed.

The Leading Edge stage indicates when an innovation has moved out of R&D and into operation. Approximately 5% of the market adopts the innovation at this stage, usually start-ups and a few industry players known for being forward-looking.

Sometimes, an innovation is picked up from another sector. As indicated in the timeline below, it typically takes 1 to 3 years to move from the Leading Edge to Early Adopters stage.

At this stage organisations are more risk averse than those at the Leading Edge, but are still keen to be in the industry’s upper quartile and adopt a new technology.

The broad timeline for technologies to remain at this stage is 2 to 5 years at which point they will have reached around 25% market adoption.

By this point a technology or business innovation can be considered as Mainstream since it will have been implemented by around 50% of the market.

2-5 years is the typical timeframe for this stage.

Technologies in the Late Adopters stage have been widely adopted across the industry with 80% - 100% of the market using them after a further 5+ years.

Not all technologies end up being adopted by everyone, with some 20% of technologies never reaching full adoption.

One small step to cloud, one giant leap in performance and efficiency

The financial services industry was slow to adopt cloud computing until around the middle of 2015. Now, adoption is widespread, and a single paradigm – hybrid infrastructure – has become the favored approach. A number of factors has come together to drive this rapid shift: cost pressures; maturity of public and private cloud offerings, especially with security; and greater acceptance by regulators.

Public cloud solutions have moved outside the development shop. Forward-thinking banks are adopting IaaS and PaaS for mission-critical production systems. Virtual private cloud and managed private cloud solutions have been implemented for core banking systems, even at global scale. At the same time, SaaS solutions for core banking systems are emerging with clear benefits in cost, flexibility and speed of deployment.

Orchestration of hybrid cloud and traditional infrastructure is fast becoming indispensable. Organizations are looking to manage these complex environments with a single, automated service-delivery model. The next wave of innovation will be dynamic sourcing of computing power from external and internal sources, based on cost and availability of capacity. Likewise, the next generation of automation and orchestration will be a step beyond today’s software defined infrastructure to the automated management of the entire data center from the application layer via an API set.

API management will be extended beyond the boundaries of the organization to harness the new business models of the API economy. This will add further layers of complexity in security (Know Your API); in performance management (SLA monitoring across internal and external APIs); and in resilience (throttling of API calls).

The development community is pushing ahead in using containers that make it easier to test and deploy software and allow large teams to work in parallel on different elements of a system. Containers also facilitate the exploitation of APIs and microservices, which will be essential in a post-Payment Services Directive PSD2 world. Effective adoption of open APIs will depend on an organization’s ability to manage banking services across a fragmented infrastructure, with internal and external APIs being brought together in real-time to provide a seamless service to banking customers.

In addition to these technical shifts, there has been a swing of the pendulum when it comes to sourcing. For the last 10 to 15 years, organizations have been moving away from sole-source arrangements toward multi-sourcing. Now, they're shifting in the other direction. Many banks see a sole-sourced model as the only viable way to achieve change at scale and speed. While multi-sourcing was designed to optimize cost, banks now want to optimize speed and depth of transformation. Automation of hybrid cloud management also calls for new skills and technology that in-house teams may lack.

Looking over the horizon, the next wave of infrastructure innovation will likely come from highly distributed environments, such as Internet of Things and distributed mesh networks that move storage and processing to the edge. Making it possible are new computer architectures, such as neuromorphic and quantum computing, that enable a dramatic leap in performance and efficiency.

Explore these and other trends in the Cloud Technology lens of our Innovation Model.

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Cloud Expert

Andrew Dare
Technology Innovation Lead

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