If data is the lifeblood of an AI solution, technology is the heart that keeps the blood pumping.
The science behind AI and ML algorithms hasn’t changed dramatically in the last 30 years – it is the advent of cheap, scalable computing power hosted in the Cloud that is driving the conversation around AI today.
Banks, therefore, need to embrace Cloud technology and set the business up in the right way to use Cloud computing as effectively as possible.
A benefit of Cloud technology is that the largest platforms – Amazon Web Services, Google Cloud and Microsoft Azure – offer access to a range of open-source AI technologies as part of their service.
Many banks have embarked on the journey towards Cloud computing, but they are not yet at the point where any project, within any team in the bank, can quickly spin up a development environment to test a hypothesis with readily available AI enabled applications. This is the vision that banks should be aiming for today.
In the absence of full adoption, banks can at least ensure they have a structured technology pipeline moving from a development sandbox to a secure, highly controlled production infrastructure, with states in between that allow development to take place with a varying level of control. Engineers can then develop and test solutions in a controlled manner, building out the algorithms, microservices and APIs required to connect to existing infrastructure and data sources. This interoperability will allow teams across the bank to benefit from a single AI solution.
Where a vendor AI solution is being tested and ultimately implemented within the bank, the technology needs to allow third party applications to be hosted within internal environments, or provide a secure pattern to connect to them. Keeping the number of vendors to a minimum will help to maintain an efficient process and strong governance. To do this effectively each AI project needs to make their solution available to be used across the bank, and to create commercial constructs with vendors that allow for engagement by multiple teams, departments and geographies.
Getting the technology right is a key foundational component for any AI project. Companies that are more digitally mature (fully embracing cloud, utilising APIs, microservices architecture etc.) are far better placed to reap the benefits that Artificial Intelligence can bring.
Read our whitepaper “Navigating AI Financial Services” for more information and for the Woodhurst Blueprint© for building Artificial Intelligence capabilities
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- Why everyone is talking about AI
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