Modern banking is evolving. Increasing consumer demands for better technology, combined with the rise of open banking and digital-native challengers for example Monzo and Starling, mean that traditional members of financial services industry must develop new, innovative methods to remain competitive.

AI (Artificial Intelligence) will undoubtedly have a significant role to play in this. AI and ML (Machine Learning) will enable Financial Service companies to intelligently process large-scale data to create better customer decisions, identify fraud and automate certain customer service elements through technologies such as chatbots. Many of the large banks are already doing this. However, legacy IT systems and latent security concerns means many are also stuck in the concept stage. For big organisations, becoming more agile and adaptable could be a challenge. However, as new functions and employ cases for AI emerged, it's imperative that the financial sector has the capacity to lay strong foundations for AI which permit it to keep up with the pace of innovation.

Carmine Rimi, AI Product Manager at Canonical


Creating the AI Building Blocks
The initial step is ensuring that the right technology is in place to enable the use of AI. Many banks are already undertaking digital transformation initiatives and also have embraced the cloud for handling the large amounts of data they handle. Yet they are still not set up to optimise their utilization of AI. Cloud is by far the very best method of implementing AI due to the sheer scale of the workloads that are being handled, combined with the fluctuating interest in running algorithms. However, the compute power necessary for AI will not always be constant. Spikes in data inflow or changing demand for AI initiatives from over the business means that the scalability of public cloud is often more appropriate for running AI efficiently, as opposed to using static on-premise solutions. Regardless of this, regulatory concerns have held back a lot of lenders from making more use of public cloud.

In this environment, multi cloud me is becoming ever more prevalent. Banks and other financial institutions can operate across both private and public cloud environments to ensure security and regulatory compliance, whilst using public cloud to benefit from its advanced AI capabilities and workload management.


The humans role in AI
Alongside the hype that surrounds AI, there've also been lingering concerns concerning the impact AI might have on jobs. Ex-Barclays CEO Antony Jenkins recently predicted that AI could lead to 50% of jobs in banking being replaced. While so certain roles in bank branches and customer service could be at risk due to AI's automation capabilities, AI also reveals a host of new roles inside the industry.
AI inherently still requires human input to be effective. Naturally engineers and developers are necessary to create and apply AI algorithms, in addition to manage the supporting technology stacks which enable its use.

There may also be an increase in critical strategic roles dedicated to interpreting data produced by AI within the banking industry and making it actionable insight. Business logic is still driven by human thought and motivations which AI can't account for, and people need to be trained to step into this gap to ensure that we being an industry can make the best of AI.

AI may be used to bring together unstructured data on people to create profiles which inform what type of products or communications are perfect for each, but without teams been trained in how to understand and apply an algorithm's output, businesses won't be able to extract the true value of the various tools.

This opportunity to nurture new, technology-based roles is one the industry must embrace with both hands moving forwards by taking a look at how to reskill workers to concentrate on AI.


The future of AI in banking looks bright
Many financial institutions are currently engaged in the process of making cultural shifts to organize for adopting AI on the broader scale through retraining staff and changing management structures for AI use. These organisations must also monitor for the potential purposes of AI in the future to ensure the foundations they lay now will be scalable for future uses, for example applying automation and insight capabilities to new areas.

Looking ahead, we expect to see the AI-enhanced cyber-security sector growing. This is one that will prove to be of particular importance for banks. AI has been used for fraud detection by banks for some time, but with banks also having to deal with malicious hacks at an increasing rate, using AI to improve and automate security will require AI-ready infrastructure.

Blockchain has also generated considerable hype inside the industry over the past year, although questions remain over how effective it can currently be. Implementing a culture change now that allows for improved AI use will however mean that banks are prepared to capitalise on blockchain because the technology matures, blending the technologies together.


Banking with an AI future
AI is already playing an important role for banks. However, to prevent challenges from more nimble, cloud native companies, it will be critical to take stock of the current infrastructure and have a clear picture of how to create a foundation that will allow for the utilization of future AI technologies. With this strategy in place, the financial services sector stands to reap real benefits from an AI future.

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