BANKING ON THE FUTURE OF AI

By Carmine Rimi, AI Product Manager at Canonical

 

Modern banking is evolving. Increasing consumer demands for better technology, combined with the rise of open banking and digital-native challengers such as Monzo and Starling, mean that traditional members of financial services industry must develop new, innovative approaches 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 make 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 large organisations, becoming more agile and adaptable can be a challenge. However, as new functions and use cases for AI come to light, it’s imperative that the financial sector is able to lay strong foundations for AI which allow it to keep up with the pace of innovation.

Carmine Rimi, AI Product Manager at Canonical

 

Creating the AI Building Blocks
The first 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 have embraced the cloud for managing the large amounts of data they handle. Yet they are still not set up to optimise their use of AI. Cloud is by far the most effective method of implementing AI due to the sheer scale of the workloads that are being handled, combined with the fluctuating demand for running algorithms. However, the compute power required for AI will not always be constant. Spikes in data inflow or changing demand for AI initiatives from across 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. Despite this, regulatory concerns have held back many banks from making more use of public cloud.

In this environment, multi cloud use is becoming ever more prevalent. Banks and other financial institutions can operate across both public and private cloud environments to ensure security and regulatory compliance, while also 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 have also been lingering concerns regarding 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 it’s true that certain roles in bank branches and customer service could be at risk due to AI’s automation capabilities, AI also opens up a host of new roles within the industry.
AI inherently still requires human input to be effective. Naturally engineers and developers are needed to create and apply AI algorithms, as well as to manage the supporting technology stacks which enable its use.

There will also be an increase in critical strategic roles dedicated to interpreting data produced by AI in the banking industry and turning it into 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 as an industry can make the best of AI.

AI can be used to bring together unstructured data on customers to create profiles which inform what sort of products or communications are best for each, but without teams trained in how to understand and apply an algorithm’s output, businesses won’t be able to extract the true value of the tools.

This opportunity to nurture new, technology-based roles is one the industry must embrace with both hands moving forwards by looking at how to reskill workers to specialise in AI.

 

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

Looking ahead, we also 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 a while, 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 within 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 as the technology matures, blending the technologies together.

 

Banking on an AI future
AI is already playing an important role for banks. However, to avoid 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 use 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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