I have recently moved to Dublin for a six-month secondment, and have the pleasure of leading our small but growing Accenture Research team based at The Dock, Accenture’s state-of-the-art R&D hub.

This is an amazing space to work in, where that terrible phrase “the art of the possible” isn’t so cringingly hackneyed, and actually means something. In a room close to where I am sitting writing this, there is a team creating software for a space “cube” that will be launched into orbit to gather data for a project (I could tell you what that involved, but then it would automatically self-destruct etc., etc). In this environment, automation could almost feel old hat.

Not so intelligent automation though. This is definitely in the realm of “anything is possible”. Intelligent automation learns as it works. It isn’t just doing what it is told; it is constantly adapting to new situations. Imagine a robo-advisor that remembers when a customer started to sound agitated during a call, and adapts the number or style of questions they ask on their next interaction, to try to improve the experience? Hyper-personalisation of services is an expectation by which customers will increasingly rank their banking experience, as they become used to having the choices available to them through Open Banking. And intelligent automation is one of the core tools available in a bank’s armoury to get them to this level of service, without (ahem) breaking the bank.

Banks are in the perfect position to ride this wave of personalised services—if they can adapt to a platform that funnels a customer towards these slicker services. And thanks to intelligent automation, this need not come at a hyper-cost to the business, with fully automated approvals that adapt to a users’ preferences and usage of third parties. Even the potential for fraud could be reduced as a result of IA learning a customer’s patterns of use and being able to spot anomalies and potentially fraudulent transactions.

Aside from the pure efficiency benefits available from IA, this technology could also provide recommendations to customers for products and services available to them based on their current circumstances and financial needs, such as an overdraft facility if they are low on funds. Thanks to IA, the bank knows that based on previous spending patterns, the consumer will likely need £x amount to spend until their next bank credit payment is due.

This intelligent automation of services is heavily reliant on data, the last but by no means least part of the AI trinity: People x Process x Data. And there are numerous ways in which banks are custodians of vast amounts of customer information, which is ripe for a reinvented approach. And they don’t even need to send a cube out into space to achieve this.

For more details about how to redefine banking with AI, read our report.

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