AI in banking: where next?

Chatbots, apps and on-demand services are established tools within financial services. Explore how technology and regulations are driving institutions to evolve still further.

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Artificial intelligence (AI) isn’t coming to financial services.

It’s already here.

The industry has always face unique challenges when it comes to balancing innovation and agility with security and governance. In the past, the need for caution may have meant lost opportunities for institutions. This is no longer the case, at least for forward-thinking leaders.

A recent Gartner CIO Agenda survey found ‘Banks and other banking and investment services organisations clearly recognise that the status quo is not sustainable, and they must disrupt themselves before it is done to them’.

The growth in the use of chatbots, apps, mobile banking is all testament to this. Where will the industry go from here? Below we take a look at some of the way banks and insurers are evolving their early-stage offerings.


By 2020, AI will be the main way banks interact with their customers. This prediction comes at a time when customer experience has become the new battleground. At first glance, this may seem somewhat of a paradox: How do banks and insurers ensure a more personalised experience, without using people?

The answer is chatbots.

AI will eliminate 1.8 million jobs and create 2.3 million by 2020 (source:

So far these have been mainly used as a solution to automated ‘press 1, press 2, return to the main menu’ call centres. Or a more interactive version of a website’s FAQs. However, over the next few years expect the chatbots role to evolve. Recommending products, helping with budgeting, becoming a de facto personal adviser, such as Cleo.


Insurance has always has access to vast volumes of customer data. The challenge has always been about extracting value, and insight. Expect this challenge to be met sooner rather than later.

Insurtech startup Lemonade hit the headlines when it used AI to process a claim within three seconds. High use of automation for transactions reduces fees, while a ‘one click’ switching service is accelerating the company’s growth.

Tractable, another startup, is using ‘AI estimating’ technology to ‘ provide a full estimate repair cost using photos in minutes’.

Cyber defence (and attack)

Cyber defence is no longer about simply securing an organisation’s perimeter. The rise in mobile devices and cloud-based computing means institutions require real-time protection and authentication at every stage. Until recently, security tools such as automation and DCIM systems were sufficient for this (human error notwithstanding). Not any longer.

At Black Hat USA 2017, a leading cybersecurity conference, 62% of attendees surveyed say ‘Criminals will likely use AI for offensive purposes in the next 12 months’. By 2021, there will be 3.5 million unfilled cyber security jobs worldwide. AI, along with machine learning (to learn from hackers’ AI attempts), will step into the breach and bridge the gap.

A question of questions

Of course, there are still plenty of early-stage answers to resolve. At first, AI was touted as the panacea for managing the overflowing streams of data (more created in the past year than since the beginning of the human race). In 2018, new legislation may force a rethink.

GDPR comes into effect on 28 May. PSD2 and the move to open banking is under way. In any era, these changes would have a major impact on banks and insurers. In Industry 4.0, things are magnified. It’s unclear if banks will still have the rights to access the data. Using third parties to validate insurance claims may be problematic from a regulatory and compliance perspective.

This uncertainty is why many banks are going down the partnership route. Whether that’s with fintechs or transformation consultants. It all points to one thing. A culture of collaboration will join innovation as a central feature of 2018’s financial services landscape.

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New guide: Applying AI to financial institutions

Analyse the future potential of AI, with use cases for financial institutions