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The future of AI in fintech


Panellists on stage at the Credit Summit, including Cashflows CCO, Camilla Sunner; AI; fintech; implementing AI; future of AI; future of tech; insights

Over the next twelve months, it is clear that AI, it’s implementation, and what it means for the fintech industry will be a key topic of discussion amongst thought leaders, industry experts, and regulators. As AI becomes increasingly embedded into processes, both for customers and behind the scenes, the impact this will have necessitates careful consideration to ensure that its use equates to clear benefits. With 77% of bankers believing that the ability to unlock the value of AI will be the difference between the success or failure of banks, AI and how to implement it successfully is going to stay top of mind1.

Whilst much is being done in the background of businesses from and AI perspective, how this will be taken forward and used for consumers at various touchpoints remains to be seen. So far, there has been less done to provide concrete advantages to customers, which is a lost opportunity to creatively use AI to improve the customer journey and experience. With 2022 Emplifi research showing that 86% of consumers would leave a brand they were previously loyal to if they had just two or three bad customer service experiences, AI could offer the solution to ensuring consistent and speedy support2.

With a 2021 survey from J.P. Morgan Chase highlighting that 89% of respondents already use mobile apps for banking and 41% want more personalised banking experiences, there is definitely an appetite for integrated tech and the kind of comprehensive data gathering enabled and processed through AI3. Innovations involving AI predictive technology, for example, could make using the card of your choice for certain purchases via a mobile wallet (Clubcard for groceries, credit card for large purchases, etc.) far easier or assist in switching bank accounts based on predicted needs. 

It is my opinion that seeing how AI can offer improvements to financial institutions will also help to drive increased consumer trust in an industry that has historically struggled to obtain this by making lives easier and increasing transparency.

However, care does need to be taken that the switch to AI is considered. From the rise of Chat GPT and other AI tools that have taken the tech world by storm over the last few months, it is evident that AI is becoming ubiquitous far faster than is perhaps wise. 

One reason for hesitation is that, though there has been much debate around the issue of ethics and bias, particularly the impact of data biases on AI programmes, regulation and oversight lags, as usual, behind the speed of development. Issues with telling fact from fiction and the validity of sources necessitates caution.

The other is that we still don’t fully understand much of the AI being implemented. Whilst users arguably do not need to understand the inner working to utilise the product (look at iPhones – how many people know how apps work versus how many people use apps?), even those who have created AI programmes have said they don’t fully understand it and have more to learn. This is particularly worrying in light of Bank of England findings that machine learning tools are in use at two-thirds of UK financial institutions4.

There are clear risks with companies using AI programmes that they don’t understand, particularly those that involve automated decision-making. A study from IBM showed that over 90% of fraud notifications generated by these systems do not result in the creation of a suspicious transaction report, meaning customers are being declined without any notable improvement in fraud detection5. We need to continue to ensure oversight to avoid the so-called “Blackbox hallucinations”, where erroneous decisions or information is the output. The trick will be to establish the correct balance. To avoid complacency whilst taking advantage of the benefits of automation, being able to focus on the 20% of the job that requires more time and complexity and increasing value.

Long term, the question on everyone’s minds is the impact on jobs. There’s an argument that we will always need a human touch in customer interactions, but I would actually disagree with that certainty. I am very much of the opinion that customer expectations are driven by think it’s dependent whether you’re used to something and whether you’ve grown up with it. In my lifetime, I think we will always need a human touch to our interactions, just from a comfort element. For the younger generations growing up with automation, I don’t think they will cling to it in the same way.

There will always be jobs for people, but it is becoming increasingly clear that we have no idea what those will look like. The key question, therefore, becomes: how can we educate the next generation if we have no idea what the requirements for them will be? I think one thing we can be certain of is that AI is going to demand a lot more critical thinking and evaluation skills from people. We will increasingly have to be able to make the decision of whether we can actually trust the outputs of AI and should use those going forward.

AI will continue to drive benefit and efficiency, with automation freeing up valuable time and resources, enabling people to focus on areas that drive value to be increasingly creative. However, it is process that needs to remain centre stage, with AI providing creative solutions to provide better experiences rather than looking to innovate for innovation’s sake. The movement has facilitated change incredibly quickly, and we don’t know the true extent of what the AI can do or its possible repercussions. It will be key to be deliberate and careful in how the technology is implemented in order to achieve the best outcomes for consumers and businesses alike. 



1 Forbes

2 Emplifi

3 JP Morgan Chase

4 Bank of England

5 Pymnts