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3 ways AI can drive customer experience in Financial Services


Although the concept of artificial intelligence (AI) has existed for more than 60 years, only recently have we had the computing power and data to take advantage of it and its practical applications that can benefit businesses.

Machine learning – the mechanism by which computers learn from data to adapt their behaviours to make predictions – is already a presence in our everyday lives. Anyone who has been surprised by the uncannily accurate recommendations made by Amazon or Netflix has experienced machine learning in action.

Machine learning is also playing an increasingly significant role in the way we interact with financial organisations and relate to money itself. In a financial context, it has long been used in high frequency trading, credit assessment, and to prevent fraud.

Letting AI take care of more routine or computational tasks makes businesses more efficient, and gives humans more time to focus on tackling complex issues.


With the predictive insights offered by AI’s algorithms, it’s possible to determine and offer what customers need next, before they even know it themselves.

The real opportunity lies in moving beyond the analysis of data to real predictive insights, spotting issues or opportunities ahead of time based on specific data, aggregate trends, changing habits or even physical locations.

This treatment of data allows businesses to personalise customer experience, as customers have come to expect. According to Accenture’s UK Financial Services Customer Survey 2018, when customers are asked why they’ve switched to a new current account provider, their most common response is ‘lack of personalised services’, with 26% putting this in their top three factors. Among Millennials the effect is even stronger, at 30%. Similarly, the survey found that insurers are also falling short of customers’ expectations when it comes to delivering personalised, tailored products and services.

Customers no longer just want access to their information. They want insights from their data, and a personalised service from the financial services they engage with. The rapid rise of challenger banks like Monzo is a great illustration of this. Having launched in 2015, Monzo now has more than 750,000 customers and expects to reach “several million” customers by the end of 2019.

Why has Monzo been so successful? Because it offers far more than a pre-paid contactless card or what many banks can offer. Monzo customers enjoy an accompanying app, which provides real-time spending notifications and helps users budget. This year, the company also added personalisation to its Help screen for customers.

To preempt customer’s questions before they’ve asked them, Monzo has added a section of answers that are “Suggested for you.” It shows customers answers that it thinks will be the most helpful, based on how they’ve been using Monzo recently. If you’re a new user it will show you tips on how to get started. If you’re abroad it will show you the exchange rates in that country. And if you ordered a replacement card but haven’t activated it yet, it will teach you how to do it. No two users ever see the same Help screen. According to Monzo, by adding this level of personalisation and making it easier for customers to find answers themselves, it’s managed to decrease the number of customers that need to get in touch by 33%.  

At the moment, Monzo personalise these suggestions by manually setting a series of rules, that link certain states to certain answers, but it’s looking to machine learning to help predict customer’s potential questions with much more accuracy, and discover new patterns that are difficult for humans to spot - further freeing up resource within its internal teams.

Home Assistants

Voice activated devices like Amazon Echo, Google Home and Apple HomePod are changing the way we interact with digital content and engage with brands. These next generation digital assistants reduce the need for people to continually have their smartphone in their hand to perform certain tasks or access information.

Home assistants are still in their relative infancy, yet their potential continues to grow as voice recognition improves and more brands develop compatible apps. According to research from Capgemini, 51% of consumers are already users of voice assistants, with 28% of these using their devices to make payments / send money.

Watch our video of a skill we have created for Alexa – as an example of how it can be used within the insurance sector.



Chatbots - automated online services that customers can engage with through messaging apps, chat windows or with their voice - have been deployed by many businesses to handle routine customer service queries on a 24/7 basis, leaving their human counterparts more time to resolve more complex issues. Chatbots can be ‘trained’ with the help of data from previous customer interactions, and are often ready to get to work in a matter of weeks.

Natural language recognition has increased the reliability and effectiveness of bots, as our Technical Strategist and Microsoft AI MVP, Gary Pretty, explains, “It means 100 different customers can come to a chatbot and say something in 100 different ways, but the technology will still understand what they’re trying to achieve. We’re in a position now where these chatbots can rapidly learn and get much more sophisticated in their understanding.”

Research by Accenture has found examples where chatbots can resolve more than 80% of chat sessions, and the cost savings of using virtual assistants to answer basic questions are estimated by the National Australia Bank to be $16 million per annum for its organisation alone.

The potential of chatbots goes further than customer-facing tasks though. They can also be deployed internally to enhance customer service. “Companies can use chatbots internally in a call centre scenario, enabling an agent on the phone to search through FAQs more quickly and efficiently rather than having to know exactly where to go and look. It may not be a customer-facing feature, but it still impacts the customer experience in a positive way,” says Gary.

It’s perhaps of no surprise then that 62% of marketers in Financial Services intend to incorporate chatbots into their marketing approach within the next two years – according to Episerver’s recent Money on the Move report.

As the importance of bricks and mortar declines, the Financial Services playing field is far less dependent on current brand reputation and far more dependent on delivering customer experience through flexible, personalised services driven by deep insights at scale.

“You can definitely see this world emerging where the people with the best AI win.” Saf Iqbal, Senior Digital Project Manager and Strategist, HSBC

You can read more about AI in Financial Services in our report: AI-driven customer experience - what it means for Financial Services