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AI Chatbots: Closing the Gap Between Fintech and Traditional Banking

In recent years financial and big tech companies have taken over parts of the payments industry that were previously dominated by traditional banks. The latter are not resting in defeat though, as they attempt to catch up with fintech firms by implementing superior user experience and internal design.

Smart use of Artificial Intelligence (AI) and machine learning is helping them close the gap to industry disruptors and in this article Aurélie Fon, product marketing manager for digital banking at Worldline examines how banks are doing this.

Change is coming slowly to traditional banks for a number of reasons, but not for the want of trying. According to the Innovation in Retail Banking report 2019, 76% of banks say that use of advanced data and machine learning is the highest priority for them in their transformation to a digital-first organisation. As an industry, only healthcare saw more AI companies founded between 2014 and 2019. Not only do banks recognize the need to fulfil an ever-growing customer demand for personalisation, but in AI solutions they also find a way to save time and money.

Millions of Messages

One way banks can help their customers 24 hours a day, 7 days a week is through the use of chatbots. According to MobileMarketer, around 40% of millennials communicate with automated bots on a daily basis. Juniper Research says the majority of people used voice search at some point last year and expects that by 2023, 8 billion voice assistants will be active worldwide. 

54% of people do their banking in the evening or during the weekends, which makes chatbots and their always-on working capacity even more attractive. CaixaBank saw a 20% reduction in calls to their contact centre after the implementation of Neo, their chatbot that’s been used by at least 2.5 million customers. Neo has had more than 23 million conversations and customers received fitting answers on 85% of their questions, needing no further (human) assistance. 

Another example of chatbot success can be found at Bank of America, where some ten million users corresponded with chatbot Erica. Erica has helped more than 100 million client requests since its launch and knows the answer to more than 400,000 different financial questions. This being considered, it won’t be long before having a chatbot will be the norm for any financial organisation. 

Human or Automated Advice

Chatbots are perfectly capable of handling most simple enquiries by customers. There is no need for human intervention when someone is logging on to check their balance or making simple transactions. But for more complicated customer service requests, humans are still required. This is because people do not want to rely solely on computers to make decisions for them. 61% of users reject the idea of automated decision-making. However, this number drops to 45% when it comes to seeking advice. People do not object to help from computers, as long as there are experts on hand to have the final word with.

Bank of America is exploring where the human versus machine limit lies with customers. Erica, the same chatbot serving millions of their clients, proactively sends insights about users’ spending and saving habits. On average, 150,000 people click on these insights every week, to gain a perspective on how to improve their finances.

With every conversation a customer has with a computer, the database of possible questions and answers grows. Machine learning improves the bots’ knowledge and with every successful interaction and solid piece of advice, people’s trust in automated banking increases. 

For now, the advantage younger fintech companies have over traditional banks, with regards to automation and digitalisation, is nothing to sneeze at. Several institutions are working very hard to make up lost ground, with more and more banks learning to embrace and successfully use AI to help improve the customer experience.


  • Gina is a fintech journalist (BA, MA) who works across broadcast and print. She has written for most national newspapers and started her career in BBC local radio.

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