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January 13, 2017updated 28 Jun 2022 9:07am

Are Bots Ready to be Bankers?

The bots are ready, are you?

By James Nunns

In 1950, Alan Turing anticipated the rise of Artificial Intelligence (AI) with his “Turing Test”, which imagined a conversation between a computer and a human and declared that if the human couldn’t tell if they were talking to a computer then it must be exhibiting intelligent behaviour. In 2014 the Turing test was finally declared “passed for the first time”.

This has been made possible by the rise in popularity of chat and instant messaging –

about 2.5 billion of us have at least one messaging app installed on our smartphone and it is becoming an increasingly popular forum for businesses to deliver their customer service.

Here at Intelligent Environments we’ve seen this opportunity emerge as increasing numbers of our clients have come to us to discuss how to capitalise on chat and instant messaging to improve their customer service offering. Live chat now delivers the highest satisfaction levels for any customer service channel at nearly 75%. The next few years is likely to see a boom in the use of chat bots in commerce and Gartner predicts that by 2020 autonomous software agents will participate in 5% of all economic transactions.

Tech giants Google, Apple, Facebook and Microsoft have all opened up their platforms to third-party chat bot services and bots are already at the core of some companies’ business models. However, there are still challenges with bots. Research by Wired magazine concluded that during the recent US presidential election about 20% of tweets were generated by bots that were spreading “rumours, conspiracy theories or misinformation…and having their tweets retweeted by thousands of humans”. Their output could easily have been mistaken for grass roots support and may even have influenced voted turnout in some areas.

The last few years have seen a step change in the sophistication and scale of bot use across the financial services industry. Virtual agents that use natural language processing and machine learning to understand and answers customers’ questions have begun to appear with RBS and Sweden’s SEB banking group deploying bots based on IBM’s Watson technology.

Deploying AI technology offers banks a variety of opportunities to improve customer service and make savings internally. Historically, banks have struggled to build a responsive presence in the communication channels their customers prefer. For example, it takes companies about 10 hours to respond to a Facebook private message but bots can give users an instant answer.

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Internally, chat bots can reduce the cost/income ratio in the same way that automated support systems have reduced call centre costs. Bots don’t require a salary, paid time off or health insurance and they’re available to deal with multiple customers simultaneously, 24 hours a day. Although deploying bots might allow financial services companies to reduce their head counts, they can also free up humans for more complex work.

While it is still early days for the banking bot, in March, Amazon and Capital One announced that customers can now pay their bills just by talking to a bot running on Alexa, Amazon’s intelligent personal assistant on its Echo device. Meanwhile at Money2020, Bank of America unveiled Erica, a smart chat bot that’s coming in “late 2017”. Erica is said to make use of AI, predictive analytics and cognitive messaging that will help customers make payments, check their balances and even offer advice on saving money and reducing debt by directing users toward educational videos and articles.

While bots are starting to find a role for themselves, they are not the panacea, just yet. Bots can still frustrate customers by failing to set expectations or by acting in unexpected ways. As Forrester analyst Peter Wannemacher notes that’s not a problem if you’re just ordering a taco but “the stakes are too high when it comes to actions and advice related to people’s money”. There is also the question of emotion, for all its intelligence AI still can’t emphasise or understand emotions – bots can’t hear a customer’s frustration.

Ultimately, whether customers want or accept bots will probably come down to trust and whilst it’s unlikely that AI is going to start experiencing feelings any time soon, the Turing test teaches us that it doesn’t have to, but it will need to learn how to fake them.

The strength of AI comes from its ability to learn and some gremlins can be addressed through practice – robots can learn colloquialisms, spot spelling mistakes and poor grammar, by watching humans’ process enquires for example.

In small numbers, on messaging apps and digital assistants, bots are already bankers. Their number is growing and whilst their success is not assured, Moore’s Law and the commodification of machine learning technology make it more likely than not.

Machine learning will allow banks and financial services companies to cut costs and scale up to offer customers a personalised and always-on service wherever they are. Chat bots will never be a standalone solution to business challenges; rather a part of a company’s larger portfolio of digital touchpoints.

Just as banks adapted to technological shifts by making themselves available over the phone, on the internet and on our smartphones, they must now add chat and messaging to their omni-channel strategies.

The bots are ready, are you?

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