It doesn’t take a super computer to work out that artificial intelligence is going to make banking more effective. Banks have been using basic customer data to sell more products to the right people for decades. The ability to crunch more data, in real time, and learn from customer behaviour means they can refine this process to the nth degree.
According to research group Forrester, AI will be one of the 15 fintech technologies to watch over the next four years.
The attraction? Its potential to sift and analyse the vast volumes of data that banking generates to give a competitive edge, increase transparency and bring down costs.
AI is particularly attractive for wealth managers and those in retail banking. According to one report, (Efma and Comarch 2016), these sectors can improve customer experience and bring down costs by incorporating AI into chat bots and robo-advisers.
So big is the opportunity that Kearney predicts that assets managed by robo advisers will jump 68 per cent to $2.2tn within five years. Meanwhile, MyPrivateBanking expects hybrid robots to manage 10 per cent of investable assets by 2025.
In many cases, the big breakthrough has been natural language processing – machines that interact via voice, rather than a keyboard or digital recognition. As they learn more language, the programs get better, more accurate and more useful.
Some bank customers can already tell their bank via Siri or Amazon Echo to pay the rent, send cash as a birthday present to a family member, cancel a standing order or increase a direct debit. The service takes note of the command, can decide whether it is likely to be repeated and can nudge the customer ahead of the next time. The service learns context.
Similarly, Finie, a voice-activated intelligent personal assistant from fintech provider Clinc, can be asked direct questions such as: “Do I have enough money to go out to dinner tonight?” or “How much do I spend each month on groceries?”
RBS, NatWest and Ulster Bank customers can ask chatbot Luvo to transfer money. At Swedbank, Nuance Nina offers a human-like conversational service that is currently able to answer eight out of 10 customer questions, and manages almost 80 per cent of the time to resolve any issue.
In wealth management, some companies such as Nutmeg and Moneyfarm have already incorporated AI into their offer. Morgan Stanley uses its 3D Insights Engine to analyse research and products, to match them to relevant clients and financial advisers. BlackRock’s Aladdin uses natural language processing to read thousands of documents including news articles and broker reports, to come up with a sentiment score on a particular company or investment.
AI will also open up wealth management services to a bigger market – to the mass affluent for example – driving revenue and profit growth. AI will bring down the costs of providing a tailored service, through customer data analysis by a computer, making it possible to help far more people.
This is not to say that all wealth management will become automated. It’s likely that ultra-high net worth individuals will still receive a personal service from banks. But even at this level, the information the relationship manager will refer to, with regard the market, and the customer, will stem more and more from AI systems.
When it comes to AI, being a pioneer will pay off. Accumulated learning will give a real competitive advantage. Just look at Charles Schwab, which launched Schwab Intelligent Portfolios in March 2015. By the end of June that year its service had grown to $3bn in assets under management, with more than 39,000 accounts. This scale plays to AI’s strengths – learning from the quality and quantity of data. More opportunities like this beckon.
