AI: the answer to everyday financial life?

Most ordinary consumers don’t have access to a personal financial adviser, but a growing number of AI services promise to change that by offering tools to help consumers track their spending and provide advice on how best to manage their money.

Although artificial intelligence is used in financial services and to manage more sophisticated financial products such as ETFs, AI is increasingly being used for everyday “wallet management”, says Fabian Stephany, research lecturer in AI and work at the Oxford Internet Institute. This typically involves apps gaining access to a user’s bank account, analysing their spending patterns and offering them tailored advice.

“It could say this is my income and at the end of the month I’d like to save x amount of money, how can I do that?” he said. “But it could also compare you with your peers in a similar financial situation and tell you if you’re spending a lot more on things like food or clothing, for example.”

Some people need a helping hand to manage their finances. According to the UK’s Financial Conduct Authority (FCA), 24 per cent of adults surveyed last year said they had low confidence in managing their money; 38 per cent said their financial knowledge was low.

Apps such as Wally can track a user’s finances across their current, savings, credit card and investment accounts to identify trends and predict upcoming spending, as well as create personalised chatbot-generated spending plans when given a goal and timeframe. Cleo, which plans to relaunch in the UK, can decide how much you could save on a monthly basis and automatically set it aside, as well as fining you a set amount – which goes into a savings pot – if you overspend on unnecessary or luxury purchases. Plum helps users manage debts and overdrafts by setting aside an affordable amount as soon as they are paid.

Taking personalisation a step further, San Francisco-based startup Wallet. AI, which plans to launch in the UK, will offer its users insights such as which days of the week they are most likely to overspend and – using Bluetooth and location data – whether they overspend in certain places or with certain friends.

“We’re focused on behaviour and helping you change your behaviour,” said chief executive Omar Green. “We all want to spend time with our friends, but if your budget is really tight, maybe you can put off that pub date with that person who is having a bad impact on your finances.”

Lenders such as Salad Money are using AI to help borrowers who might otherwise fail to meet underwriting criteria. The social enterprise says its use of AI democratises access to small loans for people with impaired credit scores.

Using individuals’ open banking data and machine learning to categorise their spending habits, it says 85 per cent of applications are automatically accepted or declined, meaning it can process more applications and offer lower interest rates than its customers would normally have access to. Created as an alternative to payday loans, it offers a £10,000 loan repayable over 18 months at a representative annual percentage rate (APR) of 79.5 per cent.

It has lent more than £47.5 million to 35,221 customers over the past four years. Just under half of its customers are NHS staff, while 71 per cent of its customers are female.

“It means we can make better credit decisions for people who would normally be turned down because they have a missed payment, a county court judgment or have gone bankrupt in the last six years,” said chief executive Tim Rooney. “We are putting that to one side and asking ‘can this person take on a credit commitment’ based on their ability to service it and their propensity to pay bills and debts.”

Some experts have concerns about the risks of AI in personal finance, such as whether the behavioural insights generated by transaction data and AI could be used to push people to spend more.

“There could be some bad uses of AI linked to personal finance and then accessed by third parties to suggest to vulnerable consumers what they should do next,” Rooney said.

Many of the apps offer paid-for, tiered subscription memberships, but there are also free services. Mick McAteer, co-director of the Financial Inclusion Centre, said he was concerned that if apps have commercial relationships with lenders or insurance providers, their targeted advice could be geared towards promoting their services.

“It’s unclear how they can monetise these apps – so people really need to be careful about what they sign up to,” he said. “They could end up restricting their choices rather than expanding them.”

Although reputable companies may have data policies that require them to delete and anonymise data, users who are unclear about how AI works may be less inclined to sign up to additional services that rely on the technology if they fear it could be used for nefarious purposes.

The FCA says it is currently considering how regulation can promote the safe and responsible use of AI in finance, and points to its Consumer Duty, which requires firms to develop products and services that deliver good outcomes for customers, as a framework it will use to address issues arising from AI.

There’s also a risk that financial services that rely on AI could exclude people who aren’t digitally savvy. Banks are increasingly using chatbots to manage help requests. While these can handle increasingly complex questions, they often provide limited and pre-defined answers, to the frustration of potentially distressed customers looking for help with their finances.

Holly Mackay, managing director of consumer website Boring Money, says AI could be helpful in dealing with people’s factual questions, such as whether they can have a cash and stocks and shares Isa, but for more substantive advice, consumers may be unwilling to take financial advice from machines.

“People still overwhelmingly trust people, and it will take a number of years for that to change. … I think this is more of a five-year evolution than an immediate revolution.”