Phillip O’Neill, Financial Services Director, Kin + Carta
Most of the millennial and gen-z cohort will have had little (if any) direct interaction with their local bank manager. But in the not-too-distant past, bank managers were a key figure in the local community.
They knew everything about their customers: the names of their parents, what they did for a living – even where they went on holiday that year. And with that insight into individuals’ lives, they could offer personalised advice and products.
But with the closure of many high street banks, the role of the manager has diminished. And with it, the bank’s connection with the customer has weakened. This has had a negative impact on both the customer experience and banks’ ability to offer the most suitable products and services to the right people.
In the context of the FCA’s new Consumer Duty Act, which places the onus on banks to provide products and services that meet customer needs and offer fair value, this is an issue that requires immediate attention. Fortunately, smart use of AI and data offers a way to fix the situation – and bring a tailored approach back to banking.
Everyone’s a manager with AI
Rather than replacing employees (as is often feared) AI and data will allow all bank staff to take on those missing elements of the manager role. Results from Morgan Stanley Wealth Management’s most recent investor pulse survey show that while 74 percent think AI will help Financial Advisors (FA) better serve their clients, 82 percent believe that artificial intelligence will never replace human guidance.
The personal data that banks collect about their customers means that all the key information managers used to make recommendations is still available to them somewhere. But when it’s siloed in different departments, there’s not always someone who is able to piece it all together and create an integrated customer profile.
Using AI to optimise the data that banks have on file and put it at the fingertips of employees in an accessible format will allow them to cross-sell products in a more coherent and effective way. And by eliminating the more menial elements of data admin, it also frees up more time for them to further understand the customer’s intent and facilitate their desired outcome.
Also, from an ethical standpoint, keeping a human in charge of the final decision that could affect a customer’s financial life retains a crucial level of accountability that should never be removed.
A level playing field
In the local bank manager’s heyday, customers often banked with the same institution for a lifetime. Banks could usually count on selling a full suite of products and services to all of their customers, because it was far more convenient for them to apply for a mortgage or a credit card where there was an existing personal relationship than risk trying to build a new one.
But now data and credit scores are the key influencing factors in the likelihood of being granted a loan, consumers are able to choose from a much wider range of providers. Loyalty is on the wane as a result – and it’s the challenger brands that have benefited most from this shift so far.
A US study from Cornerstone Advisors shows that since 2020, digital banks’ and fintech’s share of new current accounts grew from 36% to 47%, while the shares of traditional banks declined. It’s the same story here in the UK.
Challenger banks are outpacing competitors by using customer data to create personalised products and features that help customers to manage their money, save towards their goals, and buy large purchases with flexible payments. Take Monzo, for example. Since being granted a banking licence in 2017, the company has mined a treasure trove of data about how customers manage, spend, save and borrow money to offer personalised products. It’s gained considerable market share as a result.
Thanks to AI however, we’re approaching a pivotal moment where it’s within the power of big banks to recover this lost ground. It offers the potential for them to intelligently deliver a full suite of products, tailor-made to the customer’s intent, by using the data and metadata they already possess in a smarter way.
Rising to the challenger (bank)
As consumer options increase, there is an increasing need for solutions that match the complexity of their financial lives.
Taking a customer outcome approach to building new financial products is one way to address this. Applications (as the key touchpoint for modern consumers) should be designed not only to be intuitive to use, but tailored to the individual.
For example, adopting the format of a Google-esque search bar in-app, powered by an integrated data profile, could be one way to both simplify and optimise the customer experience. It would help them both when looking for new products and interacting with existing ones.
Artificial intelligence and data can offer a way for banks to level the playing field and match or even surpass challengers’ in the customer experience stakes – but only if they can move to grasp this crucial opportunity quickly enough. The secret is collecting and storing accessible, accurate and trustworthy data that will allow AI solutions to offer hyper-personalization at scale.
