Imagine the bank of the future, where every experience you have in financial services is tailored to your individual requirements.
Welcome to the age of hyper-personalization, where the businesses we use every day — including financial services institutions — create tailored online experiences for customers through a combination of machine learning (ML), artificial intelligence (AI), and big data.
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That’s what Kavin Mistry, head of digital marketing and personalization at TSB Bank, will be trying to create at his organization during the next few years.
“We want to use AI and ML to identify key events in the customer’s life that might necessitate financial support and use that response to help customers ultimately achieve their life ambitions,” he says to ZDNET in a video interview.
Effective hyper-personalization means using data that’s already been collected in combination with emerging technologies to help customers achieve their individual goals.
Mistry paints a picture of the hyper-personalized banking service of the future, and how emerging technology, such as AI and ML, will help TSB to enact its data-led approach.
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“If you’re a new customer, having just onboarded and got onto our mobile app, the first experience would be to establish your needs,” he says, picturing what kind of service his bank would like to provide in a few years.
“We would look at gathering information and data in a gamified way to allow it to be an experience that is straightforward for the customer and that establishes specifically what your needs are and where you are today.”
Those kinds of objectives resonate with Samantha Searle, director analyst at Gartner, who says to ZDNET in a video-conferencing conversation that a successful hyper-personalized banking service should do two things.
First, it should help customers achieve their financial goals, such as saving for a mortgage or better budgeting.
“We’re seeing with advances in adaptive AI technologies that it’s becoming easier for banks to not only put this information into their business operations processes, but to infuse it into their customer-facing processes, so those also can become more goal-orientated.”
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Second, a hyper-personalized banking service should focus on a customer’s life journey and provide support through significant life transitions, such as getting married, looking for a mortgage deal, and offering related add-on products, including home and life insurance.
“So, instead of the customer having to put all this data in a form, for example, when they apply for something like a mortgage loan, the bank would already have a good idea of your credit history through data analytics and would push personalized products and services.”
Back at TSB, Mistry gives the example of how his bank might provide a hyper-personalized service to an aspiring first-time homeowner.
This individual might need to save a deposit for a mortgage, and they might also have to ensure their credit score is enhanced, so they can get the funds they require.
“We would set up experiences, communications, and targeted goals to enable them to save their deposit,” he says.
“We would then look at their spending habits and support them in being able to scrimp and save on a regular basis. We would track where they are versus their goal. And we would keep them updated regularly on any savings opportunities and benefits they can get from TSB.”
Mistry says his bank would also use its data-led approach to ensure aspiring first-time homeowners cover all their bases, whether it’s having visibility into their credit score, developing a route to improving it, or providing access to mortgage advisors once the time is right.
This kind of pathway to effective hyper-personalization involves a careful blend of technology.
Mistry says TSB uses AI and ML-based modeling to understand the propensity for customers to act upon certain communications.
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In the longer term, he wants the bank to predict customer events before they occur and to provide a much deeper understanding of the experiences that people have with TSB.
Mistry’s team scans the market for AI products that will help the bank to achieve its aims.
The company is using Adobe Automated Personalization Activity as part of its strategy and is considering how it might make use of the tech giant’s Firefly tool, which is a generative AI model.
Mistry’s team is also developing a Money Confidence Hub, which will be an area within the firm’s app that allows customers to track and trace their hyper-personalized goals.
The technology is being delivered on Adobe Experience Manager and the aim is to start taking customers on the next stage of their banking journeys at some stage in 2024.
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Gartner’s Searle says moves into hyper-personalization are an important step for any high-street bank to take if it wants to stay ahead of its competitors.
She says banks in the US are more proactive in this area than their UK counterparts. More generally, banks are being forced to act due to the risk of disruption from startup challenger banks, which are “pushing” traditional providers to focus on personalization.
Searle says some banks are partnering with fintechs to hone their hyper-personalized services.
“Banks have been using data to predict customer events for quite some time,” she says. “Now, it’s more of a question of making this effort more customer-centric to achieve hyper-personalization.”
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Crucially, Searle also says that, while there tends to be a focus on machine learning, other systems and services also are likely to play a big role in AI-led hyper-personalization efforts.
“Natural language-generation technologies can help banks to interrogate and understand data, and are also important for things like chatbots and helping the customer to actually engage with the bank when they have a question, problem or complaint,” she says.
So, what about generative AI — could that hyped technology play a big role in hyper-personalization? Yes, says Searle, but we’re still some way away from banks adding ChatGPT-like services to their banking propositions.
“One example might be personalized marketing,” she says. “A generative AI tool that provides smart answers about products could save the customer the burden of having to go off and look and do the research themselves.”
And while hyper-personalization is important to the future of banking, Searle says it’s not the only technology that could help to shape the long-term provision of financial services.
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For customers, the future of financial services is going to involve a lot of technology.
Searle refers to robo-advisors who will guide consumers on their investment portfolios, AI-enabled financial coaches who will help people manage their money more carefully, and something called “machines as customers”, where AI-enabled assistants undertake research into financial services and even make decisions on an individual’s behalf.
“That’s longer term and will appear during the next decade,” she says. “But those trends are another consequence of the evolution of all these different AI technologies and they’re something that an industry like financial services could really take advantage of.”
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