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AI can make customers love, not loathe, their bank in tough financial times

Of all institutions, banks are at the forefront of sensing and encouraging the financial resiliency of their customers. They have clear insights into the state of an individual’s financial balance, spending and debt situation. This is especially valuable as customers’ finances are put under unusual strain through no fault of their own.

Financial resiliency is becoming a major issue as the economy transitions from those measures that protected jobs at risk. Additionally, we are seeing a sharp rise in the cost of living in many major markets including the UK. The FT recently reported that all families will be confronted with higher energy and food bills this autumn.

Increases on energy bills of up to 50% will be followed by tax increases in spring 2022 when national insurance rates will be raised to pay for increased NHS expenditure. Inflation is also set to rise from today’s rate of around 3.2% to 4% by the end of 2021.

Taking these and other factors together, banks are going to find themselves under pressure to provide credit for their customers over the coming months. Making the right responsible decisions around lending and credit will be closely monitored both within banks and by regulators.

The standard approach with a customer under pressure is for a bank to offer a consolidation loan or a temporary extension on an existing credit limit. These options have to be applied with an understanding of the wider context of the individual customer. It’s not that banks don’t have the information they need or the ability to access a combination of the internal and external data to have a fully informed context. It’s often more about the operational setup, the product options, the credit risk policies and how to best apply them in that context and tailor it to the customer’s circumstances.

A good example of what can be done here is how an Australian bank, Commonwealth Bank of Australia, introduced intelligent automation into how customers could seek financial help. It has quite rightly made a big deal of its push to educate customers on the support available from government and the bank through the ‘benefits finder’ part of its bank app. However, it is also set up in such a way that if a customer has a temporary cashflow need, they can, via the app or website, get personalised recommendations of the best options based on products they already have with the bank. For instance, it might suggest a mortgage redraw if they are ahead on their mortgage payments, which would be the cheapest and best result for them.

The AI behind this process is set up to offer responsible lending and do the right thing by the customer. It’s about saying, ‘What is the best advice and context our bank can give to the customer?’. The benefit here is how the AI enables the customer to go through this process themselves without needing manual intervention, but gives the option to access in-person advice if they want. Getting that balance right is critical.

Other banks have done a great job looking at predictive analytics to get an earlier warning to the bank of a customer having problems. This enables the bank to be proactive in offering constructive help before a situation worsens. From a library of rules and next best interactions, you can use advanced probability-based decisioning capabilities to deliver product or service messages that can really help individuals and businesses’ cashflow needs.  

It’s no longer enough to just take customers through a step-by-step journey. Well, you can, but you’d be missing an opportunity – the opportunity to bring personalised decisions to life at scale. Not every interaction with a customer needs probability-based process AI, but for those that benefit from it, then you can really add value for the customer, your staff and controls over a process. For example, setting automated kick-off for KYC investigation processes based on certain triggers or escalating loan application or drawdown scenarios automatically based on probability of credit or non-credit issues. It also gives you the benefit of being able to scale better, gain efficiency and again balance where you need in-person intervention compared to straight through automated processing. One of the debt advisory services here in the UK – StepChange – did exactly that to set up more online servicing, but it was very conscious to highlight and enable personal advice and choice.

It's a delicate balance between using different combinations of automation and AI to speed up advice, resolution and service, and getting to the right level of in-person or virtual assistance. And it’s no more important than when customers are under financial pressure.


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