Helene Panzarino, Director of the Centre for Digital Banking and Finance at The London Institute of Banking & Finance, explains why banks should use technology to predict financial vulnerability and help clients avoid losses that could harm both customers and the bank
A major European retail bank was already several weeks into an exploratory partnership with a fintech that identifies vulnerable customers when one of its executives made a startling admission: the bank had no idea how many vulnerable customers they had. There could be, the executive added, “a few million”. His firm is not alone.
Why the lack of data? First, definitions of vulnerability have long been fluid and imprecise. Second, regulators have been slow to make banks and financial services providers treat vulnerability as seriously as they should. Third, credit and risk teams are often reluctant to invest in areas with no obvious tie to profitability and/or loss mitigation.
But bank attitudes are starting to change. That’s partly because of cost-of-living crisis – the number of customers showing signs of vulnerability is growing. But regulators are also on the case.
In the UK, the FCA’s new Consumer Duty, set to be enforced from Summer 2023, requires FCA-regulated firms to proactively focus on the “real and diverse needs of their customers, including those in vulnerable circumstances, at every stage and in each interaction”.
Who counts as a vulnerable customer?
Anyone can be financially vulnerable. The FCA defines financially vulnerable customers as those: “who, due to their personal circumstances, are especially susceptible to harm, particularly when a firm is not acting with appropriate levels of care”.
It’s often assumed that being financially vulnerable is identical with being vulnerable in the widest sense – such as having poor health, low levels of education or limited cognitive skills. But that is far from the case. For example, the distracted and overtired parents of very small children, who might otherwise manage their finances well, can struggle with money management.
Many common life events, such as bereavement or divorce, can undermine financial resilience. And then there are the problems of longer-term financial vulnerability that come with serious illness and ageing. Some 15% of those living with dementia and their careers report being victims of financial abuse.
Why the Consumer Duty regulation is good for banks
The Consumer Duty rules might seem like a regulatory burden for banks that is primarily of benefit to customers. But better management of financial vulnerability also supports banks – and their bottom line.
Weak financial resilience among consumers – such as the inability to manage a period of unemployment or unexpected household expenses – has a clear, and direct, impact on bank balance sheets when customers default on mortgage or loans. It’s in the interests of a bank to help their customers build a backstop.
But poor financial capability in general is also a threat to financial services firms. For example, if consumers are using high-rate or predatory financial products, rather than borrowing from mainstream firms, that can translate into higher loan delinquency risk for banks. Why? Because it undermines consumer ability to afford products and services from legitimate businesses that do borrow from financial services firms.
Machine learning can spot financial vulnerability
Financial vulnerability is a highly personal problem, but it’s also a very common one. In the past, banks relied on tellers in local branches spotting struggling customers and offering help.
But that assumes customers will use a branch and that staff know them well, which is unlikely to meet the requirements of Consumer Duty obligations.
What to do? To really know what’s going on “at every stage an in each interaction” banks can use technology. That’s possible because financial vulnerability comes with predictive patterns of behaviour. For example, people suffering from depression may stop using their bank account altogether. Those who suffer from mania, on the other hand, often spend impulsively on things they don’t need, or can’t afford.
Data from cognitive neuroscience can be used to help train machine learning models to recognise, and learn from, patterns of financial distress. If lenders identify and act on those, they can detect problems before they spiral out of control.
Technology won’t be a panacea. Making it useful will depend on really understanding the risks associated with individual customers, and on having staff trained to help identify and manage that.
Implementing technology to identify vulnerability is, essentially, about meeting “the real and diverse needs” of all customers. It’s about good citizenship and good conduct. It’s also an investment that should help the bottom line. It means a firm can avoid any whiff of mis-selling, prevent excessive borrowing and – ultimately – delinquency and default.
And, without the appropriate strategy, handling vulnerability is like steaming toward an iceberg in the dark: you won’t know the problem until it you are on top of it.