At the end of July, new rules will come into force in the UK, setting out tougher consumer protection standards for more than 50,000 financial services firms.
These rules, imposed by the UK’s Financial Conduct Authority (FCA) under its new Consumer Duty policy, establish an obligation on firms to deliver “good outcomes” for retail customers while taking into account the characteristics of those customers, including their “vulnerabilities”.
The new obligations represent a challenge for financial services firms at a time when a cost of living crisis is stretching personal finances.
Yet our research – by Warwick Business School, the University of Leeds, the University of Nottingham and Lloyds Banking Group – suggests that many financial services firms have access to an under-exploited trove of transactional data that could be used to better understand customers and help discharge their regulatory duties.
In the developed world, people spend a significant proportion of their lives online. From doing the grocery shopping to booking a holiday, as well as work, leisure, banking and healthcare, our lives are mapped out in a trail of digital interactions.
The key to unlocking [the value of banks’ data] is knowing the right questions to ask
These details are a potential source of valuable information that many organisations fail to make the most of. For most companies, collecting and storing this information is part of the administrative routine of their business. The key to unlocking its value is knowing the right questions to ask and giving careful consideration to what patterns and associations might be hidden in the data.
For our purposes, we wanted to see if people’s spending patterns might tell us something useful about the likelihood of their defaulting on payments and getting into financial distress.
Spending habits
To investigate this we decided to look at one specific aspect of a person’s spending – their spending habits. The idea is that people who have very chaotic or complicated lives may find it difficult to stay on top of that complexity and are therefore more likely to get into financial trouble.
The more widely a person’s spending is distributed across different categories in a given period the more difficult it is to predict their spending from one period to the next. We call this unpredictable buying pattern ‘spending entropy’ as entropy is often used as a measure of disorder.
High entropy – in this context, more unpredictable spending – is where spending spread across different categories is greater than average. Low entropy spending, meanwhile, is where spending is focused on fewer categories and more predictable.
Our reasoning was that if a person’s spending behaviour is more chaotic, and therefore less predictable, it could be indicative of a disorderly lifestyle or personality that might adversely affect their personal finances.
Our study draws on two main sources of data: the Argus Credit Card Payments Study (190,429 individuals and 197,179 credit cards) and customer data from Lloyds Banking Group, which includes Lloyds Bank, Halifax Bank and the Bank of Scotland (personal current account and credit card details for 100,963 people).
Unpredictable spending, predicted
Using the data, we were able to look at the distribution of people’s spending on a month-by-month basis across a range of spending categories including retail, travel, household bills, financial services, and hobbies and interests.
It was then possible to see if there was an association between unpredictable spending behaviour and problems with managing personal finances. An individual was considered to be in financial trouble if the data showed they missed payments on credit cards, personal loans or mortgages, or exceeded overdraft limits.
The results showed a clear association between the unpredictability of spending behaviour and the likelihood of getting into financial distress.
High spending entropy in one month is a good predictor of missed payments and financial distress in the following month, as well as three months down the line. The greater the deviation from the average towards higher spending entropy, the greater the effect.
Read more on the Consumer Duty
To give a rough idea of the size of the effect, in monetary terms the impact of moving from average to high spending entropy on the chances of missing a credit card payment would be similar to a reduction of £200 in monthly income. Or, for the chances of missing a loan payment, it would be similar to a reduction of £3300 in monthly income.
The exact mechanism for the relationship between spending predictability and short-term and long-term financial distress is uncertain. However, our results suggest that it is more likely to be a personal trait that persists over time than it is a state that changes from month to month depending on the circumstances.
It is important to note that this is an association revealed from the patterns in the data – not everyone with high spending entropy will fall into financial distress, just as not everyone with low spending entropy will avoid it. It is just that the data suggests those individuals are more likely to miss important financial payments than people with average or low entropy scores.
What does this tell banks?
The upcoming Consumer Duty includes an obligation for financial services firms to consider the characteristics and objectives of their customers and how those customers behave, including “vulnerable customers”, at every step of the customer journey.
The FCA's definition of a vulnerable customer is broad: “someone who, due to their personal circumstances, is especially susceptible to harm, particularly when a firm is not acting with appropriate levels of care”.
Spending entropy offers an alternative to intrusive surveys of customers
The provisional results of the FCA’s 2022 Financial Lives Survey suggest that almost 30 million, or 46%, of UK adults exhibited one or more characteristics of vulnerability as of May 2022.
The Consumer Duty means that financial services firms must not only aim to have good customer outcomes but also understand and evidence whether those outcomes are being met. That duty extends specifically to vulnerable customers. It is linked to a longer-term strategy that reflects the FCA’s aspiration to be more data-led and agile, allowing it to intervene earlier to reduce and prevent harm.
Our work shows how routinely collected administrative data can be used by firms to try to gain a better insight into the lives of their customers in order to deliver better outcomes.
Spending entropy offers an alternative to intrusive surveys of customers that rely on self-reported responses and more opaque ‘black box’ machine learning models.
Financial firms can use transactional data that they already possess to analyse their customers’ spending behaviour and help identify those that are likely to get into financial distress and that may be vulnerable.
These findings should capture the interest of managers at financial firms and their regulators.
Naomi Muggleton is assistant professor of behavioural science, Neil Stewart is professor of behavioural science, and Nick Lee is professor of marketing at Warwick Business School.
