(Financial Credit Authority)
A study of the credit files of hundreds of thousands of people reveals the typical financial lives of those who fall into money problems. The findings confirm, but also confound many assumptions about financial distress.
Many of us will be fortunate enough never to fall into distressed debt – watching the unpaid bills mount up, the County Court letter arrive, and the debt collectors knocking at the door.
What went wrong for those people who do suffer financial distress? Are there symptoms that could be warning signs for those who would later become financially unwell?
In a first step to try to answer these questions we have researched the credit files of almost half a million individuals in the UK. Our aim has been to study the financial lives of those people who find themselves in distress and identify how they differ from those whose finances keep on an even keel..
The research was based on credit files drawn from one UK Credit Reference Agency and covered records for the period from January 2015 to February 2018.
The study excluded people who had no debt and no regular bills to pay, and also excluded individuals with business loans. Finally, the sample excluded people who were already persistently in arrears on financial commitments – the aim being to study those whose circumstances changed.
The final research was able to draw on the credit files of 428,097 individuals – anonymised of course.
The files provided a wealth of data beyond an individual’s credit score including age, total debt balances, mortgage balances and their use of other types of credit, including standard cost credit (such as a personal loan or credit card) or high cost credit (such as certain payday loans, doorstep lending or rent to own products). They also contained data for average monthly current account turnover, which may be reasonably used as a proxy measure monthly income.
What is distress?
There is no universally agreed definition of financial distress and different organisations use the term in slightly different ways. On the personal scale, of course, financial problems cause feelings of distress to people in different ways and human misery is something that is felt rather than measured.
But for the purposes of such a large scale study using impersonal financial information, we needed to settle on some unambiguous criteria that would show up clearly in the data available. So in the context of this research, individuals were deemed to have entered financial distress if they met one or more of the following criteria:
- They reached 90 days (or a default) on any credit product or bill
- A County Court Judgement (CCJ) is issued against them
- One or more of their credit accounts was passed to a debt collector
- They were declared bankrupt
By this measure approximately 12% of our sample fell into financial distress during the period covered by the study.
Our aim was to compare the financial pasts of those suffering financial distress and those who did not in order to isolate any distinguishing differences.
Looking across the sample, we can see that those who go on to experience distress tend to share some common characteristics six months prior to hitting problems.
They are typically younger, lower income, have a lower credit score, higher total debt balances, and tend to hold more expensive forms of debt. They also tend to have used up more of their available credit.
There is also on average a fall in income among those who enter financial distress. This shows up as a small change in the averages, but underneath this is a range including some people who suffer major falls in income and other who enter distress despite having suffered no such drop.
Distressed debtors also tend to be disproportionately concentrated in major urban centres (London, West Midlands, the urban North West and North East and Southern Scotland).
But while these trends hold true across the study, a closer analysis and a break-down of borrowers into different groups, or archetypes, revealed a more complex picture.
Each of these characteristics (age, income and so forth) were more relevant for some types of borrower than others. And in some groups the correlations were even the opposite of the average.
Using clustering techniques – a statistical method for dividing a sample into meaningful groups based on common characteristics – we identified four distinct groups or borrower archetypes.
The analysis used a range of measures including age, total debt and credit score. Data on income was not directly available, but what could be measured was average monthly turnover in an individual’s current account. Though not perfect this is a reasonable proxy for income.
The other key measures were type of borrowing used by different individuals and it was the type of borrowing that emerged from the cluster analysis as the clearest characteristic for each of our archetypes.
Put plainly, the people in each group typically hold the vast majority (95%+) of their debt in one particularly form of borrowing and so we have labelled each group according to this designation.
It is important to note that we have labelled groups according to their main form of borrowing.
For example, not all mortgage holders are in the ‘mortgage holder’ group. There are a tiny number of mortgage holders in other groups, but their mortgages are typically extremely small and are dwarfed by their other debts.
For the purposes of research into debt, an individual with a very small mortgage, but with high levels of personal loans and credit card debt is not best-described as a mortgage-holder.