Analysis of the ‘Credit Counts’ National Strategy Measure: Adult Financial Capability Survey 2018

• Context
• The study
• Key findings
• Points to consider

Context

Credit Counts is one of five headline measures making up The Money and Pension Service’s (MaPS) UK Strategy for Financial Wellbeing for 2020 to 2030. It is about people’s ability to manage credit day-to-day and MaPS’s chosen measure is based on people not using credit for everyday essentials.

Those who very or fairly often use credit for food and bills are defined as using credit for everyday essentials and are counted in the ‘credit for essentials’ group described here. There were an estimated nine million adults in the UK who met this definition in 2018 and MaPS has set a national goal for reducing this by two million people.

The study

The analysis uses data from the 2018 Adult Financial Capability Survey (n= 5,905). The question asked in the survey to capture using credit for essentials was, “How often do you/your household use a credit card, overdraft or borrow money to buy food or pay bills because you’ve run short of money?”.

The focus for the study commissioned by MaPS was to explore how the nine million adults who often used credit for essentials in 2018 differed from other adults who were not using credit in this way.

The borrowing behaviour of these adults was also explored in the analysis using four key borrowing measures:

• Being very or fairly often overdrawn on current account.
• Very or fairly often borrowing money to pay off their debts.
• Very or fairly often borrowing from family or friends.
• Having used short-term high-cost credit in the last year.

The author used bivariate and multivariate (logistic regression) analyses to determine the strongest predictors of using credit for essentials from a range of demographic and socio-economic characteristics.

Key findings

Looking at individual key demographic and socio-economic characteristics, people using credit for everyday essentials in this way were significantly: * More likely than average to have dependent children present in the household (54% compared with 31%), and to have two or more children (31% compared with 17%). * More likely to be in a couple with children (36% vs 22%) and to be aged under 45 (73% vs 48%). * More likely to own their home with a mortgage (39% vs 34%) and less likely to rent from a social landlord (9% vs 14%). * More likely to be employed full time (60% vs 42%). * More likely to have lower household incomes, of less than £11,000 per year (31% vs 26%) or higher incomes, of £50,000 or more (20% vs 16%). In other words, their incomes were more polarised than those of other households. * More likely to report having disability (32% vs 26%) or a mental health problem in the last year (27% vs 12%). * In regression analysis, the strongest predictors of using credit for essentials from a range of demographic and socio-economic characteristics were having a child present and reporting recent mental health problems.

Adults who often used credit for essentials were split into three subgroups:

• A first subgroup did not meet the criteria for borrowing on any of the further borrowing measures (27%) or were overdrawn only (10%), totalling 37% of the credit for essentials group).
• A second subgroup met the criteria for borrowing on at least one of the other three measures, possibly in addition to being overdrawn (42%).
• The final subgroup, with the broadest borrowing behaviour, met the criteria on all four of the further borrowing measures (22%).

The report further explores key demographic and socio-economic characteristics of each of these sub-groups.

Points to consider

• Methodological strengths/weaknesses: The data was collected in 2018, therefore numbers reported in this study may not reflect the true scale of the numbers of people using credit for essentials today.
• Generalisability/ transferability: The data and subsequent analysis relates to credit use in the United Kingdom but findings may be transferrable to other countries.
• Relevance: The findings provide useful insights that can inform the development of interventions and targeted support in improving financial capability among working-age and retired people.