It’s been an unusual summer. England’s footballers reached their first World Cup semi-final in 28 years, while the heatwave has caused meteorologists to make comparisons with weather 42 years ago.
Now the Office for National Statistics has identified another rare event: UK households have become net borrowers for the first time in almost 30 years.
Households spent or invested £900 more than they received in income on average last year, the first time this has happened since 1988. It’s an interesting but unsurprising statistic.
The low Bank of England base rate of 0.5% means that mortgages and loans are available from lenders at attractive rates, and people are choosing to take on debt before interest rates go up. Households took out almost £80 billion in loans in 2017, the most
for 10 years.
Examining macro trends in borrowing and spending such as this are always interesting on a macro level – it can help us make sense of the bigger financial picture. But for lenders, the micro level of trended data for individual borrowers is just as valuable.
Looking at the most recent month’s data, two borrowers may look the same to a lender. However, digging deeper with trended data can help lenders to make more informed decisions.
One borrower may be making their repayments comfortably each month, whereas another could also be making their repayments, but be managing a situation where they are becoming increasingly reliant on credit over the last two years.
Furnished with the knowledge trended data from Experian provides, a lender can identify credit behaviour patterns and then make decisions accordingly.
It’s an insight which could be useful when onboarding a customer, but equally could help lenders to anticipate people experiencing problems with debt before it becomes unmanageable.
The information required to put trended data into action already exists, it’s simply about finding the best ways to extract value from it. However, there is also the opportunity to use new data sources such as Open Banking to make for a more detailed understanding
of borrowers in the future.
Whether looking at borrowing at a national level or by household, it’s improvements in the way we use data which can lead to higher quality lending decisions.