IDVU Database Volumes
Overall growth seen in IDVU is 9% with 219,585 additional vulnerable customer records – increasing the database from 2,581,849 to 2,801,434.
Purpose of Loans – What are people using high-cost credit to pay for?
Significant increases in the types of loans are shown below.
The largest shift is the 118% increase in applications for loans to pay household bills including water, gas, electricity, food and clothing. This reflects the current Cost of Living crisis as we see individuals who can no longer afford to pay for everyday necessities from using only their income, as prices continue to rise.
With inflation continuing to rise and the energy price cap going up later this year we believe loan applications for this purpose will only increase.
Loan applications for ‘Reduced hours’ rose by 5% and loan applications to ‘Pay Rent/Mortgage’ dropped by 2%. Employment in the UK remains high and interest rate increases have yet to have a significant impact on mortgage repayments.
The statistics we see from the loan applications support the well-publicised impact of increasing everyday costs for less affluent consumers.
What is IDVU?
IDVU is an aggregated database of high-cost, short-term credit applications – often referred to as payday loan data.
The type of customer who needs this kind of finance typically has no access to funds beyond their weekly or monthly income, has struggled with credit in the past, has no savings and no option to borrow money from friends of family. A short-term loan is often required to pay for emergency, unexpected or increasing costs that have not been budgeted for.
IDVU identifies the individuals most at risk of financial harm and enables the service or product provider to take measures to protect these customers.
IDVU is commonly utilised by lenders, insurance companies, gaming operators and Housing Associations to use information to create better outcomes for their customers, as well as to ensure they meet their regulatory obligations where necessary.
The solution provides top-level categorisation of vulnerability or individually appended data records with current and financial information from loan applications.
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