The UK financial system needs an "immediate" overhaul to become fairer and more inclusive, according to Sho Sugihara, chief executive and co-founder of Fuse.
He says modern technology can help financial institutions assess a person's risk of falling into financial difficulty and should be used more effectively across the board.
Vulnerable people in particular are struggling to make informed decisions, he says, adding many are "suffering".
In a Q&A with FTAdviser In Focus, Sugihara explains how artificial intelligence and data can help banks spot problems before they arise, allowing them to tailor their products to clients' needs more effectively.
FTA: The rising cost of living is pushing more people towards credit, is there a danger default rates will go up as a result?
SS: Default rates are already on the rise. Statistics from our vulnerability report show that a third (32 per cent) of lenders have seen an increase in borrower defaults over the past 12 months.
Credit is becoming an increasingly important tool to navigate the current cost of living, and when used correctly, it can be a real lifeline for people’s financial stability.
It is vital that mainstream lenders are able to accurately evaluate the real-time financial situation of prospective borrowers to ensure they have access to affordable credit options.
FTA: Would you say current lending models are fair?
SS: Most lenders prefer borrowers with a stable and predictable income, but the fairness and long-term viability of this approach should be questioned. For example, gig economy workers who lack a constant and predictable income are often shut out of good credit as a result of this.
Combine this with the fact that higher interest rates lead to banks applying stricter affordability assessments, this means an even higher number are getting shut off from credit than usual.
With the cost of living showing little signs of easing, the situation seems set to only worsen for many.
The number of edge cases that are rejected has increased, and this disproportionately impacts the likes of gig economy workers or sole traders.
New probabilistic income assessments can alleviate the number of underserved borrowers by helping lenders assess complex earning patterns.
FTA: How can the use of data help lenders make better decisions on credit?
SS: Enhanced insights and data can help lenders predict changes in affordability, probability of default, and even financial vulnerability levels before they occur. This would allow lenders to offer personalised products and services based on the unique characteristics a customer may exhibit.
For example, Health Signals – a product that automates vulnerability monitoring by analysing customer transaction data – has been designed to support lenders to meet the consumer duty requirements that were implemented earlier this year.
