Are banks ready for the transition to a rental economy?

Recent years have seen a shift towards a shared society – or the rental economy – with people moving away from ownership and towards experiences.

The opinions expressed here are those of the authors. They do not necessarily reflect the views or positions of UK Finance or its members.

Put simply, we own less and use more. Present generations are spending and saving differently to their parents, opting for pay-as-you-go models rather than being tied into lengthy contracts, and 60 per cent of millennials in the UK prefer to spend their money on experiences instead of material things. It’s a similar picture for Gen Zs.

There are multiple drivers behind this trend, including post-pandemic working patterns, cost-of-living crisis and increasing mortgage interest rates, but also a significant change in consumer behaviours and preferences. This feeds into the ‘uberisation’ of industries, something we already saw in the prevalence of the gig economy and on-demand services popularised by the likes of Netflix, Airbnb and more.

According to research, as UK consumers embrace ‘access over ownership’, they are spending on average £277 per month renting everything from mobile phones and clothes to cars. With vehicle ownership also declining, many opt for the instant convenience of Zipcar, for instance, when they need it. For today’s climate-conscious generations, sustainability and cutting waste is another significant factor. Nearly one in three people are drawn to renting because it is more environmentally friendly; 40 per cent, meanwhile, do so because they want a more flexible lifestyle. Interestingly, 13 per cent believe that a time may come when they rent “absolutely everything.”

The latest Census data highlights a fall in home ownership over the past decade, with five million households – that’s one in five – now renting across England and Wales (compared with 3.9 million in the decade prior). In parallel, there has been a boom of funds entering the build-to-rent residential housing sector, as more and more people are unable to (think Generation Rent) – or unwilling to – carry the burden of a decades-long mortgage.

All of this could impact residential mortgages as a product but also lending more generally. Banks’ lending portfolios are overwhelmingly reliant on mortgages. However, in a society driven by the rental of goods and a bigger focus on experiences, traditional models will transform. Near-term liabilities will dominate, becoming more flexible as longer-term liabilities reduce. This in turn could be a catalyst for a major change in the typical product mix of banks, and one that they should consider preparing for now.

Society is evolving and banks should align and diversify their models accordingly. Now that fewer people own property and want to direct spending elsewhere, we need new ways to assess and verify creditworthiness quickly and seamlessly to be able to thrive in the new rental economy. Previously, mortgages would provide that long-term assurance to banks. However, near and long-term lending models differ greatly, and the way financial services organisations evaluate risk will have to change.

Typically, when an individual applies for a loan, banks analyse their ability to make repayments based on current income. However, a corporate applying for a much larger loan is analysed based on projected future earning potential. This needs to be flipped around to make it that lending decisions are based on individuals’ future income too, underpinned by the applicant purchasing insurance when it’s deemed necessary to provide that additional security. For that, the financial services industry needs to harness the power of open finance, get to know the customer on a deeper level and tap into more easily available and transferable data supported by fast-advancing AI capabilities (the emergence of ChatGPT brings an even deeper level of intelligence).

Technology and data analytics are growing in importance and will be key enablers of this transition. Better data integration can help create a full profile of individuals’ prospects, behaviours and everyday lives. This approach will also ensure the agility for banks to continuously refine their models based on market changes and any shifts in personal circumstances.

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