Generative Data Intelligence

Technology and the changing face of the mortgage market (Stuart Cheetham)

Date:

How is AI and machine learning revolutionising the mortgage industry?

The mortgage industry is not renowned for being user-centric and change has historically been driven by the lender’s needs. AI and machine learning transforms the customer journey, providing a completely different experience to form filling, document processing and the speed of lending decisions.

Our industry is traditionally characterised by bureaucracy, paperwork, delays, stress and uncertainty for the broker and customer. By reimagining the entire process and capitalising on the power of digital and AI, brokers can have more autonomy and provide greater certainty to everyone in the chain.

Why are advanced forms of technology, such as AI, needed in the mortgage sector? 

A joined-up approach across the entire home-buying process is facilitated by the implementation of AI. The fintech ecosystem has already benefited from digitisation, automation and AI, and the industry should continue to build on the success we have already seen. Technology ultimately delivers faster transactions and better operational efficiencies. 

Confidence in the housing market depends on certainty and stability. Consumers are frequently put off from getting a mortgage and switching mortgage providers because of the lengthy and stressful process. By improving the mortgage process, we aim to take the hassle out of applying for a mortgage, to improve the overall experience of buying or remortgaging a home.  

Is this impact augmented in the current economic climate?How can technology help prospective homebuyers in the current economic climate? 

Whilst activity is slowing down, the cost-of-living continues to rise. Homeowners and buyers are still looking to lock into mortgage rates in case they should begin to climb again. This will continue to be a trend going forwards with further base rate rises expected on the horizon. The House Pace Index, launched earlier this year, revealed that in 2022, 31% of properties received an offer within one hour of a viewing. This is compared to just 7% in 2018. This clearly illustrates the behavioural and societal change occurring to ‘buy now, consume now’, which has been escalated by the likes of Amazon, the pandemic and social media.

Digital technologies primarily offer speed and certainty, but neither is a luxury in this economic climate. With rates changing almost daily for some brokers and available properties remaining oversubscribed with prospective homebuyers, the process demands efficiency. Providing fast decisions creates stability and certainty at a volatile time for many. Brokers need innovative and responsive digital platforms to offer certainty to homebuyers or those looking to refinance their property. Simple user journeys, automated systems and affordability models built on data provide this certainty and stability for everyone in the chain.

What does the future hold, for the UK housing market and for technology in the mortgage industry?

Looking to the future, AI will become embedded within the underwriting process, and its extensive benefits will be recognised across fintech ecosystems. Rather than amend legacy systems, we will see third-party operational platforms becoming more prevalent – within the big banks in particular.

Activity may be slowing downing across the housing market, but people still need homes and need to refinance. Some stability across house prices may be on the horizon, but appetite remains. HMRC shows the number of UK residential property transactions increased nearly a third year-on-year in July as buyers tried to outpace mortgage rate rises.

The big banks have a wall of cash to invest in technology. Since the onset of COVID, banks have predominately invested in distribution and sales given capital expenditure funds were low as a result of the state of the market. However, we are now in a market where banks are cap ex rich and will be looking to deploy their cap ex – developing their technology and investing in third-party systems will be a big priority as the industry looks to source ways to both expedite, simplify and improve the mortgage journey for consumers.

As modelling infrastructure evolves and machine learning capabilities increase, the aim should be to provide real-time decisions to the brokers before they even finish an application. Until the supply matches demand, speed and certainty is what the industry needs.

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