It’s been increasingly difficult for people to get on the property ladder in the past 18 months.
With rates fluctuating and Moneyfacts reporting a drop to a 15-day average shelf life for mortgage products in June, the shortest since March, acting quickly in the market has never been more important.
Yet, securing a mortgage is even more complicated for self-employed borrowers due to their less predictable incomes compared to traditional earners.
This highlights lenders’ need for agile and dynamic pricing strategies to accommodate their unique financial situations better.
For lenders, dynamic pricing engines provide a perfect solution, allowing them to customise their offerings to meet clients’ specific needs.
They are particularly beneficial for customers with unique financial profiles, like self-employed individuals, who have traditionally struggled to obtain loans.
Barriers for self-employer borrowers
Self-employed borrowers have always found it disproportionately hard to get a mortgage compared to their counterparts with more traditional income streams.
In 2022, a study by The Mortgage Lender found that self-employed borrowers were twice as likely to have their mortgage application rejected compared to their employed counterparts.
As such, the outlook for the self-employed borrower is overcast and sometimes uncertain.
The main challenge lies in income stability and predictability.
Economic conditions have been volatile recently, even influenced by factors like weather.
According to the ONS, GDP flatlined in April due to wet weather affecting consumer spending. This hits self-run businesses dependent on footfall, making it tough for lenders to assess the repayment ability of self-employed individuals with more unstable incomes.
Self-employed borrowers also face more complex documentation requirements. They usually need to provide two or more years of company trading accounts as proof of income, while employed applicants often only need to submit three months of payslips.
With almost 4.25 million self-employed individuals comprising a significant segment of the workforce, what steps can be taken to improve their access to securing a mortgage?
Dynamic pricing and tailored scorecards
When a customer applies for a mortgage or loan, lenders need to make rapid decisions regarding risk, liability and affordability. This process is particularly intricate for self-employed applicants.
Traditional rate models have often put lenders at significant risk, leading to financial losses and dissatisfied customers.
There are many viable solutions to the problem, and a risk-based, dynamic pricing engine is one. It can mitigate risk by helping lenders make informed decisions on loan pricing, eligibility and risk assessment through instant analysis of various factors.
Risk-based and dynamic pricing is not a new concept. It has long been used for equity release products and lending to portfolio landlords.
In these areas, it effectively accounts for individual circumstances and property risks, enabling lenders to offer more personalised and competitive loan terms.
For mortgages, one key advantage of risk-based pricing engines is their ability to create accurate client scorecards, benefiting underserved demographics like the self-employed.
With the combination of key borrower characteristics, lenders can deliver a personalised scorecards for each borrower, allowing for a more holistic assessment by considering attributes outside of their income.
Borrowers reap the rewards of these advantages by gaining access to more personalised and fair rates.
This approach improves accessibility and ensures that self-employed borrowers receive fairer and more equitable mortgage options, making them feel more included and valued within the lending process.
Lender upsides and challenges
Dynamic decisioning and pricing scorecards offer a win-win scenario, adding value for both borrowers and lenders alike.
By considering individual circumstances, these scorecards ensure that rates vary across borrowers, accurately reflecting each loan’s true risk and potential profitability.
There have been concerns that personalised pricing might lower margins, but this isn’t necessarily the case.
For lenders, these scorecards drive increased application volumes via automation, decrease delinquency rates by accurately predicting repayment abilities, and adapt to changes in borrower behaviour and market trends.
Dynamic pricing scorecards also enable lenders to implement an always-on pricing model that adapts to market conditions and borrower profiles. This ensures that they can optimise profitability while providing fair, tailored rates to borrowers.
And the advantages are not strictly limited to the lenders. Brokers stand to benefit too. Dynamic pricing can safeguard clients and their mortgage applications from risk, resulting in a smoother process.
However, due to legacy systems, the widespread implementation of these technologies in residential mortgages may take time.
Yet, newer lenders are increasingly using new data sources, such as open banking and income verification services, to overcome these barriers, leading to more balanced and data-driven pricing strategies that better accommodate self-employed borrowers.
Embracing dynamic pricing engines allows lenders to significantly improve operational efficiency, manage risks with greater precision, and ultimately move towards the ability to offer personalised pricing.
These technologies will not only help lenders serve this demographic more effectively, but they will also boost customer satisfaction at a time where the market is both highly competitive and rapidly evolving.
Rowan Clayton is product director at finova
