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From HELOC to HELOAN, the global mortgage lending market is vast – it reached almost $11.5 billion in 2021 and – despite economic slowdowns – is estimated to grow at a CAGR of 9.5% through 2031, reaching a mammoth size of $27.5 billion. 

However, the last few years have brought the mortgage industry face-to-face with an unprecedented challenge – to digitize core functions almost overnight to tackle record levels of origination and forbearance activities. Many lenders had to expedite tech projects to provide the necessary infrastructure needed to support these new practices and accelerated digital solutions to create better customer experiences and reduce operational costs.

While the industry has found success in adopting new digital solutions, the UK still faces a housing affordability crisis, leaving consumers even more reliant on credit for mortgage originations, refinancing, and regular payments. Though there are attempts to combat the lack of affordable mortgages, like this initiative from Skipton Building Society, rates continue to rise.

Amidst these economic challenges, however, innovation and technological advancements in the industry provide opportunities for companies to adapt and succeed in this challenging environment. From better customer experiences to more accurate credit risk decisions and more financial inclusion, the industry is evolving. 

Discover the top three mortgage lending trends that can help you make smarter credit decisions today to thrive tomorrow.

Mortgage lending can be tedious for both lenders and applicants at the best of times, due to lengthy, complex processes with multiple stages. While mortgage transactions can take between six to eight weeks to close on average, consumers believe they should take no more than three. That’s why automation is a trend with wind in its sails: decisioning automation can help lenders meet borrower expectations. 

Instead of having to wait months for a mortgage, decisioning automation allows lenders to approve customers in a fraction of the time. Even the most complex processes are streamlined, saving time (and brain power) across the board. Customers benefit from approval periods that align with their expectations, while lenders expedite their workload to produce more accurate decisions, faster – freeing up resources to attract and retain customers while boosting sales volume. 

While automation may seem intimidating to actually use, finding the right decisioning automation tech is often the biggest hurdle. Take control with flexible technology that offers drag-and-drop UI, letting you configure and reconfigure automations to reflect your changing needs, eliminating reliance on vendors and dev teams. With optimized data and integrated workflows that can layer on top of existing tech and talk to a variety of systems, automated decisioning can be as simple as clicking a few buttons.

Credit risk decisioning is an essential element of mortgage lending, ensuring that lenders are mitigating fraud and default risk and borrowers are getting the right loan terms. For long term loans like mortgages, accuracy is essential to mitigate risk and provide competitive offers to consumers. And an increasing number of mortgage lenders are using data-driven risk decisioning to do both.

Mortgage lenders no longer have to accept uncertainty – whether it be in economic conditions or customer behavior. Accessing real-time data ensures more accurate creditworthiness assessment and lower risk for the lender. It can also help businesses grow by providing the insights needed to hyperpersonalize offers for both new and existing customers, improving competitive advantage. On-demand data can also help flag if risk profiles change, allowing lenders to step in long before missed payments or home repossession.

The ideal way to harness data-driven risk decisioning for your mortgage lending business is to invest in a data and decisioning ecosystem in which the decisioning engine pulls real-time data on demand from a variety of data sources through a single API. The streamlined, integrated tech stack helps you better understand consumer needs across the entire customer lifecycle. Add in machine learning for evolving customer insights that will eliminate the guessing game and let you make smarter credit risk decisions.

Financial inclusion has been gaining traction in the fintech world for years, but recent global economic and political overhauls permanently changed the way we think about access to financial services. Alternative data is a central feature enabling financial inclusion initiatives for lenders across the world. No wonder 65% of credit risk/lending decision makers use alternative credit data on at least half of their credit applications. And that number is only growing, helping lenders accelerate financial inclusion by enabling the creation of alternative credit scoring models, eliminating reliance on traditional credit bureau data alone.

Traditional credit scores don’t tell the whole story, especially when it comes to thin or no-file consumers – and 71% of credit providers agree. Alternative data lets lenders access a variety of data that doesn’t come from credit bureaus, including utility payment history, employment data, geographical data, and rent payment history – data that would be especially relevant to establish creditworthiness for a new homebuyer. Mortgage lenders who use alternative data to build alternative credit scoring models can expand their customer bases without increasing risk and support financial inclusion at the same time.

In order to build alternative credit scoring models, you need decisioning tech integrated with alternative data. The most powerful data and decisioning platforms simplify the data supply chain, pulling in the relevant data exactly when you need it to ensure more accurate decisions for every application. And don’t compromise on risk – create processes that pull in more alternative data for thin file applicants and less or none for traditionally creditworthy applicants. 

Mortgage lending is often a long, complex process that puts a strain on both lenders and borrowers. The trends we explored today help alleviate that strain, and that’s why they’re here to stay. 

From automation that improves processing speed and customer experience to data-driven risk decisioning that improves risk assessment accuracy and competitive edge through personalized offers to alternative scoring models that help lenders grow their business and accelerate financial inclusion of the under or unbanked, these trends represent the future of the industry.

Want to take these trends and run with them? Make sure your mortgage lending business is ready with our eBook, The Secret to Consumer Lending Success. Download it today!