Picture the scene. You approach the average shopper on the average high street and ask them how they think a bank decides whether or not to offer them a mortgage. What’s their response?
Do they dive into an animated monologue about open data access requests, Big-Data-fuelled categorisation and fine-tuned machine learning algorithms? Or do they pull a face and suggest the mortgage “gatekeeper” is some poor soul sitting in a darkened room, trawling through reams of paper, and ultimately applying a touch of magic and personal judgement to make this life-changing decision?
As we all know, the second response is the one you’re more likely to hear. And it reflects a widespread perception that people wanting to buy their dream home are at the mercy of complex processes, mysterious systems and opaque, arbitrary decisions.
Today, a new generation of “proptechs” and “fintechs” is leading the way with a wave of engaging, end-to-end, transparent and informative mortgage application processes
But it doesn’t need to be that way. Today, a new generation of “proptechs” and “fintechs” is leading the way with a wave of engaging, end-to-end, transparent and informative mortgage application processes. Examples include HomeFinder from Lifetise (a graduate of our 2019 FinTech Innovation Lab London). This is a product that maps out affordability for a buyer over time, and then integrates with Zoopla and online brokers like Habito and Trussle when they’re ready to proceed to purchase.
Equally, many incumbent lenders have been working behind the scenes to implement sophisticated decisioning engines that support the purchase process while reducing costs and increasing lending volumes without increasing risk—all helping them to stay competitive in today’s challenging low-interest-rate conditions.
However, not all lenders are doing this. Some are still far from embarking on a true digital journey and continue to fit the stereotype of high operational costs, heavy manual effort and complex policy rules preventing quick, accurate and transparent decisions.
For any aspiring lender, the compelling business case for transforming their underlying decisioning capability is reinforced by the fact that digital challengers and neobanks are claiming a rising share of the profitability available on credit products.
Be informed, be personal, be efficient!
The good news is that decisioning is at the heart of the market-leading opportunities on offer—and to seize them, there are some tangible and highly impactful changes that lenders can adopt. I see these falling into five key areas:
- Open Banking data
Lenders can provide a smoother experience with fewer touchpoints and more robust, accurate decisions by running an open decisioning platform that—with the customer’s consent—can quickly draw in income data using Open Banking application programme interfaces (APIs). - Non-traditional data points
Taking the Open Banking concept further, affordability calculations can be refined to broaden lending to new customers by drawing on data sources that were historically excluded, like Experian’s Rental Exchange. Some fintechs are now using transaction data to identify rental payment history and support lending decisions for first-time buyers.
- Rate personalisation
Advanced decisioning tools can enable lenders to use tailored pricing and preferential packages to target specific segments or loyal customers, helping to address issues around customer retention and undifferentiated products. - Tailored bolt-on products
Personalised offers for further relevant products can be generated to create a more end-to-end experience and maximise the benefits reaped from customer analytics in the decision engine. For example, BBVA’s Valora tool includes a portal to view prospective homes, apply for a mortgage and arrange home insurance quotes. - Harnessing automation
Automation offers great potential to boost efficiency, reduce costs and optimise the entire end-to-end application process. The opportunities include streamlining decisioning activity through an intelligent decisioning system such as Credit Kudos that makes affordability decisions in near-real time, and deploying Robotic Process Automation (RPA) for the remaining manual activities such as desk-based home valuations.
Time to realise the decisioning opportunity
Market-leading decisioning technology is already here—and transformed end-to-end mortgage application processes are available to try out. Partly as a result, cost bases are reducing, customer expectations are changing, and mortgage decisioning is getting faster and more accurate.
The lenders of the future are embracing new capabilities and learning how to capitalise on them to maximise business value and customer benefit—while also building more effective and profitable operations.
In the era of Open Banking and open data, the opportunity to move to a truly digital decisioning approach is clear, and the steps to take have been mapped out. It remains to be seen which lenders will help to change those perceptions of mortgage decisioning held by the average shopper. But one thing’s for sure: Change is on its way for this market.
My thanks to Rebecca Gilmore, Mohsin Chaudary, Nick Foulcher and Graham Cressey for sharing their expertise on this topic.
This blog makes descriptive reference to trademarks that may be owned by others. The use of such trademarks herein is not an assertion of ownership of such trademarks by Accenture and is not intended to represent or imply the existence of an association between Accenture and the lawful owners of such trademarks.
