New digital lenders aim to bring an Amazon-like experience to mortgages by combining simple, pre-filled applications with deep automation across both back-office and customer-facing processes.
Listed below are the leading tech trends in future of digital mortgages, as identified by GlobalData.
Leading tech trends in future of digital mortgages
Mobile-first design and responsive web
Ever since Quicken Loan’s Rocket Mortgage ad during the 2016 Super Bowl – “apply for mortgages on your mobile” – the industry has refocused on mobile-first design to reduce complexity in the mortgage application process. This is because mobile devices double as document capture (to take a photo) and improved authentication (through biometrics). This has increased engagement as an “always-on” touchpoint for status updates and advice.
Providers like SunTrust and Scotiabank use responsive web design to make that simplified experience immediately available across all touchpoints, then incrementally improve over time.
Minimal viable product (MVP) and agile development
New entrants design and deliver digital experiences in a more customer-centric, agile way. For example, digital mortgage lender Molo launched with an MVP in the less regulated buy-to-let space in the UK and developed that proposition with customers before going after the residential mortgage market. Tandem launched with 11,000 “co-founders” (in this example, co-founders = beta testers) to evolve its mortgage application journey. Co-creating MVPs in short, rapid cycles forges closer connections with customers while creating excitement around the full product launch.
Big data and analytics
Big data and analytics technology help providers analyse a greater volume and variety of data to inform credit decisions. ZestFinance looks at whether an applicant keeps a consistent phone number or has been late paying their phone bill. New digital banks like Redwood and OakNorth focus on the SME sector, combining traditional credit profiles with forecasted house prices and projected business performance – even pulling in TripAdvisor ratings and Yelp reviews. The Federal Reserve Bank of New York estimates these technologies help new entrants realise a 25% lower default rate than incumbents, despite often lending to “riskier” sub-segments.
Application programming interfaces (APIs) enable “connected” ecosystems
APIs help providers quickly and securely access income and expenditure verification, property valuation, and affordability information. This was a big part of Quicken’s success, enabling it to generate reliable “pre-approvals” in minutes. APIs enable fully modular back office functions. This means that digital lenders can pull in best-in-class capabilities across pricing, closing, document management, etc. from a variety of niche fintechs. In the UK, leading digital banks like Revolut offer digital brokerage from Trussle directly within the bank’s mobile app. In the US, Blend offers Blend Marketplace, a B2B platform for third-party digital home equity tools.
Automation (OCR, machine learning)
Optical character recognition (OCR) technology has been used to “grab” data from paper documents. Vendors like Roostify in the US use machine learning techniques to improve accuracy by recognising patterns in textual analysis. Incumbent bank mortgages can involve 700 pages of loan documentation. This is not just slow and expensive to process it is error-prone too.
Artificial intelligence (AI) and roboadvice
AI powered chatbots are critical enablers for various digital mortgage robo-advisors, able to compare thousands of mortgages in seconds. In Singapore, OCBC launched Emma, the first AI-powered home and renovation loan specialist chatbot. Working with AI-enabled data science vendors such as Earnix and Wisor, banks can deliver highly personalised mortgage offers. Instead of 20 different product permutations that confuse customers, providers recommend the one “best” product based on a deep understanding of that customer’s financial situation.
Cloud-based core systems
Cloud lowers start-up costs, run costs, and time to market for new entrants. It is notable that the most pioneering challenger banks have almost exclusively gone down this route. For example, Tandem adopted Fiserv’s Agiliti platform, while N26 and OakNorth have used Mambu. Redwood Bank uses 100% internet-based IT.
Lloyds has invested in Thought Machine towards similar ends. However, sometimes there is no appetite to replace a core system, and no easy way of exposing APIs. In these cases incumbents have used robotic process automation (RPA) to limit the cost and process complexity of legacy systems.
Internet of Things (IoT)
IoT is at a nascent stage in banking. However, the infrastructure for connected homes theoretically enables banks to pop up in moments of need. For example, before customers have had a chance to shop around. They can receive pre-approved offers of additional home financing, or loans for home improvement. Proactive interaction like this helps increase post-purchase engagement, especially when combined with smart speakers and virtual assistants.
In the UK, digital mortgage broker Mortgage Brain is already accessible through Amazon Alexa. PropTech firms in the US, like Opendoor, use IoT to let house hunters view properties by collecting keys from a secure box.
Instead of multiple parties keeping separate records on a mortgage in scattered files and systems, a mortgage blockchain can act as a single tamper-resistant store of all data. This reduces the risk of fraud and provides a full, unchangeable audit trail for all parties. HM Land Registry in the UK has tested the technology extensively.
A Russian subsidiary of Raiffeisen Bank International issued a digital mortgage through a blockchain platform called Masterchain. Similarly, the Chinese state-owned Bank of Communications has successfully issued $1.3bn in residential mortgage-backed securities using blockchain technology.
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