Millennial Mortgages – Can AI deliver a human touch to home lending?

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Every year $25 Trillion in new mortgages are issued. Mortgage is perhaps the biggest investment decision consumers make in their lifetime. However, the mortgage process is inefficient, highly intermediated with many pain points and remained has so without too many disruptions for decades.  Low interest rates and squeezed margins define the current state of the incumbent mortgage lenders, who can hardly think of a better way of doing business. Two startups Habito in the UK and Better in the US are using AI to add efficiencies to different parts of the Mortgage processes.

Habito is a UK based startup that is the first to use Chatbots to address the Mortgage advisory/broker space. Habito’s Digital Mortgage Advisor (DMA) looks up details of a customer’s financial life (e.g. employment, salary and personal life plans) with real-time market mortgage rates to calculate an indicative monthly payment. The DMA explains the impact the customer’s decision will have on the mortgage numbers as a traditional mortgage broker would, but in a fraction of the time (average 10 minutes). Habito is founded by Daniel Hegarty, who was Wonga’s head of Product, and is backed by angels including Transferwise CEO Taavet Hinrikus, Funding Circle’s founder Samir Desai and Yuri Milner.

Better, a startup based out of New York led by Vishal Garg, have managed to address the broader mortgage process, right from advising them on the right mortgage option, using AI ofcourse, to funding the mortgage. They have hired the CTO of Spotify to help them with AI capabilities that would personalise the mortgages to the customer’s financial profile. Since their launch in 2014 they have managed to fund over $500 Million in Loans. Earlier this year Better raised $15 Million from Kleiner Penkins and Goldman Sachs that valued them at $220 Million.

"I'm sorry if some of the 'affordability' questions we're require to ask may seem inappropriate."

A JD Power survey earlier this year, found that 62 per cent of people under 35 who bought a home this year said they would use a mobile app for a mortgage application, if their lender provided it. The home buying process, which is meant to be a happy phase in life, often turns out to be traumatic, filled with uncertainties. We have seen some startup activity in the real estate/proptech space (Purple bricks in the UK), real estate transaction management (on Blockchain), and real estate valuations using IoT data monitoring. However, the major pain points in the mortgage process have been broadly overlooked.

Mortgage Pain

Better and Habito have managed to look at the Mortgage lending process and improved it through clever technology, processes and business model changes. Let’s look at a few example pain points within the traditional mortgage process.

Inefficiency #1: Customers looking to buy a property typically need to factor in a few weeks to get a letter of verification (called Agreement in Principle in the UK). This letter states how much the customer can borrow, at what rates and what the monthly payments would be. So if by chance a customer found a property that he would like to move quick on, he would generally be disadvantaged. Cash only customers always have an advantage in real estate transactions.

The Millenial Way: Better have approached this as a two stage process. The first stage where they get information from the customer, and tell them what products are available for them. This is done by proprietory AI algorithms similar to Spotify’s algorithms to provide personalized music. At the end of this process customers would have a verified pre-approval letter reviewed by an underwriter. Better claim this letter would be available in 24 hours from the time the customer has made the request. The second stage kicks in after the customer has found a property, where the mortgage economics revolves around the property.

Inefficiency #2: The process of choosing the lender involves a lot of variables, however, customers generally go with the lowest overall cost of the mortgage (including various fees, upfront monies and Monthly EMIs) for the best period. They often lack visibility and guidance on what would be better for them, a larger upfront deposit or a larger monthly EMI.

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The Millenial way: Better provide complete transparency in terms of what is good for a particular customer – a higher upfront payment, or higher monthly EMI. This would depend on how long the customer intends to live in the property chosen, which in turn would decide if the break even would occur within that period.

Habito takes an unbiased and a personalised approach to choosing mortgages depending on the customers profile. The AI behind it ensures that customers are at the heart of the mortgage recommendations.

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Inefficiency #3: Mortgages often come with various costs attached to them, which is primarily because there is a person behind the scene trying to sell and close the deal for the lender, and this person needs to get paid. Also, mortgage brokers often sell products that get them better commissions

The Millenial Way: Better mortgage has no hidden costs, and it is completely free of admin charges. Better employs staff who will unblock the mortgage process, and help people through it, rather than sales staff to close deals. Their loan officers never get paid commissions. That’s a much needed change.

Habito charges equivalent fees across all mortgages as AI algorithms don’t have vested interest (yet). This ensures the customer gets the best product suited for his needs, everytime.

Inefficiency #4: Mortgage lenders offer a rate, but very often during or just before the process of the application increase the rates. I know a few friends and colleagues affected by this completely unacceptable approach by Mortgage lenders.

The Millenial Way: Better mortgages offer full transparency throughout the mortgage process. The use of technology to hold all mortgage information centrally, and loan officers who are not incentivised to mis-sell products helps too.

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As a Better customer, you can stay on the mortgage process 24 X 7, all 365 days. If a customer wanted to progress quickly on a property over a weekend (day or night), unlike high street banks, they would be able to get the required approval letters. That truly feels like a Millenial way to Mortgages!!

AI is no human

These are some interesting stories of efficiencies being added to the Mortgage process and business model, through intelligent AI algorithms. However, I firmly believe AI cannot completely replace a human on a Mortgage or an Insurance conversation. If I were going through a home buying process, or an insurance claim for a car accident, I prefer to talk to a human who understands the emotions of the process and treats it with empathy. However, I believe AI can add efficiencies, make the process unbiased, and provide personalised insights through thousands of data points that the human brain can’t cope with. The human in this process will just need to be – humane.

The US mortgage industry is $8.4 Trillion in size, and the top four fintech firms offering mortgages do just about $1 Billion in funding. There is still a long way for these firms to go, but a ground up approach to mortgages, cool technologies, and of course a human touch throughout the process can definitely proivde a happier home buying experience for customers.

Arunkumar Krishnakumar is a Fintech thought-leader and an investor. 

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3 thoughts on “Millennial Mortgages – Can AI deliver a human touch to home lending?

  1. Nice article and thanks for highlighting the inefficiencies with good examples.

    There is no doubt that AI and modern technology can dramatically improve the residential mortgage origination process. Much of the time consuming processes done by loan officers, processors, underwriters and closers can, and will, be automated and improved by AI and intelligent process flow.

    I agree that some level of human involvement will still be needed, but much more on a “counseling” level rather than a hard sales push like today. The key question is what is the right mix?

    We also should not ignore the servicing side (e.g., everything that happens after the loan has been originated). This is still a largely legacy and human-intensive operation, but clearly not as sexy and receives little attention. There are clear use cases around AI and automation to address the inefficiencies and redefine how servicing is done.

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