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How AI Could Simplify the Mortgage Market

August 10, 2026
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How AI Could Simplify the Mortgage Market

August 10, 2026

Our U.S. Consumer Finance Analyst Jeff Adelson and our Co-Head of Securitized Product Research Jay Bacow explain why AI can transform the way Americans shop for, manage and refinance their mortgages.

Morgan Stanley Thoughts on the Market Podcast

Transcript

Jeff Adelson: Welcome to Thoughts on the Market. I'm Jeff Adelson, Morgan Stanley's U.S. Consumer Finance Analyst.

 

Jay Bacow: And I'm Jay Bacow, Co-Head of Securitized Products Research, also working at Morgan Stanley.

 

Jeff Adelson: Today, how AI could change the way Americans shop for, manage, and refinance their mortgages.

 

It's Monday, August 10th at 10am in New York.

 

The U.S. mortgage market is worth more than $14 trillion, and its performance ultimately depends on the choices millions of homeowners make. Today, refinancing still means shopping around, comparing offers, and working through a lot of paperwork. AI could make that process much easier, especially when rates begin to fall.

 

Jay, you led this work on our AI mortgage blue paper. What's the main way AI could change the mortgage market, and why does the borrower matter so much?

 

Jay Bacow: So we think the biggest change would be borrower adoption of using AI agents to manage their personal finance. An agent on your phone could just monitor mortgage rates, compare lenders, reduce the paperwork, and make homeowners more likely to refinance when the economics work.

 

Let's think about what that could be. Historically, only about 30 percent of borrowers that had the ability to lower their mortgage rate by a 100 basis points did so in a given year. When a borrower went to get a mortgage quote, less than half of them asked more than one lender for a quote.

 

That agent could go reach out to 30 lenders, ask for a variety of different mortgages, could upload all the documents, could do this all effectively instantaneously, present the homeowner with the best option. Allow the homeowner to effectively click a button and refinance. I think this could be pretty transformative for the mortgage market.

 

Jeff Adelson: Now, as we think about this transformation, Jay, mortgage investors still rely heavily on past refinancing behavior trends. If AI makes borrowers more likely to refi[nance] when rates fall, how could that change the way these investors value mortgage-backed securities?

 

Jay Bacow: Well, we all know that past performance is not indicative of future performance, and those models are likely to understate future prepayments. If you get a faster response, it's going to make mortgages more negatively convex.

 

That's going to make the durations shorten. It's likely to widen mortgage spreads by about 10 basis points in our base case. And now, if that base case were to happen and we get, let's call it 100 basis point rally in the future, we think that that could cause something like a 40 percent pickup in refinance volumes versus our current expectations of what refinance volumes would look like in that 100 basis point rally.

 

Jeff, you cover a lot of the largest mortgage lenders. What does this mean for their business model?

 

Jeff Adelson: So, it's pretty straightforward. More borrowers refinancing means more loans for the industry to originate. Today, we're still sitting below what I would describe as normalized levels of originations.

 

We're sitting at about $2 trillion of mortgage originations per year. As we think about normalized, we think that's somewhere in the order [of] around $2.5 trillion. So just that $600 billion alone could get us straight there.

 

We tend to think about this more in our bull case, where we could see something in the order of $3 trillion of originations or more, still below what we saw during the peak COVID years of about $4 trillion or more. But still pretty meaningful and material for the industry.

 

Now, for the scaled lenders, that can create meaningful operating leverage. Mortgage companies have historically had to hire aggressively when volumes rise, and then they've had to reduce headcount when the cycle turns. AI could allow them to process more loans with the same employee base, making their cost structures more flexible and reducing the need to rebuild capacity during every single refi[nance] wave.

 

But the earnings benefit we don't think will necessarily match the dollar benefit from volumes. If AI makes it easier for borrowers to compare offers and allows every lender to process more loans, then competition could intensify and pressure gain on sale margins. So the opportunity is a larger market and better productivity.

 

The key question for individual lenders is: how much of that volume can they capture without giving too much back through pricing?

 

Now, as we think about automation, Jay, it could bring in more loans, but could also intensify competition and reduce the profit lenders can earn when they originate and sell a mortgage. So, how should investors in your space weigh those two effects?

 

Jay Bacow: So, the mortgage investors are short the option to the mortgage homeowner of when they can refinance.

 

And if the mortgage homeowner is going to be more efficient about refinancing, the mortgage investor is going to need to get paid more for that. They're going to demand wider spreads, and they're particularly going to demand wider spreads where that option that they're shorting is worth more. That's generally how it's going to play out, but there's also other aspects as well.

 

That duration shortening, because the borrower's more likely to refinance, means that the investors that own that duration will need to buy some more duration against that. You're also going to see more demand for duration as rates rally. So it's going to be a bid for the low strike receivers, as our options experts will pay close attention to.

 

And then if we get a further rally, you also get a more of an impact across the consumer writ large. You can imagine a world where mortgage rates are substantially lower than they are right now. An agent could sit there and say, "Why don't you consolidate your debt between your credit card, your auto loan payments, maybe your student loan payments and your mortgage?" Allowing consumers to save more and then maybe spend that in the economy.

 

Jeff Adelson: If we maybe take it a step beyond refinancing, how could AI affect home sales, homeownership, and access to home equity?

 

Jay Bacow: So let's just go back to thinking about this agent that's on your phone that's looking at all the opportunities.

 

Traditionally, right now, most people are only calling up one lender, they're getting one quote. If your agent is looking at lots of different lenders and lots of different options, you're probably going to get more ability to take out a mortgage. So you're going to get an expansion of the homeownership rate.

 

That's going to create more demand for housing. As rates rally, you're going to get home sale activity picks up more than it used to, and people are also going to be more able to take advantage of the equity they have in their house. So, you're going to get more usage of second liens and HELOCs and cash-out refinance activity.

 

Once again, we think this is mostly going to happen three to five years down the road, but we're not really sure exactly how this is going to play out.

 

So Jeff, what would be some of the signs that people could look at to see if it's playing out in the three to five-year timeline that we're expecting – or slower, maybe even faster?

 

Jeff Adelson: Sure. So yeah, I mean, I think it's going to be similar to what we've already observed as consumers ourselves and what we're seeing with all the LLMs and AI tools we're adopting today. You should see some rapid advances in the ease of use and the adoption of these technologies from a forward-facing, client-facing perspective. What we all see in the websites, what we all see in the apps.

 

It should become easier for us to engage with the mortgage process, compare rates to actually step into the process. Whereas today, you still need to maybe speak with a bank officer, a loan officer, or a mortgage broker to get deeper into the process and actually better understand what your rate means today.

 

So that would be the first step. The second step would be closing speeds. The average originator today still takes about 40 to 45 days to close a mortgage. The biggest and largest originators that have invested the most in technology and AI today are closing at about, call it, 12 to 20 days. So, half the industry level. So, that should come down over time and make it much easier to actually apply and finish a mortgage.

 

And then quite frankly, the most obvious answer would just be at the given level of rates that are outstanding today, we should see a step up in the level of refi[nance] volumes. That would be the most obvious one. But that'll be the outcome of everything else we've talked about rather than the actual cause.

 

Jay Bacow: That makes sense. So faster refinancing, it's likely to make the mortgage market more responsive when rates fall and effects that are going to reach well beyond the borrower.

 

Jeff Adelson: That could mean higher volumes for lenders, quicker prepayments for investors, and wider swings across housing and rates markets.

 

Jay Bacow: Jeff, thanks for taking the time to talk.

 

Jeff Adelson: Great speaking with you, Jay.

 

Jay Bacow: And thank you all for listening. If you enjoy Thoughts on the Market, please leave us a review wherever you listen and share the podcast with a friend or colleague today.

Hosted By
  • Jeff Adelson
  • Jay Bacow

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August 7, 2026

AI’s New Rules of Engagement

Our Head of U.S. Public Policy Research Ariana Salvatore explains how U.S.-China tensions, export...

Transcript

Ariana Salvatore: Welcome to Thoughts on the Market. I'm Ariana Salvatore, Head of U.S. Public Policy Research at Morgan Stanley.

 

Today, a look at how government is increasingly determining the future of AI in the U.S. – from where it's built to which technologies US companies and consumers can use.

 

It's Friday, August 7th at 10am in New York.

 

AI is rapidly reshaping the economy and society, so this is a pivotal moment for government to consider the rules governing that development. The first area to watch is technology restrictions, particularly in the context of U.S.-China competition.

 

Now, for much of the past decade, the government's approach has been to restrict a relatively narrow group of technologies with clear national security implications while maintaining broader commercial ties. But as export controls spread across more sectors of the economy and AI moves from software into physical infrastructure, the definition of what qualifies as national security has become broader.

 

The Department of Commerce could, for example, expand the entity list. That would require US cloud providers, software companies, and model marketplaces to remove or stop supporting models tied to designated Chinese developers.

 

Congress could then make those restrictions more durable through things like the annual defense bill or other policy vehicles. We're keeping an eye on several legislative proposals, like the AI Overwatch Act, which would tighten controls and give congressional oversight around exports of the most advanced AI chips; and the MATCH Act, which would extend restrictions further upstream to semiconductor manufacturing equipment and seek closer alignment with allied producers.

 

These measures wouldn't directly ban Americans from using a Chinese model, but they could constrain China's ability to train future frontier systems.

 

But it's not just the US that could impose a set of restrictions. China has a parallel set of tools focused more on integration and market access. Regulators could block four models or APIs. They could require locally controlled deployment. They could impose Chinese data and content standards or use cybersecurity and entity list authorities to promote domestic substitutes.

 

The likely result is an increasingly distinct pair of AI ecosystems. That's our two worlds thesis in practice. Over time, we think that means a bifurcated global AI market into separate technology ecosystems.

 

That looks like the U.S. relying on export controls, allied supply chains, and largely closed frontier model platforms, while China emphasizes domestic hardware, open-weight models, subsidized compute, and localization. Over time, that bifurcation could produce different chips, models, standards, data rules, and distribution channels, while third countries navigate between the competing stacks.

 

The second area to watch is domestic regulation. Today, the landscape is pretty fragmented. States are moving first on certain specific issues, including automated decision-making and child safety. Now, at the same time, Congress is confronting competing objectives from industry, consumer groups, and national security officials.

 

So far, we think the evidence suggests that the administration's preference is for a light-touch approach, a largely voluntary national framework rather than a broad new licensing regime. But it's also moving toward more direct oversight of the most advanced models. That includes the possibility to play a more active role prior to model release to ensure that certain protections like cybersecurity and intellectual property are met.

 

Publicly outlined priorities from industry seem to broadly overlap with that approach: a consistent federal framework, clearer liability standards, access to data, compute, and power, and copyright rules that don't materially limit model training.

 

But of course, the industry isn't monolithic. There are some important nuances between frontier developers and other players.

 

So, what does all this mean for investors? The government's reaction function will be critical to the way AI is developed and diffused throughout our society in two key ways.

 

First, we see regulation altering not only the pace, but also the geography of AI infrastructure.

 

At the same time, we think these constraints could strengthen the investment case for bottleneck solutions like on-site power generation, fuel cells, storage, and more.

 

Second, greater technology bifurcation supports investment in parallel supply chains.

 

The key takeaway here is that the government is no longer simply regulating the industry from the sidelines. It's helping to determine how fast AI develops through domestic rules, where it develops through infrastructure, permitting, and sovereign AI policy, and which technologies are accessible through export controls and market access restrictions.

 

Thanks for listening. If you enjoy the show, please leave us a review wherever you listen and share Thoughts on the Market with a friend or colleague today.

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August 6, 2026

Why Brick and Mortar Banking Still Matters

America’s biggest banks are opening more local branches. Our Head of U.S. Large Cap and Mid Cap Ba...

Transcript

Manan Gosalia: Welcome to Thoughts on the Market. I'm Manan Gosalia, Morgan Stanley's Head of US Large Cap and Mid Cap Banks Research.

 

Today: why the bank branch you pass on your commute may matter more than you think.

 

It's Thursday, August 6th at 10am in New York.

 

When was the last time you went to your bank? You probably do most of your daily banking online and maybe go to the local branch for occasional transactions, like getting a certified check or talking to a financial advisor.

 

So, you might think that bank branches are fading into the background. But America's biggest banks are actually accelerating their investments in physical locations.

 

That shift could reshape the competition for your deposits. In our research, we looked at where 12 large U.S. banks are expanding their footprints, and we identified 57 target markets. 34 of those markets are being pursued by multiple banks, and nine of those markets are being pursued by five or more banks.

Since mid 2025, about 80 percent of these banks' new branches have opened in those markets. Most of the expansion is happening in the Southeast and Texas, with additional activity in the Midwest and several major metropolitan areas. 95 percent of the target markets have either above median projected population growth or they have ranked in the top 10 percent for deposit growth.

 

That helps explain why Nashville and Atlanta are each targeted by seven of the banks, while Miami, Dallas, and Denver are targeted by six. These are places where households and businesses are growing and where banks see an opportunity to build relationships that could last for decades.

 

The central question is whether physical branches still attract deposits. The evidence suggests that they do. From 2022 to 2025, 90 percent of the time when a large bank increased their branch share in the market, their deposit share also increased. But to become a real contender, a few scattered branches are not enough.

 

Banks generally need at least a mid-single-digit share of local branches to compete effectively. At 10 percent or more branch share, deposit share exceeds branch share by a median 3.5 percentage points. So, density, not just presence, is what matters.

 

Most large banks that we looked at have not reached that level. 60 percent of their positions in expansion markets remain below 5 percent market share. And so, this build-out looks like the beginning of a long competitive cycle.

 

Even then, the pressure is already visible in what banks are paying for deposits now. The highest offered retail certificate of deposit rates are higher in the South compared to the Northeast. Higher rates do make deposits more expensive for banks to fund.

 

In fact, evidence from the recent earnings reports suggest that this may already be happening. And we expect higher funding and branch costs to pressure bank margins and lift expenses into 2027. This means the cost of gathering core deposits could move structurally higher. And the lesson is surprisingly old school.

 

You can do almost everything on an app, but a branch on the corner still carries weight.

 

Thanks for listening. If you enjoy the show, please leave us a review wherever you listen and share Thoughts on the Market with a friend or colleague today.

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