Tuesday, June 30, 2026
6.30.26 Investor Outlook; Experian’s Likhitha Mahendar Singh on First-Time Home Buyers; Hawkish Versus Dovish
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Today’s episode includes a look at how investors are interpreting policy and volume indicators to make informed decisions. Plus, Robbie interviews Experian’s Likhitha Mahendar Singh how the modern first-time homebuyer has evolved, why rental payment data is reshaping how lenders identify mortgage-ready borrowers, and how a data-driven approach can help better target, underwrite, and serve the next generation of homeowners. And we close with an explainer on why short-term bonds are now subject to volatility from economic data.
Thank you to Experian. From lenders and landlords to employers and consumers, Experian helps connect the housing ecosystem with the data and insights needed to make faster, confident decisions. Lead a smarter housing journey with Experian.
The Chrisman Commentary is your go-to daily mortgage news podcast, where industry insights meet expert analysis. Hosted by Robbie Chrisman, this podcast delivers the latest updates on mortgage rates, capital markets, and the forces shaping the housing finance landscape. Whether you're a seasoned professional or just looking to stay informed, you'll get clear, concise breakdowns of market trends and economic shifts that impact the mortgage world.
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Experian — From lenders and landlords to employers and consumers, Experian helps connect the housing ecosystem with the data and insights needed to make faster, confident decisions. Lead a smarter housing journey with Experian.
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(0:02) Welcome to the Chrisman Commentary Daily Mortgage News Podcast. I'm your host, Robbie Chrisman. (0:09) Topics on today's episode include investors, as it has to do with the recent housing policy (0:16) and what agency mortgage-backed securities have been doing lately, why not everyone shares (0:22) the market's hawkish outlook, and my interview with experienced Lakitha Mahendar Singh to (0:28) talk about how the modern first-time homebuyer has evolved, why rental payment data is reshaping, (0:33) how lenders identify mortgage-related borrowers, and how a data-driven approach can help better (0:38) target, underwrite, and serve the next generation of homeowners.
Here, take a listen to a little preview. (0:44) Rental payment behavior has historically been invisible in traditional mortgage underwriting. (0:49) How can rental payment history help lenders better assess both borrower readiness and (0:53) the future mortgage performance? (0:56) Sure.
This is a topic I feel particularly strongly about because at its heart, it is (1:02) a story of fairness, ensuring that consumers receive credit for the financial responsibility (1:07) they have already demonstrated. Paying rent consistently and on time, month after month, (1:14) is one of the most concrete indicators of financial reliability a consumer can show. (1:19) Yet, for many years, that track record was effectively invisible within traditional mortgage (1:25) underwriting.
Experian has worked to change that in a meaningful way. We were the first (1:32) credit reporting agency to enable positive rental payment reporting, and we operate RentBureau, (1:39) the nation's largest database on rental payment history. As a result, millions of consumers (1:45) now can receive credit recognition for paying their rent on time, which can improve their (1:51) credit visibility and in some cases, expand their access to financing.
By recognizing rental (1:57) payment history within the credit ecosystem, over 6,000 previously unscorable consumers (2:03) became scorable, which means this provides an opportunity to the consumers to expand their (2:10) access to conventional credit. So what does it mean for lenders? It has two important (2:16) implications. First, it helps surface credit-worthy borrowers who might otherwise appear in thin (2:22) file or mere prime on a traditional credit report.
Second, on-time rent payment is genuinely (2:29) predictive of mortgage performance. Consumers with a consistent history of paying rent are (2:34) highly likely to honor their mortgage obligations as well. It is a meaningful signal that (2:40) conventional underwriting frameworks have historically overlooked.
Ultimately, positive (2:46) rent reporting is beneficial for consumers and provides lenders with a more complete, (2:51) accurate picture of individuals they are evaluating. This is a genuine win on both sides of the (2:57) transaction. (3:01) Thanks to this week's podcast sponsor, Experian.
From lenders and landlords to employers and (3:06) consumers, Experian helps connect the housing ecosystem with the data and insights needed (3:11) to make faster, confident decisions. Lead a smarter housing journey with Experian. To (3:17) learn more, visit Experian.com slash mortgage.
(3:23) I decided to play golf with my friend. On the third hole, he said, let's make this (3:27) interesting. So we stopped playing golf.
(3:34) That's, that's not a good joke. How about, how about the woman who said she got stung (3:40) between the second and third hole? The instructor told her her stance was too wide. Anyways, (3:47) we digress.
Every week I receive about a half dozen invitations to mortgage golf events, (3:51) usually centered around a conference. How about coming up with something where you can (3:55) see and talk to more than three other people for four hours? Group hikes, make a bear, mini (4:01) golf, bowling, croquet, pretzel making. Actually, we did that in Frankenmuth at the Michigan (4:07) Mortgage Bankers' Annual Conference last year.
Perhaps we'll see companies and state (4:12) organizations shift their fundraising away from golf outings toward pickleball and bocce (4:17) ball. And along those lines, temperament recently seems to be constructive, pragmatic, and (4:23) people are anxious to learn. It's been nice to see that as we entered the traditional (4:27) lull in conference activity.
I want to talk policy for a second. And by policy, I mean (4:33) the proposed, passed by Congress but unsigned by President Trump, 21st Century Road to Housing (4:38) Act, which aims to curb large institutional ownership of single family homes, but its (4:43) broad and complex exemptions, particularly for build-to-rent projects, age-restricted (4:47) communities, and rehabilitative properties may significantly limit its practical impact (4:52) and leave ample room for investors to adapt their strategies. Meanwhile, the actual investor (4:57) mortgage market remains dominated by smaller landlords rather than large institutions, (5:02) with roughly 1.4 million agency-backed investor loans outstanding, totaling $275 billion, (5:08) heavily concentrated in California, Texas, and Florida.
Since 2023, investor mortgage (5:13) production has remained relatively stable in dollar volume, despite lower loan counts, (5:17) reflecting higher home prices rather than increased activity. From a mortgage performance (5:23) standpoint, investor properties have behaved similarly to second home and owner-occupied (5:27) loans, suggesting limited unique risk. Ultimately, when the legislation could alter how large (5:33) institutional investors structure acquisitions, its effect on housing supply, rental (5:37) availability, and mortgage issuance remains uncertain, especially given the industry's (5:41) ability to adapt within the law's numerous exceptions.
Agency mortgage-backed securities (5:47) and U.S. Treasuries traded quietly to begin the holiday-shortened week, with weakness (5:51) and shorter maturities offset by relative strength in the long bond as investors largely (5:55) stayed on the sidelines amid a lack of economic data and improving sentiment in equity markets. (6:01) Geopolitical uncertainty continues to temper conviction. Absent a clear catalyst, muted (6:06) activity should continue through the rest of the week.
Investors continue to favor (6:11) a cautious wait-and-see approach, gravitating toward the mid-coupon MBS while avoiding higher (6:16) coupons amid expectations for at least one Federal Reserve rate hike by year-end. Overall, (6:21) agency mortgage-backed securities remain attractively valued relative to investment-grade (6:24) corporates. As energy-driven inflation fears recede, markets are increasingly looking to (6:29) June's employment wage and inflation data to determine whether underlying price pressures (6:35) remain persistent enough to justify a restrictive Fed despite easing headline inflation.
(6:41) Markets continue to price at least one rate hike before year-end, but conviction increasingly (6:46) depends on incoming economic data rather than Fed rhetoric. Chair Warsh is expected (6:50) to reinforce the Fed's inflation-first framework in remarks at ECB's Sintra conference this (6:55) week, but his more restrained communications strategy has left short-term Treasury yields (6:59) highly sensitive to each new economic release. (7:02) Not everyone shares the market's hawkish outlook, though.
A growing minority argues (7:07) that falling oil prices, softer consumer spending outside the AI-driven investment boom, continued (7:13) housing weakness, and signs of a gradually cooling labor market—payroll gains have (7:19) averaged about $113,000 a month in 2026, reflecting a declining labor force—point toward disinflation (7:25) rather than renewed inflation, raising the possibility that markets may ultimately have (7:29) to unwind rate-hike expectations if data continues to soften. The question is whether the economy (7:35) is slowing enough to ease inflation pressures without materially weakening overall growth. (7:42) For today's interview, I wanted to welcome to the show experienced Lakeetha Mahendar-Singh (7:46) to talk about how the modern first-time homebuyer has evolved, why rental payment data is reshaping (7:50) how lenders identify mortgage-ready borrowers, and how a data-driven approach can help better (7:55) target, underwrite, and serve the next generation of homeowners.
(7:58) She's a senior scientist with Experian's Housing Business, where she turns complex (8:02) housing data into actionable insights that help stakeholders better understand the broader (8:06) housing ecosystem, including affordability, mortgage readiness, and the path to homeownership. (8:12) Her work spans rental trends, mortgage analytics, renter-to-homebuyer transitions, and the use (8:17) of alternative data to strengthen housing intelligence. (8:20) I'm very pleased to be joined by a fellow young person, and I put that in quotes for (8:24) the mortgage industry, but it's nice to see more and more people under the age of 40 or (8:28) 35 or 30 joining the industry and making waves here.
So I feel like you and I are probably (8:34) both adept to talk first-time homebuyers for the modern age. Who are we really talking (8:39) about when we say first-time homebuyers? I've heard some chatter out there that maybe the (8:45) median age has lifted up closer to 40 for first-time homebuyers, but when you think (8:49) about the first-time homebuyer of today, how has that changed from the traditional profile (8:53) of a young renter buying a starter home? (8:56) Sure. To answer that well, we need to set aside a longstanding assumption.
The traditional (9:02) image of first-time homebuyer was a renter in their mid-20s stretching to afford a modest (9:07) starter home, but it no longer reflects the reality of today's market. That profile has (9:13) shifted considerably. So the data from our experienced first-time homebuyer study illustrates (9:18) this very clearly.
In 2023, 44% of first-time homebuyers were 35 years of age or younger, (9:26) but in 2026, that share has declined to 37%, which is a meaningful generational shift within (9:34) just three years. Today's first-time homebuyer is more likely to be in their mid-to-late 30s (9:42) by the time they reach the closing table. It is important to know that this shift does not (9:47) reflect a loss of interest in homeownership among young consumers.
Rather, affordability (9:53) constraint has extended the path to ownership for many. Rising rents, student debt obligations, (10:01) elevated home prices, persistent mortgage rates, and increasing costs for taxes, insurance, (10:07) and HOA fees have made it more difficult for people to reach readiness at an early age. (10:13) That said, the opportunity for lenders remains substantial.
At Experian, we define first-time (10:20) homebuyers as a consumer with no active first mortgage and no homeowner-occupied residential (10:26) property match. So beginning with approximately 100 million non-homeowners in the U.S. and applying (10:33) filters for credit readiness, income, front-end EDI, back-end EDI, we found that there are (10:39) approximately 8 million financially qualified actionable first-time buyers today. We also see (10:47) that 71% of first-time homebuyers are purchasing single-family homes, with condos and townhomes (10:54) making up much of the remaining activity, where condo purchases have declined over the past three (11:01) years.
And that likely reflects increased consumer sensitivity to HOA fees, total monthly housing (11:08) costs, etc. The demand is clearly there. The real question for lenders is, how do you identify (11:15) and engage these buyers earlier before a competitor does? (11:20) So given that today's first-time buyers are entering the market later, (11:24) and I would add navigating greater affordability challenges, is the real issue finding demand, (11:29) or is it using better data to identify renters who are genuinely ready to make the transition? (11:35) That's a great point, and it actually connects to the challenges lenders face today, (11:40) which is not the lack of demand, but it is the conversion.
More specifically, it is the ability (11:47) to distinguish mortgage-ready renters from the broader renter population, which requires the (11:53) more sophisticated approach. Many lenders that we see today continue to rely on broad demographic (12:00) based first-time homebuyer campaigns that are segmented by age or geography. While this is (12:06) understandable, this approach often results in significant missed opportunity, both in terms of (12:13) qualified buyers who are never reached and the marketing investment that does not convert.
(12:19) A more effective strategy would be in involving layers of data signals to identify who is (12:25) genuinely ready to act right now. That means looking at income trajectory, credit profile, (12:31) debt-to-income, local affordability indicators, including escrow and HOA costs, (12:38) rental activity, and in-the-market model scores that can help identify consumers who are likely (12:44) to open a mortgage or a specific account type in a defined time window. When lenders use this (12:51) strategy to combine inputs thoughtfully, the approach shifts from changing a broad demographic (12:58) to identifying specific individuals at the right moment in their journey.
(13:03) That precision and strategy is where competitive differentiation becomes possible today. (13:08) I'm wondering what insights today's renter population offers about future homeownership (13:14) demand. And maybe this is the best time ever to ask this question because we can do more (13:19) with data today with artificial intelligence in the ways that it's being processed than ever.
(13:25) So what have we learned about future homeownership demand based on renter population? (13:29) Absolutely. Speaking of data, rental data gives lenders an early view into future (13:36) first-time home buyers' pipeline. It not only tells us who is renting today, but it also tells (13:43) us who may have the credit foundation, income profile, and financial behavior to become a (13:49) homeowner tomorrow.
We have some stats that our state of rental report discusses. The average (13:57) renter household income is approximately 52,000, and about 61% of the renters fall into low-to-moderate (14:06) income category. Yet one thing to pay attention is that 44% of all renters are prime or better (14:14) credit scores.
This is important insight for lenders, and you may ask why. It's mainly because (14:20) there is a meaningful credit quality within the renter population. These consumers should not be (14:26) viewed as a low-quality segment.
In fact, they are potential future homeowners who may simply need (14:32) the right timing, product, education, or affordability support. Also, the division that the rent burden (14:40) is causing in today's market is significant. Low-to-moderate income renters are allocating (14:46) 56% of their income to rent in comparison to 34% of non-low-to-moderate income renters.
(14:54) That gap tells a very important story. Many renters are not financially undisciplined. (15:04) They are operating in a market where rent consumes so much of the monthly income that it becomes (15:10) difficult to save for down payment, reducing their debt, or build financial cushion that is (15:16) needed for homeownership.
The rental data that we have empowers lenders to segment the renter (15:22) population in a more meaningful way, such as those who are ready to pursue homeownership now, (15:30) those who may need structured assistance such as down payment programs or total cost of (15:35) homeownership guidance, and the third segment would be the ones who would benefit from (15:40) preparation timelines. The ability to identify which category a given consumer falls into will (15:47) allow lenders to engage with relevance and appropriate timing, which is a far more (15:52) effective approach than treating the renter population as a uniform audience today. (15:58) So my sister is actually going through looking at homes and putting offers in on homes, and so (16:05) it's very easy for the younger generation, I've been talking with her about this, it's very easy (16:09) to stretch your wallet when maybe you shouldn't.
Maximize your GTI and say you're renting before (16:14) now your monthly payment has probably shot up and that can be a huge shock. And I'm wondering if (16:20) there's a way for lenders to identify when a renter is genuinely prepared to transition into (16:25) homeownership without taking on an unmanageable level of payment shock, or just what we're seeing (16:31) in terms of kind of the data as being predictive when it comes to that. Sure, this is where the (16:37) data and the analysis become particularly actionable for lenders.
One of the most valuable (16:44) findings that we have had from our research is what we refer to as the comfort zone. So this is (16:50) basically a framework that allows lenders to assess both transition readiness and performance (16:56) risk in a single view. So what do I mean by comfort zone? So we define it as the situation where a (17:03) borrower's projected mortgage payment falls approximately within 1.25 to 1.75 times that (17:11) prior rent amount.
Within that range, delinquency rates remain relatively low and buyer participation (17:18) is meaningfully higher. It represents the point where the payment increase is real, (17:24) but it is also proportionate to consumers affordability metrics. As per the study that (17:29) we did on state of rental report, renters who transitioned to homeownership had an average (17:35) rent to income ratio of 25% which underscores affordability as a prerequisite to exit.
For (17:43) lenders, this means that rent payment tracking serves a purpose well beyond consumer advocacy. (17:49) It is a practical data-driven tool for identifying which applications are well positioned for a (17:55) successful transition into homeownership and which individuals may benefit from a different product (18:00) structure or additional preparation time. When paired with positive rent reporting, (18:06) lenders can gain a substantially more informed view of the readiness, the affordability picture, (18:12) and the long-time performance potential of a consumer.
(18:17) And ultimately, for lenders out there looking to differentiate, what does a data-driven (18:21) first-time buyer strategy look like in practice? And I would add to that, (18:26) how does data evolve from a risk tool into a true competitive advantage? (18:31) Yeah, so we all know that this is a super competitive market and the advantage goes to (18:37) the one with the most precise view of who is ready to transition into homeownership, (18:42) where they are, what they need, basically the quality of the data behind it. (18:47) So let me give an example to illustrate what that looks like in practice. (18:52) Consider a real example we refer to as a tale of two cities.
Looking at two zip codes within Houston, (18:58) Texas, experience data reveals a striking contrast in affordability. In Hedwig Village, (19:05) the average home price is just under $1 million with a $6,000 monthly mortgage payment (19:10) and approximately 12 miles away in West Houston, the home prices drops to $589,000 (19:18) and the monthly mortgage payment is $3,200, like approximately half. (19:24) Same city, same broad campaign, but entirely different levels of first-time home buyers (19:29) readiness profile.
That is the power experience brings. It provides us visibility into the (19:35) complete picture, drilling down to the local affordability level. So when we combine this (19:43) hyper local affordability data, including escrow, HOA estimates, rent payment activity, (19:50) credit profiles, and income signals, we help lenders build precise actionable prospect segments.
(19:58) When lenders can use this information, they can engage each of those segments with a targeted (20:05) appropriate message. They move from broad awareness campaigns to meaningful conversations. (20:11) This result is not simply more first-time home buyers volume, but it is better matched borrowers (20:17) and improved pull-through rates.
That is how experience data transforms from a risk management (20:23) input into a true competitive advantage, one that helps lenders grow their business (20:29) while helping more consumers achieve the milestone of home ownership. (20:34) The opportunity is real. The data is available.
The question is how effectively we put it all (20:41) together and walk together. Certainly a ton of valuable insights, (20:46) Lakita. I really appreciate the time.
It's exciting to hear from you on this subject and hopefully (20:52) it brought some good awareness and insights people in the industry that were listening. (20:57) Thank you very much. Thanks, Robby.
Delightful to be a part of this. Thank you. (21:04) Today's economic calendar has April house price indices from FHFA and S&PK Shiller.
(21:09) Those will be followed by June Chicago PMI and June consumer confidence. Consumer confidence (21:15) is forecast to rise on the month's declining gas prices and inflation expectations should fall. (21:20) Good tidings for the rest of the summer travel season.
Tuesday starts with agency MBS prices (21:26) relatively unchanged from yesterday's close. The two-year yielding 4.10 and the 10-year (21:32) yielding 4.37 after closing yesterday at 4.37%. Let's wrap up with a joke and some housekeeping. (21:42) How to sing the blues, a primer, part two.
Teenagers can't sing the blues. They ain't (21:48) fixing to die yet. Adults sing the blues.
In blues, adulthood means being old enough to get (21:54) the electric chair if you shoot a man in Memphis. Blues can take place in New York City, but not (22:00) in Hawaii or any place in Canada. Hard times in Minneapolis or Seattle is probably just (22:05) clinical depression.
Chicago, St. Louis, Kansas City are still the best places to have the blues. (22:13) You cannot have the blues in any place that don't get rain. A man with male pattern baldness ain't (22:20) the blues.
A woman with male pattern baldness is. Breaking your leg because you were skiing is not (22:26) the blues. Breaking your leg because an alligator be chomping on it is.
You can't have no blues in (22:32) an office or a shopping mall. The lighting is wrong. Go outside to the parking lot or sit by the dumpster.
(22:38) Good places for the blues, a highway, a jailhouse, empty bed or bottom of a whiskey glass. Bad places (22:45) for the blues, Nordstrom's, gallery openings, Ivy League institutions and golf courses. Nice to see (22:52) this episode come full circle.
(22:58) Thanks again to Experian for sponsoring today's podcast. From lenders and landlords to employers (23:04) and consumers, Experian helps connect the housing ecosystem with the data and insights needed to make (23:09) faster, confident decisions. To learn more, visit Experian.com slash mortgage and lead a smarter (23:16) housing journey with Experian.