- 2 days ago
As consumers are entering the home buying journey, their rental history reveals more than just where they lived—it uncovers critical insights into affordability, credit behavior, and financial readiness. In this session, we’ll explore how Rent Bureau Data and Observed Data can help mortgage lenders and marketers optimize lead generation and reduce costs.
Learn how rental payment patterns correlate with income, credit improvement, and mortgage risk—and how to use these insights to target the right consumers at the right time. Discover how Experian’s suite of verification tools can streamline pre-qualification and closing, while keeping your budget in check.
Learn how rental payment patterns correlate with income, credit improvement, and mortgage risk—and how to use these insights to target the right consumers at the right time. Discover how Experian’s suite of verification tools can streamline pre-qualification and closing, while keeping your budget in check.
Category
📚
LearningTranscript
00:00Okay. All right. Well, let's go ahead and get started. Welcome, everyone, and thank you for joining our webinar. We are ready to start. My name is Zeblo. I'm the Senior Director of the Content Studio here at Housing Wire, and our webinar today is Rethinking Mortgage Lead Strategy, How Alternative Data Sources Can Predict Income, Risk, and Readiness, Presented by Experian.
00:24So before we dive in, there are a few housekeeping notes. This is meant to be an interactive webinar, and we want to hear from you. So we will be hosting a Q&A towards the end, but in the meantime, you can submit questions at any time using the chat. There will be polls. We encourage you to interact with the polls and give us some feedback, give us your information.
00:45Also, a recording of today's sessions will be sent to all the registrants later this week, so no need to worry. If you missed something, no need to have a pencil out, to be taking notes. We'll send you everything that you need.
01:00Today, we are joined by our panelists, both Joy Mina, the Director of the Product Commercialization of our Ad Experian, excuse me, and Ted Wenzel, the Senior Product Marketing Manager at Experian.
01:13Joy and Ted, you guys ready to roll?
01:15Let's go.
01:16All right.
01:17Let's do it.
01:18Next slide, please.
01:21Next slide.
01:23And, yeah, why don't we dive in?
01:26Before we begin, let's start with a quick poll.
01:30We'd love to hear from you.
01:31This is important information.
01:33How often do you find yourself double paying for an employment record?
01:37Please answer the poll, and then we'll share the results as soon as everybody's gotten their answer in.
01:45Absolutely.
01:46When we say double pay for an employment record, we mean, you know, for a given consumer, same transaction.
01:54You're going to different verifications providers, trying to get verified income from your employment,
02:02and you happen to get the same record from multiple, and you happen to pay for it more than once.
02:09Great.
02:10Looks like results are in.
02:11Thank you, everybody.
02:15Then we have another poll.
02:17Seb, can you go to the next poll?
02:18Which consumer behavior do you believe most strongly predicts readiness to open a mortgage product?
02:27Think about income stability, rent-to-income ratios, and employment history.
02:33We'll give you some time to answer.
02:37All right.
02:38Why don't we head up to the next page, please, Seb?
02:42We'll get started.
02:43So, according to recent MBA's Research Insights Quarterly, mortgage origination costs continue to climb,
02:50averaging between 2% to 5% of the loan amount.
02:53This reinforces the need to rethink your early-stage strategies.
02:57Relying solely on verified data at the top of the funnel or other types of data is increasingly getting cost-prohibitive.
03:03By incorporating alternative data sources earlier in the process, lenders can reduce acquisition costs,
03:10improve targeting efficiency, and preserve margins in a high-cost environment.
03:16Next page.
03:20Every stage, as you know, every stage of the mortgage journey adds costs.
03:24And with about 30% to 50% of consumers dropping out before closing,
03:29filling your pipeline with qualified borrows is critical.
03:33Upfront smart prospecting saves time and money,
03:37especially when consumers aren't charged early on or fail to close.
03:41This high fallout rate also highlights the need for cost-effective lead qualification strategies.
03:48Next slide, please.
03:51But you can arm yourself with data.
03:53In fact, you need data at every stage of the consumer journey to ensure that a loan closes properly.
03:59And not all data is created equal.
04:01From stated to verified, each has its own place.
04:05We recently introduced a proprietary offering called Experian Observed Data.
04:10It takes inputs from many sources, including creditors, property managers, and others.
04:16This type of data actually starts out as consumer-stated data,
04:20but is substantiated by third-party creditors who have originated lending products
04:25and report on the performance of these products.
04:28Think of it as substantiated data points over time that are sourced from different third parties
04:34and can be overlaid to give a holistic view of the consumer.
04:37Even before getting verified data, you can have a preview of the consumer's employment and income data
04:43with Experian Observed data.
04:47With this data, early in the process, you can better segment prospects, reduce risk, reduce fallout,
04:54by focusing on applicants that have high chance of success.
04:58This type of data is ideal for screening and segmentation, as I mentioned,
05:02while verified data remains essential for decisioning at later stages in the consumer journey.
05:08Next slide, please.
05:11Choosing the right data means balancing multiple variables, including accuracy, compliance, coverage,
05:19cost, speed, and, of course, trustworthiness.
05:24Next slide, please.
05:26Let's take a closer look at Experian Verify versus Experian Observed data.
05:31You use verified data when you need to decision or you need to be able to adverse action.
05:37Verify data is directly from the source, whether that be the employer or the payroll provider.
05:44On the other hand, you use observed data when decisioning is not required.
05:49It can be used to segment a wide spectrum of prospects for better targeting and really specific messaging.
05:56This data is not adverse action.
05:58We're currently working on leveraging rent bureau data from Experian as a source for observed data.
06:05This type of data can offer deeper insights about your mortgage prospects or loan prospects,
06:10depending on where you're from, and their behaviors.
06:14Observed data is not necessarily a replacement for verified data,
06:17but it can be used earlier on in the consumer journey to optimize your pipeline and your expenses.
06:23You can start flagging risk.
06:26I would call that out as well.
06:27Yeah, good point.
06:29Next slide, please.
06:32As we all know, the use of mortgage trigger leads is going away in March 2026,
06:37so you'll need new strategies for lead generation.
06:40Experian Rent Bureau data offers an alternative option,
06:44leveraging verified rental payment history to identify qualified prospects.
06:48Experian Rent Bureau is actually the largest and most widely used rental payment database in North America.
06:54It includes over 36 million profiles, furnished by over 10,000 property management companies
07:02and third-party rent reporters.
07:05Next slide.
07:07Having said that, you can leverage different types of data at different stages of the consumer mortgage journey
07:13to optimize your lead generation strategy and move more borrowers to closing more efficiently.
07:21Next slide.
07:24For example, let's take a look at some Rent Bureau data.
07:27Rent Bureau data can signal annual income.
07:30While verified income data may be cost-prohibited at the lead generation stage,
07:34you can arrive at the same conclusion by looking at Experian Rent Bureau data.
07:40In this slide, we overlaid Rent Bureau data.
07:42Specifically, a consumer's annual rent with three Experian income sources,
07:47modeled income, stated income, and payroll income, to uncover additional insights.
07:53And what we found is that annual income can be extrapolated from rental data.
07:57A consumer's annual rent can help predict their income.
08:01Across all three income sets, we found that the income value on these consumers
08:06was typically showing that their income value was equivalent to three times their annual rental payments,
08:11taken from rental bureaus.
08:13So there's a high correlation there.
08:16If I can add to that, Ted.
08:18Please.
08:19What's really interesting is the correlation is consistent across the different data sets.
08:25But what we'd love to share with this audience here is,
08:29in pouring this type of data into Experian XRF data,
08:33what we're able to do is dig significantly deeper than what's shown here.
08:38You know, I think we can all understand that income roughly three times rent seems like a sensible thing,
08:46but how is that going to be useful for a mortgage lender or a tenant screener in a way that's helpful?
08:53So what we're looking at with experience, getting that data down to, you know,
08:59let's go to the state level, let's go to the county level, let's go to the ZIF level,
09:04and really give insights that consumers in that specific region,
09:09maybe their rent-to-income ratio, instead of, you know, averaging at three times,
09:16we can say with confidence is, you know, 2.8 times or four times or, you know, three and a half.
09:25And by being able to give you that level of insight at a lower cost earlier on,
09:32to Ted's point, you can make smarter segmentation decisions
09:36versus using kind of one-size-fits-all, you know, blanket estimates.
09:42Yeah, there are definitely regional differences in housing costs,
09:45just West Coast, Northeast, Midwest.
09:48So next slide, please.
09:51Another way to use rent bureau data is that many buyers are comfortable with mortgage payments
09:56that are about 25 to 75% higher than their comparable rent.
10:02And this is possibly due to long-term equity benefits or just market conditions or regionality,
10:07as Joy mentioned.
10:08If you look at the chart, lower mortgage-to-rent ratios, those less than 0.25%,
10:14show higher delinquency rates.
10:16And a low mortgage doesn't always mean financial health.
10:19It can mask underlying vulnerabilities such as low income, high non-housing expenses,
10:25or unstable financial conditions.
10:29Beyond, on the other hand, beyond a ratio higher than three,
10:33the delinquency rate begins to rise again.
10:35And this is possibly reflecting over-leveraging or affordability issues.
10:41The most stable range lies between a rate of 1.25 to 1.75.
10:48And this is where delinquency rates are relatively low and buyer participation is high.
10:54This is what we call the affordability sweet spot.
10:58Next slide, please.
10:59Looking at consumers' rental history can also offer insights to their future mortgage payment behavior.
11:07Using RENT Bureau data, we found that consumers with more than two late rental payments
11:12have four times more first mortgage delinquency rates.
11:16This type of data can help you better segment prospects
11:19who are less likely to default on their mortgage payments.
11:24Next slide, please.
11:25And finally, when consumers have verified income tenure on more than six months,
11:31we found they were two times more likely to apply and get approved for a mortgage.
11:36It could be a first, second, HELOC, or other type of loan.
11:39When consumers start to hit that comfortable period in their employment,
11:43they start to feel more comfortable with longer-term spends on big loans,
11:47such as mortgage or an auto loan.
11:50Data points like this can help you target the right consumers in your marketing funnel
11:54and become more focused in your approach when prioritizing your approval process.
11:59Next, I'll hand it over to Joy to share more about our Verify data offering from Experian Verify.
12:06Wonderful.
12:06Thank you so much, Ted.
12:10Yes.
12:11Sorry.
12:11Can you start a ride?
12:12Turn up on the mic.
12:13Oh.
12:14Okay.
12:15Thank you, Zev.
12:16All right.
12:17So let me just take a step back.
12:21So Ted just walked you through what are all the alternative data sources that can be used earlier on in the process
12:29to help you better segment your interests of consumers.
12:34What I would like to talk about is once you've had that consumer population narrowed down to those who are ready,
12:43and you are ready to either decision or underwrite, what are the best ways to get verified data,
12:49and how you can do that in a way that is smarter, more cost-effective, gives you more flexibility,
12:58and allows you to have a bit more control in your process.
13:03You know, I think our theme here today is wanting to arm you with as many tools as possible to find out information
13:12about consumers earlier on, having a more holistic view, and ultimately you deciding when and where in your process,
13:20getting those data points would be most valuable.
13:23So if we can go to the next slide, please.
13:25Okay, so I would hope that everyone on this call is familiar with verified data as a whole.
13:34You know, in the industry, you have instant verifications, consumer permission verifications,
13:41and research verifications or manual verifications.
13:44At Experian, we have our Experian Verify portfolio, which covers all of those.
13:49Our portfolio is available through many different partners and platforms in the market,
13:57whether it be ICE or Xactis or others.
14:00Here's just a sampling.
14:02If you happen to have a platform of interest, you know, please let us know if you'd like to get our products through that.
14:08Happy to talk to you there.
14:10But ultimately, trying to make it as easy as possible for you to access verified information
14:16from whatever LOS you're using.
14:19And looking ahead, we're targeting more POS systems as well.
14:26So if we can go to the next slide, Zip.
14:30So when Ted earlier said, you know, verified data comes directly from the source,
14:35whether it be employers or payroll providers,
14:38here at Experian, we have a business dedicated to offering employer services directly to employers.
14:45And as part of that, we contract directly with the employer and get access to verified income employment data.
14:54And we tend to kind of cut across all market segments, all geographic segments,
15:00trying to get as diversified as a view of consumers as possible.
15:08Ultimately, understanding that consumers in all industries or employment types do need to have their income verified at some point.
15:17So if we can go to the next slide.
15:19Focusing primarily on instant verifications, this being, if you request a verification from Experian,
15:32we return a response in seconds.
15:34The Experian Verify instant product currently offers over 60 million active records.
15:41So that's active employment records that are consumers who are actively working and receiving pay.
15:48This solution is available in real time, either through a direct API or through a portal,
15:56or even through a batch process if that's more in your scheme.
16:02Ultimately, we want to give you the ability to get the highest quality and fidelity data of that verified income and employment when you are ready to pay for it.
16:17We understand that verified data certainly can be costly and has increased in costs over time.
16:23And so our focus is trying to give you as many options for when you do come to get that verified data,
16:31you have higher confidence that that consumer is one who you really need it for versus for earlier on.
16:39And on that theme of more options, we can go to the next slide.
16:43I want to share with you something that we are launching early in 2026, which is the Experian Verify Preview Report.
16:53The Experian Verify Preview Report is a new offering for instant verification solution,
17:00and it will give you ultimately a preview of what employment records Experian has access to.
17:10So you would be able to call our verification service using the same API or same method you would access to actually get the verification,
17:20and before getting the verification, request a preview of what employers does Experian have employment records for for a given consumer.
17:35So you would pass us the consumer's information and just say, hey, you know, which employers Experian do you have information for?
17:42And we would return to you a very simple employer list.
17:46So if you see on this slide, we have this table to the right where we have, you know, sampling of employment data.
17:52You have an employer name, a hire date, a position end date, a title, you know, base pay.
17:59We understand mortgage.
18:00You know, you want all the pay breakouts.
18:02So while a traditional verifications report would have all of that level of granularity,
18:09what this offers you is the ability to just see which records are available at Experian
18:18so you can be smarter and more strategic in when you call our service,
18:24requesting a full income and employment verification for a consumer.
18:27When we did our poll earlier, Ted, did we get some insights into how often folks were saying
18:37they were paying for records more than once?
18:40Let's see if we can go back.
18:42Yeah.
18:44All right.
18:45It looks like 50% said never, 10% rarely, 40% occasionally.
18:51Oh, I love that.
18:52That is a far better, far better answer than what we get in some other places.
18:56So that's really wonderful if that's not a frequent problem for you.
19:01We do often hear that if there's a problem where our either mortgage or tenant clients
19:07are looking for certain employment records and they ultimately, you know,
19:13end up having to pay for the same information more than once.
19:18If that's not a problem for you, that's fantastic.
19:22The Experian preview might not be relevant for you,
19:24but if it ever is a problem or you want just more options or more information
19:30before you commit to that larger price tag, income and employment verification,
19:35this will be an option for you to leverage next year.
19:40So if we can go to the next slide.
19:42So going through kind of the benefit of this preview report specifically for mortgage by leveraging
19:52this type of very light touch, just giving you a sense of what employment records we have
19:59access to, you can get insights into experience employer coverage without having to commit to
20:07a purchase of a full report.
20:10You can access it through the existing integration that you use, whether that be portal or API.
20:17It is not a different endpoint.
20:19It is the same endpoint.
20:21It's just a different report type that's being requested.
20:24And then you can leverage that to really effortlessly move on to, at the end, requesting the full verification.
20:34What we'd love to give you the flexibility to do is earlier on in your process,
20:40leverage observed data to substantiate what consumers have put on their applications
20:45or help you kind of segment out which consumers you want to request more detailed information for
20:52or which ones to progress a little quickly or better inform which ones are more likely to not drop out.
21:01And so while you can do that and get that further narrowed down,
21:06we want to give you the ability to have even more data at your fingertips
21:11before pulling the trigger and ordering the full income and employment verification.
21:18So this is meant to be kind of an in-between step of you've gone through,
21:23you know, your marketing and your funnel and your pipeline and the consumer's going through your flow
21:29and you just want to get a sense of where can I even get the employment record that I need.
21:35You can check this and then decide to purchase a verifications report.
21:42And you can decide how to implement it in your workflow.
21:46For our tenant screening clients, I know this might also be of interest to give you
21:52more tools to get insights on verified data
21:57data with the understanding that you don't yet need a full report.
22:03So if we can go to the next slide.
22:07So here's what, just a sample of what the Experian Verified Review Report will look like.
22:14This is not a standalone solution, so it will be something that is available
22:19given you contract for and are going to request verified reports.
22:27It would be a consumer report made available.
22:30You can request it, like I said earlier, using whatever existing method you have.
22:35It would return just a list of nicknames for employers found in Experian's Employer Network.
22:42And that would be employers from all of our data providers, whether they be employers or
22:48payroll providers, we would return to you, here's the employers we have information for,
22:54for Jane Doe, across our different data providers.
22:59You can then decide if the employers listed there, meet ones that you need a verified record for,
23:07to submit a new inquiry, and order the full verifications report.
23:12So I think that's all I had, just to be mindful of time and respectful of folks' time.
23:19So let's open it up for questions, and we can go from there.
23:31All right.
23:32Let's see here.
23:34First question we have.
23:36I'm sorry, Joelle, what did you say?
23:38I said, don't be shy.
23:39Well, I've got, we've got a couple.
23:42Let me get to the first one.
23:44Given that credit is being accessed earlier in the process with Fannie Mae's early assessment,
23:49how should lenders rethink when they start looking at income and employment?
23:53Oh, that's a good question.
23:57So if we take a look at our slides, if you would be mind maybe going back to slide 12,
24:04I think that's a good visual for this question.
24:11Maybe I'll start them on, Ted.
24:13You can edit.
24:15All right.
24:15Yeah.
24:17That one.
24:18Yes.
24:19Yes.
24:20Yes, absolutely.
24:22So if we're looking at, you know, the different stages, whether it be prospecting, recall, initial
24:28application, underwriting, and then pre-close, as Ted had mentioned, there are different types
24:36of data or even different versions of the same type of data that would be more appropriate
24:42at a given stage, given the business risk you're wanting to assess and the price point you're
24:48comfortable at.
24:49So if you look at, you know, the very top of the funnel prospecting, something like observed
24:55data would be an appropriate fit there.
24:58And as lenders are pulling credit information earlier on in this process, what we want to
25:06give you is the option to also get insights into income and employment data at those earlier
25:13stages of getting insights of credit data.
25:16So whether that be at the pre-call stage for the mortgage market, we offer a pre-qualification
25:25verifications report.
25:27It is a light-touch verifications report and goes, you know, hand-in-hand very well for
25:35that pre-qual stage and it's designed specifically for that to give you just enough information
25:41for the pre-qual at a lower price point and ultimately, you know, allowing you and the consumer
25:48to progress onto application and not incur prohibitive costs at that stage.
25:57And the end result is really just for you to optimize not only the people you're putting
26:04into your funnel so that more people close, but the costs, especially if they drop out,
26:10you don't want to be responsible for any fees or costs that were accumulated along the way.
26:17Absolutely.
26:18And what did you say, Ted, or the dropout average rate was...
26:2230 to 50%.
26:2330 to 50%.
26:25That's a lot.
26:26That's a lot.
26:27More than I expected.
26:30You know, Ted and I, we operate across many different verticals and spaces, and so that
26:35really is quite a lot, and that's a big cost for you to carry, whether that be in mortgage
26:42or any other housing vertical.
26:46I would imagine for tenant screening, that's even higher.
26:51Okay.
26:52Are there any more questions?
26:55Yes.
26:56We've got at least one more.
26:59What are some types of alternative data that can be used as a source for observed data?
27:03Well, if you want to go one slide before this one, that might be a good visual just to have up.
27:23But while you do that, a few callouts of observed data today sources data from different creditors.
27:33And to Ted's point, that's information that started out as consumer-stated information, but has gone through some substantiation method.
27:44So whether that's a, you know, credit or decided, yes, to issue that credit product.
27:50So that's, you know, a way to get it of, we might not return the verified data, but you know, consumer applied for a given product.
28:01They stated their income was, you know, $50,000, and you know that they received that product.
28:08And knowing that data point and then having other data points of other lending or credit products that they applied for and ultimately got.
28:19And the performance of those products would give you kind of a confidence, a reasonable sense of their, you know, income.
28:28Yeah, but sources could be auto lenders.
28:30It could be personal loans, mortgages.
28:33As I mentioned, we are working on rent bureau data, integrating that.
28:39But it could be any type of financial product where somebody has to make a statement about their employment income.
28:45And that is substantiated.
28:49We're looking across all of the experienced businesses to see what additional data sources we can pull in.
28:56So while we're starting with credit data, to Ted's point, rent bureau data will be coming in.
29:05And that is when you know a consumer's rent payments and you have verified rent payment history,
29:12and you know at what rate they have ever been delinquent or not,
29:18and the performance of their rental payments,
29:20not only can you get an insight into a consumer's income,
29:25but also some insight into some of that behavior,
29:28which is what we're looking to build out into observed data.
29:33So certainly we can give you an estimate of, you know, like, knowing where Ted lives and his given zip.
29:39I can say with fairly decent confidence his income is probably our favorite $2 million.
29:46If only.
29:48We wish.
29:48Given what zip code he lives in.
29:53And while that's helpful insight, where it becomes really interesting is if you also get additional insights like,
30:02and he's had really consistent rent payments and never been delinquent,
30:07or, you know, his rent might be this much and we estimate his income is this much,
30:12but like, oh, geez, he's missed a ton of rent payments or been very inconsistent.
30:16So being able to pull those types of insights in earlier on,
30:22better flagged risk and reduce cost.
30:27And fallout.
30:28And fallout.
30:29Yeah.
30:30And we're also looking at, you know, quite a few other data sources that are,
30:35I like to say creative, you know, at Experian, we have a wide access of different types of data across our many businesses.
30:46And our goal is always to help consumers get access to more financial services and products that would suit them best.
30:55So I think we always like to say, say yes to more consumers, especially to those consumers who are maybe underrepresented in traditional data sources.
31:05So looking at, you know, say credit data, if someone has a really fantastic rental history,
31:13that can give you insights that wouldn't necessarily be available in their credit file if they are, you know,
31:20a new immigrant or, you know, new to the country, but they still have a lot of good history there,
31:29and that can give us insights.
31:33Sorry, I'm sorry.
31:34Time fell off, but I get excited.
31:36Zebra, are there any more questions?
31:39No, sir.
31:40That's it.
31:41I believe we are.
31:44Got all our questions done.
31:46All right.
31:47Well, thank you very much for joining us today.
31:49We appreciate the time you've spent, and we hope you've learned something from joining us.
31:54For sure.
31:55And for our audience, just a reminder that we'll be sending out a recording of today's session.
31:59To all the registrants, and you'll be able to access the full webinar on our website at housingwire.com forward slash events.
32:08So thank you all for being with us.
32:10Joy, Ted, thank you so much for sharing with us, and we look forward to seeing you all at a future HousingWire event.
32:18Thank you, guys.
Recommended
1:00:29
|
Up next
1:05
1:25
1:00
9:14
Be the first to comment