Unlocking Hidden Value: How AI is Transforming Rent Verification

At Trigo, we've been quietly transforming how rental history data gets collected, and the results are eye-opening. We’re excited to share more about how AI has catalyzed that transformation.

In residential real estate, previously slow and inefficient processes were gradually and reluctantly written off despite their significant value. Now, these onerous processes are suddenly back in play and achievable with breakthroughs in technology.

The Fallacy About Rent Verifications

In the real estate industry, property managers screen tenants analyzing personal financials and background checks. Rent verifications are a part of that background screening. For example, if you want to know how an applicant paid their rent, you have to, with the consent of the applicant, call the prior landlord(s) and ask. Ten short years ago, those phone calls were commonplace (and often required!), given the obvious and significant value of that data to the new landlord.

However, a shift happened over the last decade. The prevailing consensus in multifamily today is, “Don’t bother with rent verifications. Landlords don’t answer those requests anymore.” We’ve discovered that can’t be farther from the truth, particularly by leveraging AI to do things that site-level staff can’t.

With staffing shortages and high turnover, the property management industry has always struggled to perform rent verifications profitably, consistently, and in a HUD-compliant manner. On any given day, on-site teams have a litany of other important day-to-day responsibilities. Chasing a landlord a fourth time for a callback falls to the bottom of the lengthy to-do list of responding to maintenance requests, turning vacant units, etc. As a result, screening standards partially eroded. Many operators slowly abandoned rent verifications altogether -- and at their own peril.

The Data: A Rate of Automation “Hockey Stick”

Our latest internal analysis reveals a profound shift, however. AI is dramatically changing our ability to retrieve critical data that was previously considered too difficult to obtain from prior landlords.

The below graph represents our rate of automation using AI across our entire platform. A few of the applications include autonomous phone calls, texts, and emails, and ingesting, cataloguing, and routing large daily influxes of data and inbound / outbound communications As of December 2024, almost half of that activity was happening without any human involvement or direction whatsoever and increasing exponentially.

Source: Internal Trigo operational dashboard.

AI Is Transforming Data Retrieval

What started as an experiment in automation has transformed into a game-changing approach for our data retrieval strategy. The automation has driven greater speed and, more importantly, greater data availability. By leveraging AI, we've:

• Increased our rent data coverage to over 80% (vs. < 3% from the credit bureaus)

• Reduced our average rent verification times to under 24 hours (vs. the industry avg. of over 90 hours)

• Created a more comprehensive view of rental histories than previously possible in the pre-AI era

Credit Bureaus vs. Trigo

Unfortunately, the credit bureaus have less than 5% coverage of rent payment history. At that level, the data doesn’t have much utility for landlords or financial institutions, resulting in low usage and institutional adoption.

The reason for that low coverage is that, unlike your credit card or utilities company, very few landlords proactively report rent payments to the credit bureaus. That’s right. If you’re like me and have been paying your rent on time for 10+ years, you are almost certainly not getting “credit” for those rent payments in your FICO score. It’s a problem that has persisted for years. Residential owners refuse to report it, which is bad for renters. The irony, however, is that it creates an even larger problem for the owners themselves.

Because residential owners do not typically report rent payments to the credit bureaus, they leave themselves with only one alternative: difficult, manual data retrieval (i.e., rental verifications).

Why Rent Data Is Important

Traditional underwriting and resident screening datasets have significant blind spots. Credit scores, income, and background checks tell part of the story (and an important one) - but rental history? That's the largest missing piece of the puzzle.

For example, what do you think is a more predictive indicator for whether you will pay your rent or mortgage: how you paid your electric bill, or how you paid your previous landlord?

At Trigo, we’ve been patiently collecting this data since 2023 to prove how much these legacy datasets are missing (a topic I’m planning for a future post!). The data paints a stark picture of what landlords and underwriters are missing by relying exclusively on legacy metrics like FICO and Income / RTI.

Rent Data Matters Even More for Renters

If you qualify for a mortgage or a credit card, chances are you already have a robust credit file. In contrast, renters in the U.S. over-index on “thin” or “invisible” credit profiles.

Many renters do not have lines of credit, have not had the luxury of a parental co-signer on a first credit card, or built credit with a personal loan or otherwise.

Thus, the “chicken and egg” problem of the legacy FICO scoring system persists. You need to have credit to get credit. This dynamic boxes out many hard-working Americans from accessing affordable forms of financing and housing.

The vast majority of these “thin” credit-filed Americans have one thing in common, however. They rent! Not only do they rent. Over 92% of renters pay their rent on time and in full. This data is invaluable to: (i) help renters establish and build credit, and (ii) aid property managers and underwriters in making more informed decisions.

Reimagining What’s Possible with AI

Our team has discovered that AI doesn't just incrementally improve processes; it fundamentally reimagines what's possible.

Over the past 18 months, we discovered that it takes, on average, 11 call/email/text outreaches before a landlord will complete a rental verification for a single address. Typically rent verifications require multiple addresses, adding up to over 20-30 inbound and outbound communications in less than 72 hours. What property manager has the time to do that for one applicant, let alone multiple, while juggling hundreds of other critical day-to-day responsibilities? The answer is very few. But AI can, and it’s reimagined what’s possible for all kinds of data retrieval, including mission-critical rent verifications.

The real excitement, however, isn't about the technology itself. It's about helping more renters access affordable housing and credit and providing property managers and financial institutions with more accurate, holistic insights that improve their bottom-line.

Curious about how AI is reshaping data retrieval and the consumer credit landscape? I'm always eager to learn and share more, so please don’t hesitate to reach out!