Model Match vs Informative Research

Hiring producers versus clearing conditions

Model Match helps a lender recruit and prospect. Informative Research helps a lender pull credit and verify a borrower. The comparison makes sense as a budget question and little else. A lender short on originators has a capacity problem. A lender paying too much per verification has a margin problem. The two rarely trade against each other in the same review. Both bills still land in the same technology budget, which is why buyers ask.

Model Match sells market data by the seat

Model Match publishes tiered pricing at $49, $99 and $199 a month. Enterprise is quote only. The data covers loan officers, agents, companies and branches. Loan level records support refinance and equity targeting. A CRM with calling, email and AI call notes sits on the higher tiers. History runs back to 2017 across mortgage and property records. A 14 day trial and month to month billing lower the risk of a test. Nothing in the product touches a live loan file.

Informative Research sells a waterfall and a credit file

Informative Research runs a verification waterfall across named providers. FCRA governed sources include The Work Number, Experian Verify and Thomas and Company. Consumer permissioned data comes through AccountChek. Manual verification runs through Veri-Tax and EmpInfo. IRS reported income comes from Halcyon. Lenders order cheaper sources early to hold down cost per file. The waterfall stops when a source returns a usable result. That order is configurable by role, user level or loan stage. Its credit side covers tri-merge, prequal soft pulls, FICO 10T and rapid rescoring.

Ownership tells you something about staying power

Stewart Information Services acquired Informative Research in 2021 for $192 million. Stewart trades on the NYSE under STC. AccountChek joined the group through a 2023 acquisition. Recent moves include a chief technology officer promotion in July 2026. A new AccountChek release followed the same month. Model Match is privately held with 11 to 50 employees listed on Crunchbase, and no disclosed funding. Balance sheet backing matters when you sign a multi year data agreement. A public parent also files results a buyer can read.

One publishes rates, one answers only on request

Informative Research publishes no price for credit or verification. Its FAQ says pricing depends on products, volume, bundles and configuration. It does state zero setup or integration fees. Ask for a per file cost at your volume, broken out by waterfall step. Model Match by contrast puts three monthly prices on a public page. No support service level agreement appears on either public site.

Named partners on each side

Informative Research names Blend, Encompass, Finastra, Empower and MeridianLink for integration. It joined the Dark Matter Exchange network in October 2024. It states that provider reports approved for DU and LPA can pass through the platform. Cloudvirga and Floify have also been named in its integration announcements. Model Match names no lending system at all. Its listed connections are email, calendar, Salesforce and HubSpot. It also supports Zapier and offers API access on the Premium tier.

Where the two products brush against each other

Both vendors sell borrower data, which is the single place they overlap. Model Match Borrower Insights filters loan level records for refinance and equity candidates. Informative Research markets borrower alerts and retention data on the credit side. The sources and the permitted uses differ sharply. A credit based alert carries FCRA duties that a market data export does not. Ask each vendor to put the data source in writing.

Which one to pick

A lender rebuilding sales capacity should fund Model Match and measure it against hires made. The monthly cost is small against a single producer. A lender carrying heavy verification and credit spend should work the Informative Research waterfall. Ask Informative Research for average cost per completed verification across your actual waterfall order. Ask Model Match how borrower contact data is sourced and how often it is refreshed. Get both answers in writing before signing. A vague answer on data sourcing is itself a useful answer.

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