Model Match vs Data Facts

What the rubric says

Model Match and Data Facts are both scored in Verification & Data. Model Match carries an overall of 4.8, Data Facts an overall of 2.3. The widest gap between them is Production impact, at 2.8 of a point. That axis measures whether the tool moves volume, pull-through or cycle time. Model Match takes it, 4.9 to 2.1.

Where the five axes separate

On Production impact the record favours Model Match, 4.9 against 2.1. On Return on spend the record favours Model Match, 4.9 against 2.3. On Functionality and depth the record favours Model Match, 4.8 against 2.3. On Adoption and support the record favours Model Match, 4.9 against 2.6. On Integrations and ecosystem the record favours Model Match, 4.3 against 2.3.

Pricing posture

Model Match publishes pricing. Its listed model is published per-seat monthly tiers from $49 to $199, plus custom enterprise. Data Facts does not publish pricing. Its listed model is quote only. One of the two can be costed before a sales call, the other cannot.

Deployment and who each one targets

Deployment for Model Match: Cloud, self-serve with a 14-day trial and month-to-month billing. Deployment for Data Facts: Cloud, ordered through LOS integrations or a web portal. Segment focus for Model Match: Mortgage recruiters, branch managers and originators sourcing talent and agent partners on a small budget. Segment focus for Data Facts: Community banks and credit unions that buy mortgage credit and employment screening from the same. The two entries name different buyers.

What each record credits

Model Match: Rates published outright, from $49 to $199 monthly, with trial and no annual contract. Model Match: Search plus built-in outreach, calling, notes and email, so recruiters skip the spreadsheet. Model Match: Founded by working mortgage recruiters, so it matches how recruiting actually runs. Data Facts: One vendor covers lending and employment screening, which suits banks and credit unions. Data Facts: Publishes direct connections to Fannie Mae DU and DO and Freddie Mac LPA. Data Facts: Flood certifications fulfilled through ServiceLink against current FEMA data.

What each record holds against them

Model Match: Transaction history starts in 2017, shorter than the deepest rival datasets. Model Match: No CRM or LOS integration named, no applicant tracking either; API sits top-tier. Model Match: The 25,000-professional user figure and client logos are self-reported, without third-party confirmation. Data Facts: Short, dated LOS list, still naming Ellie Mae ePASS and Byte 2.0. Data Facts: The homepage leads with background screening; mortgage buyers dig to find lending. Data Facts: No pricing published and no ownership or parent detail disclosed.

Which one fits which shop

Best fit for Model Match: A recruiter who wants originator production data and a pipeline CRM in the same seat. without an enterprise contract. Best fit for Data Facts: An institution consolidating mortgage credit and background screening under one contract.

What each entry concludes

Model Match: Model Match grew out of the recruiting agency Hammerhouse, and it shows. Model Match: This is a recruiter’s tool first and a market data product second. Data Facts: Data Facts runs two businesses under one roof: background and tenant screening, and a mortgage lending division. Data Facts: The lending side sells credit reports, verifications, fraud prevention, appraisal tools, flood certifications through ServiceLink, and portfolio monitoring.

The short answer

Model Match finishes ahead on the published rubric, 4.8 to 2.3. The margin comes mostly from Production impact. Same rubric, same weights, no sponsorships.