Data Facts vs Point Predictive
Verification & Data head-to-head · axis by axis, same rubric for both
Verification & Data
Verification & Data
| Axis | Data Facts | Point Predictive |
|---|---|---|
| Production impact | 2.1 | 2.3 |
| Functionality & depth | 2.3 | 2.3 |
| Integrations & ecosystem | 2.3 | 1.6 |
| Adoption & support | 2.6 | 2.1 |
| Return on spend | 2.3 | 2.1 |
| Overall | 2.3 | 2.1 |
Data Facts wins 3 of 5 axes. Same rubric, same weights, no sponsorships.
What the rubric says
Data Facts and Point Predictive are both scored in Verification & Data. Data Facts carries an overall of 2.3, Point Predictive an overall of 2.1. The widest gap between them is Integrations and ecosystem, at 0.7 of a point. That axis measures how well it reaches the rest of the stack. Data Facts takes it, 2.3 to 1.6.
Where the five axes separate
On Integrations and ecosystem the record favours Data Facts, 2.3 against 1.6. On Adoption and support the record favours Data Facts, 2.6 against 2.1. On Return on spend the record favours Data Facts, 2.3 against 2.1.
Pricing posture
Data Facts does not publish pricing. Its listed model is quote only. Point Predictive does not publish pricing. Its listed model is quote only.
Deployment and who each one targets
Deployment for Data Facts: Cloud, ordered through LOS integrations or a web portal. Deployment for Point Predictive: Cloud, delivery mechanism not published. Segment focus for Data Facts: Community banks and credit unions that buy mortgage credit and employment screening from the same. Segment focus for Point Predictive: Higher-volume lenders using fraud scores to triage underwriting, with auto lending as the company’s core. The two entries name different buyers.
What each record credits
Data Facts: One vendor covers lending and employment screening, which suits banks and credit unions. Point Predictive: MortgagePass rank-orders applications by fraud propensity, enabling risk-based triage over binary flags.
What each record holds against them
Data Facts: Short, dated LOS list, still naming Ellie Mae ePASS and Byte 2.0. Point Predictive: No origination system or point of sale integration is named anywhere.
Which one fits which shop
Best fit for Data Facts: An institution consolidating mortgage credit and background screening under one contract. Best fit for Point Predictive: Lenders with enough application volume for score-based triage to change staffing.
The short answer
Data Facts finishes ahead on the published rubric, 2.3 to 2.1. The margin comes mostly from Integrations and ecosystem. Same rubric, same weights, no sponsorships.
Both tools are scored on the same weighted rubric, production impact carries the most weight. Comparisons are never sponsored. Disclosure →