Argyle vs Point Predictive

What the rubric says

Argyle and Point Predictive are both scored in Verification & Data. Argyle carries an overall of 4.6, Point Predictive an overall of 2.1. The widest gap between them is Integrations and ecosystem, at 2.9 of a point. That axis measures how well it reaches the rest of the stack. Argyle takes it, 4.5 to 1.6.

Where the five axes separate

On Integrations and ecosystem the record favours Argyle, 4.5 against 1.6. On Return on spend the record favours Argyle, 4.9 against 2.1. On Production impact the record favours Argyle, 4.8 against 2.3. On Functionality and depth the record favours Argyle, 4.4 against 2.3. On Adoption and support the record favours Argyle, 4 against 2.1.

Pricing posture

Argyle does not publish pricing. Its listed model is quote only, usage based per verification. Point Predictive does not publish pricing. Its listed model is quote only.

Deployment and who each one targets

Deployment for Argyle: Cloud API, embedded in LOS and point of sale. Deployment for Point Predictive: Cloud, delivery mechanism not published. Segment focus for Argyle: Lenders replacing or supplementing instant-database VOIE with direct payroll connections. 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

Argyle: Approved for Fannie Mae DU validation and supported in Freddie Mac AIM. Argyle: Names Encompass, Byte and Empower, plus point of sale links including nCino. Argyle: Pay per use, no subscription; lenders pay for verifications actually ordered. Point Predictive: MortgagePass rank-orders applications by fraud propensity, enabling risk-based triage over binary flags. Point Predictive: Draws on application, servicing, real estate and behavioural data plus its consortium repository. Point Predictive: Published paystub fraud research, finding one in ten submitted paystubs fake, grounds the modelling.

What each record holds against them

Argyle: A 55 percent published verification rate leaves half of attempts needing fallback. Argyle: The 80 percent cost saving figure is a vendor claim without audited benchmark. Argyle: Borrowers must authenticate into payroll accounts, adding drop-off database vendors avoid. Point Predictive: No origination system or point of sale integration is named anywhere. Point Predictive: The half-of-applications and sixty percent claims carry no third-party validation. Point Predictive: Consortium depth is strongest in auto, with no equivalent mortgage scale disclosed.

Which one fits which shop

Best fit for Argyle: A lender whose verification bill has outgrown the loan volume it supports. Best fit for Point Predictive: Lenders with enough application volume for score-based triage to change staffing.

What each entry concludes

Argyle: Argyle connects to a borrower’s payroll account, with permission, and returns income and employment data from the source. Argyle: That replaces querying a database of employer-contributed records. Point Predictive: Point Predictive builds fraud risk models from a consortium data repository, and its centre of gravity is auto. Point Predictive: MortgagePass is the mortgage product, a score that rank-orders applications by the odds of material fraud.

The short answer

Argyle finishes ahead on the published rubric, 4.6 to 2.1. The margin comes mostly from Integrations and ecosystem. Same rubric, same weights, no sponsorships.