Cotality vs Point Predictive

What the rubric says

Cotality and Point Predictive are both scored in Verification & Data. Cotality carries an overall of 4, Point Predictive an overall of 2.1. The widest gap between them is Integrations and ecosystem, at 2.8 of a point. That axis measures how well it reaches the rest of the stack. Cotality takes it, 4.4 to 1.6.

Where the five axes separate

On Integrations and ecosystem the record favours Cotality, 4.4 against 1.6. On Functionality and depth the record favours Cotality, 4.9 against 2.3. On Production impact the record favours Cotality, 4 against 2.3. On Return on spend the record favours Cotality, 3.2 against 2.1. On Adoption and support the record favours Cotality, 3.2 against 2.1.

Pricing posture

Cotality does not publish pricing. Its listed model is quote only, enterprise contracts. Point Predictive does not publish pricing. Its listed model is quote only.

Deployment and who each one targets

Deployment for Cotality: Cloud, APIs, cloud marketplace delivery and LOS integrations. Deployment for Point Predictive: Cloud, delivery mechanism not published. Segment focus for Cotality: Large lenders, servicers and capital markets participants buying property data at scale. 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

Cotality: One counterparty covers property data, flood, tax servicing, valuation and fraud scoring. Cotality: Stone Point Capital and Insight Partners ownership since 2021 brings rare capital depth. Cotality: Data ships through Snowflake and Databricks marketplaces, not only proprietary APIs. 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

Cotality: Bundled, opaque pricing makes per-product cost hard to isolate at renewal. Cotality: Enterprise sales and implementation run long against point-solution rivals in every category. Cotality: The 2025 rename means contracts and references still carry both names. 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 Cotality: An enterprise that wants property, flood, tax and valuation data from one counterparty. Best fit for Point Predictive: Lenders with enough application volume for score-based triage to change staffing.

What each entry concludes

Cotality: Cotality is CoreLogic renamed in March 2025, private under Stone Point Capital and Insight Partners since June 2021. Cotality: The lending catalogue runs property and address data, flood determinations, tax servicing, and valuation through Mercury Network. 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

Cotality finishes ahead on the published rubric, 4 to 2.1. The margin comes mostly from Integrations and ecosystem. Same rubric, same weights, no sponsorships.