Policy switching and bind probability, at signal speed.
Property, casualty, life, and health insurers use predictive intelligence to identify in-market switchers and tier prospects by bind probability. Predictive scoring reduces wasted underwriting and dramatically improves cost-per-bind economics.
What makes Insurance different.
Switching intent
Behavioral signals correlated with renewal-window evaluation and active comparison shopping.
Life-event triggers
New home, new vehicle, new family member, retirement — life-event signals materially change insurance demand.
Bind-probability scoring
Top-of-funnel filtering by probability of binding, not just by lead presence.
Decay, velocity, and cost — measured.
Per-vertical curves derived from the platform's calibrated model output. Industry averages overlaid for reference.
Hours since first intent signal
Days from first contact
Traditional vs. predictive within the vertical
Inside a deployment
Mid-market lender lifts ROAS 3.1x with behavioral risk + intent overlay
Behavioral risk scoring integrated with intent signals produced cleaner top-of-funnel for a consumer lender. The combined model reduced underwriting waste 38% and lifted return on ad spend 3.1x within two quarters.
Supporting research & guides
auto insurance switching intent
home insurance renewal signals
life insurance life event data
commercial insurance prospecting
Common questions
Which lines work best with predictive intelligence?+
Auto, home, life, and small-commercial show the largest measured lift. Health is supported but governed by additional compliance overlays.
Predictive intelligence · enterprise onboarding
Move from list-buying to probability-buying.
Engage your account team for a calibrated intelligence estimate, methodology walkthrough, and a sandbox environment scored against your own audience.