Z-SPARK^TM

Pinpoint the Properties Most Likely to Ignite

Z-SPARK predicts non-weather fire risk by applying modern fire science to property-level intelligence to identify properties at higher risk of ignition, rapid fire spread, and loss

Model the Fire Risk That Actually Drives Loss

Z-SPARK analyzes how site and environmental conditions interact at every address, moving beyond broad community classifications and emergency response proxies to reveal hidden hazards.

Property-Level Precision

Captures how structural and site-specific conditions interact at each property to drive ignition and fire-spread risk.

30X Risk Differentiation

Separates high-risk from low-risk properties by 30x in fire claim frequency for sharper segmentation.

Verified Fire Data

Built and validated on millions of fire incidents and verified carrier claims.

Transparent Risk Drivers

Reveals the factors behind every score, giving underwriters clear justification for decisions and appeals.

Modern Fire Science

Grounded in latest fire science and structure-ignition research to pinpoint non-weather fire risk at the property level.

Nationwide Coverage

Provides continuously updated property-level risk scores across 100% of the contiguous U.S.

Claim Frequency Score: Likelihood of Fire Ignition

Z-SPARK predicts the likelihood of a non-weather fire risk at the address level by analyzing property-specific variables, including maintenance, material vulnerability, structure-to-structure proximity, and local fire response capabilities.

At a granularity unmatched by conventional models, these insights allow carriers to prioritize inspections, tailor coverage, or adjust risk mitigation precisely for each address.

Side-by-side comparison of a fire-damaged and intact kitchen illustrating Z-SPARK’s address-level claim frequency scoring.

Claim Severity Score: Magnitude of Fire Loss

Z-SPARK predicts loss severity by modelling the conditions that drive rapid fire spread and structural damage, not just emergency-response conditions. Because modern structure fires can reach flashover in as little as 3 to 5 minutes, response time alone does not fully explain the severity of loss. Carriers can use this insight to optimize pricing, set coverage and deductible guardrails, and manage portfolio loss costs.

Side-by-side view of an intact home and a house with total structural fire damage, illustrating Z-SPARK's claim severity score.

Strengthen Underwriting and Rating Workflows

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Price Risk with Precision

Traditional models rely on broad territorial averages that treat neighboring homes as identical. Z-SPARK evaluates risk at the individual property level, allowing insurers to differentiate risk within the same neighborhood and align premiums with true fire exposure.

Fast-Track Low-Risk Properties

Identify low-risk properties at quote time to reduce manual review and support fast, frictionless, straight-through processing. Direct underwriting attention to higher-risk structures where inspections, coverage adjustments, deductible guardrails, or homeowner engagement are needed.

Protect the Portfolio

Traditional models rely on thin historical data and static attributes, allowing high-risk properties to quietly enter the book. Z-SPARK surfaces hidden fire hazards early, enabling carriers to avoid adverse selection and manage portfolio loss costs.

Aerial view of residential roof and structural fire damage used as risk signals for Z-SPARK fire risk modeling. — ‍

How Z-SPARK Works

Z-SPARK analyzes how key structural, site, and environmental factors interact, including building materials, maintenance conditions, fire suppression infrastructure, local property density, climate conditions and more. These interactions explain why two homes on the same street can carry very different non-weather fire risk.

Data Ingestion

Feature Engineering

Model Development

Commercial kitchen fire used as real-world incident data for Z-SPARK ingestion and non-weather fire risk analysis.

Diverse, High-Quality Inputs

Aerial Imagery

Identifies property features that drive non-weather fire risk, such as roof-material vulnerability or hazardous proximity between structures.

Property Characteristics

Analyzes building materials, site maintenance, occupancy and additional factors to determine flammability and vulnerability.

Climate Data

Accounts for local climate conditions that influence structural combustibility and susceptibility to ignition.

Location Characteristics

Examines the surrounding environmental and infrastructure conditions that affect property-level fire exposure.

Verified Claims Data

Incorporates verified claims from carriers across the country.

Fire Suppression Capacity

Incorporates fire station proximity, road access, and community suppression resources.

Aerial view of suburban fire spread used for Z-SPARK feature engineering, analyzing building density and vegetation.

Turning Raw Data Into Insight

Computer Vision Analysis

Detects key physical attributes from aerial imagery.

Environmental Stress Indicators

Evaluates surrounding conditions such as building density, vacancy rates, and power grid reliability that influence fire risk.

Climatology

Models how local climate patterns affect material degradation and structural combustibility.

Emergency Response Infrastructure

Accounts for fire station proximity, road access, and community suppression resources.

Grid electric stability is a critical risk factor.

Purpose-Built for Non-Weather Fire

Built on Verified Claims

Trained and validated on claims from carriers across the country.

Gradient Boosted Machines

Models complex interactions between property features, climate conditions, and fire suppression infrastructure.

Dual-Model Architecture

Estimates claim frequency and severity, revealing the likelihood and potential magnitude of loss.

Transparent Risk Drivers

Exposes key factors influencing each property’s score, supporting underwriting review and regulatory transparency.

Mitigation-Aware Scoring

Accounts for mitigation actions taken by homeowners, enables underwriting overrides, and allows carriers to simulate how mitigation improvements may affect a property’s risk score.

Proven Predictive Power & Financial ROI

Z-SPARK delivers 30X improvement in risk differentiation over traditional territory-based models by revealing meaningful differences in non-weather fire risk at the property level.

Real-world fire incident data used to validate Z-SPARK’s proven predictive power for address-level risk assessment.

Seamless Workflow Integration

Z-SPARK integrates into existing underwriting and rating workflows. It operates as a standalone scoring model or augments community-level frameworks with property-level intelligence.

Laptop displaying the Z-SPARK dashboard, showing property-level frequency and severity scores for seamless underwriting integration.

Zero IT, Full Transparency

Z-VIEW^TM is a web-based application that delivers instant access to Z-SPARK risk scores, top risk drivers, aerial imagery, and mitigation simulation tools for any address.

No IT integration required. Ideal for underwriters, actuaries, and field teams alike, Z-VIEW puts Z-SPARK insights at your fingertips from day one.

For system-wide deployment, ZestyAI offers portfolio batch processing through Z-PORTFOLIO^TM and API integration across underwriting, renewal, and reinsurance workflows.

Z-VIEW interface showing the Z-SPARK appeal process, allowing users to review and update address-level fire risk drivers.

See the Hidden Fire Risk Your Model Misses

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Z-SPARK reveals the non-weather fire risk at the property level, helping you segment risk, price accurately, prioritize inspections, and manage loss costs. Book a demo today.

Proven Results

Browse Customer Stories

The product described on this website may be covered by one or more U.S. patents. For additional information, visit zesty.ai/patents.