> ## Documentation Index
> Fetch the complete documentation index at: https://develop.cotality.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Property and casualty insurance

> Data and AI solutions for P&C underwriters and claims teams — model climate exposure, assess structural risk, and accelerate hazard policy decisions.

Cotality's property insurance solutions help P\&C insurers, underwriters, and claims teams make faster, more accurate decisions by surfacing the physical condition, climate exposure, and structural risk data they need — at any address, at scale.

***

## Who this is for

<CardGroup cols={3}>
  <Card title="P&C underwriters" icon="shield-halved">
    Evaluate roof age, construction materials, and climate risk scores to price hazard policies and set coverage terms
  </Card>

  <Card title="Claims adjusters" icon="file-invoice">
    Verify structural details, assess pre-loss condition, and cross-reference physical characteristics for faster claims decisions
  </Card>

  <Card title="Risk and actuarial teams" icon="chart-bar">
    Model portfolio-level climate exposure, stress-test against hazard scenarios, and identify concentration risk by geography
  </Card>
</CardGroup>

***

## Key use cases

### 1. Hazard policy underwriting

**Business problem:** Underwriting a property hazard policy requires assessing both the structure's physical vulnerability and its exposure to weather and climate perils — data that typically requires manual inspection, third-party reports, or slow data pulls.

**With Cotality:** Retrieve roof age, construction type, foundation type, and multi-peril climate risk scores for any property in the U.S. in a single MCP tool call. Use the results to calculate replacement cost estimates and set deductibles without ordering a physical inspection for every policy.

**What you get:**

* Age of roof estimates with confidence ranking
* `universalRoofCoverCode` and `universalRoofCode` for material and style
* `universalExternalWallCode` and `buildingClassificationCode` for construction type
* Climate risk scores for wildfire, flood, hurricane, and other perils

***

### 2. Multi-peril climate risk modeling

**Business problem:** Climate risk is a growing priority for insurers, but modeling long-term exposure at the property level is data-intensive and requires combining physical asset data with peril-specific hazard models.

**With Cotality:** The Climate risk analytics tools return property-level hazard scores across multiple perils — including wildfire, flood, and hurricane — normalized to return periods (e.g., 50-year, 100-year, 200-year). Combine these with property characteristics to build a complete risk profile for any address.

**What you get:**

* Property-level climate risk scores by peril and return period
* National coverage across all U.S. residential and commercial parcels
* Batch processing for portfolio-level exposure analysis

[View Climate risk analytics →](/mcp/property-data/tools/climate-risk-analytics)

***

### 3. Roof condition assessment

**Business problem:** Roof age and condition are among the most significant factors in property insurance pricing and claims outcomes, but obtaining current roof data traditionally requires an inspection order or satellite imagery analysis.

**With Cotality:** The age of roof tool returns a statistically derived estimate of roof age with a confidence rank — no inspection required. Use this to triage properties that warrant closer review, flag aging roofs for premium adjustment, or validate policyholder-reported condition at renewal.

**What you get:**

* Estimated roof age and construction year
* Confidence rank for the estimate
* CLIP-based batch retrieval for portfolio monitoring

[View age of roof tool →](/mcp/property-data/tools/climate-risk-analytics#pacra-property_analytics_age_of_roof_by_clips_tool)

***

### 4. Claims verification and desk review

**Business problem:** After a loss event, adjusters need accurate pre-loss property data to validate claims — but access to real-time structural records during high-volume catastrophe response is often slow and inconsistent.

**With Cotality:** Use property characteristics to retrieve pre-loss structural data for any property during claims intake. Verify reported square footage, construction materials, number of buildings, and accessory structures against county records and Cotality's modeled data.

**What you get:**

* `livingSquareFootage`, `grossSquareFootage`, and footprint geometry
* `universalFoundationCode` and `universalBasementCode` for flood and sewer loss assessment
* Ownership and parcel details for fraud validation
* Batch retrieval for CAT event response across thousands of claims simultaneously

***

### 5. Portfolio risk management

**Business problem:** Insurers need to monitor aggregate climate and physical risk exposure across their books of business — identifying concentrations, flagging emerging hazards, and ensuring capital adequacy.

**With Cotality:** Combine climate risk analytics with property characteristics across a portfolio of CLIPs to build a structured risk register. Layer on market trend analytics to monitor property value changes that affect insured-to-value calculations.

**What you get:**

* Portfolio-scale batch processing for climate and structural risk data
* Property value trends by geography for insured-to-value monitoring
* Exportable structured JSON for downstream risk models and actuarial platforms

***

## Integration paths

<Tabs>
  <Tab title="MCP Server (AI-embedded)">
    **Best for:** Teams building AI underwriting assistants, claims copilots, or risk intelligence tools powered by LLMs

    Connect any MCP-compatible AI assistant to Cotality property and climate data at runtime — no custom API integration required.

    **Lifecycle:** <Badge color="green">GA</Badge>

    **Typical tool call sequence:**

    1. `clip-find_property_by_full_address` → resolve address to CLIP
    2. `pacra-property_analytics_by_clips_tool` → retrieve age of roof + climate risk
    3. `pc-characteristics_by_clips_tool` → retrieve structural details

    [Get started with MCP →](/mcp/overview)
  </Tab>

  <Tab title="REST API (direct integration)">
    **Best for:** Teams integrating property and risk data into underwriting systems, policy management platforms, or actuarial models

    Access property characteristics, climate risk scores, and market data through standard REST endpoints.

    **Lifecycle:** <Badge color="green">GA</Badge>

    Key APIs for insurance use cases:

    * **Property API** — Physical and structural property data
    * **Insight API** — Derived risk intelligence and scoring
    * **Underwriting Center API** — Automated underwriting data

    [Browse API reference →](/getting-started/overview#rest-apis)
  </Tab>
</Tabs>

***

## Relevant capabilities

| Capability                                                                    | What it provides                                                  | Lifecycle                       |
| ----------------------------------------------------------------------------- | ----------------------------------------------------------------- | ------------------------------- |
| [CLIP tools](/mcp/property-data/tools/clip-tools)                             | Address-to-CLIP resolution for any U.S. property                  | <Badge color="green">GA</Badge> |
| [Property characteristics](/mcp/property-data/tools/property-characteristics) | Structural data: construction type, roof, foundation, walls, size | <Badge color="green">GA</Badge> |
| [Climate risk analytics](/mcp/property-data/tools/climate-risk-analytics)     | Multi-peril climate scores and age of roof estimates              | <Badge color="green">GA</Badge> |

***

## Industry standards alignment

Cotality property and risk data conforms to dominant insurance industry standards:

* **ACORD P\&C standards** — `universalConstructionTypeCode` maps to ACORD `ConstructionCode`; roof and wall codes map to ACORD structural rating standards for risk underwriting
* **OGC well-known text (WKT)** — Building footprint geometry is returned in WKT format, compatible with ArcGIS, QGIS, PostGIS, and Leaflet

***

## Get started

<Steps>
  <Step title="Define your risk data needs">
    Identify which perils, structural attributes, and geographies are relevant to your underwriting or claims workflow
  </Step>

  <Step title="Get credentials and authenticate">
    Obtain OAuth2 client credentials and [get your first access token](/mcp/authentication)
  </Step>

  <Step title="Test with sample properties">
    Use the [MCP inspector](/mcp/quickstart) to retrieve climate risk and property characteristics for test properties in your market
  </Step>

  <Step title="Integrate into your platform">
    Connect via MCP for AI-embedded use cases or REST API for direct system-to-system integration
  </Step>
</Steps>