> ## 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.

# Finance and mortgage

> Data and AI solutions for lenders, AMCs, and appraisers — automate collateral evaluation, appraisal order management, and compliance review.

Cotality's mortgage and valuation solutions help lenders, appraisal management companies (AMCs), and property appraisers automate the most data-intensive parts of the loan and appraisal lifecycle — from initial collateral evaluation to final UAD compliance sign-off.

***

## Who this is for

<CardGroup cols={3}>
  <Card title="Lenders and mortgage IMBs" icon="building-columns">
    Automate collateral review, run comparable analysis, and flag risk before loans advance in the pipeline
  </Card>

  <Card title="Appraisal management companies" icon="clipboard-list">
    Manage appraisal order lifecycles, match orders to qualified appraisers, and automate compliance review at scale
  </Card>

  <Card title="Property appraisers" icon="magnifying-glass-chart">
    Retrieve comparable sales, access property characteristics, and validate appraisal reports against UAD standards
  </Card>
</CardGroup>

***

## Key use cases

### 1. Automated collateral evaluation

**Business problem:** Underwriters spend significant time manually pulling property data, verifying comparables, and checking for valuation risk flags — slowing down loan origination and introducing inconsistency.

**With Cotality:** Use the property characteristics tool to retrieve granular physical and structural data for any property in the U.S. in seconds. Combine with the CLIP identifier to normalize property records across data sources. Feed results directly into valuation models or underwriting rules engines.

**What you get:**

* Standardized property records aligned with MISMO v3.x and FHFA appraisal datasets
* Access to `livingSquareFootage`, `actualYearBuilt`, `universalTotalValue`, and more than 200 additional fields
* Batch processing across multiple CLIPs for portfolio-level review

***

### 2. Comparable analysis (comps)

**Business problem:** Finding accurate comps for appraisals and desk reviews requires manually searching MLS records and county data — a slow, judgment-intensive process prone to recency bias.

**With Cotality:** Filter properties by structure characteristics such as `livingSquareFootage`, `actualYearBuilt`, and `landUseCode` to identify geographic comparables programmatically. Pull market trend data to benchmark against current listing activity and median price movements.

**What you get:**

* Property characteristics data for filtering comp candidates
* Market trend analytics including median sales price, days on market, and inventory velocity
* Home price index (HPI) data and forward-looking HPI forecasts by ZIP, county, CBSA, and state

***

### 3. Appraisal order automation

**Business problem:** AMCs manage thousands of appraisal orders simultaneously, each requiring manual order entry, status tracking, and vendor assignment — a high-volume operational burden that is difficult to scale.

**With Cotality:** Use the **appraisal order AI agent** to manage order lifecycle in natural language. Create orders, check status, view workflow history, and receive streaming updates — without custom development against a form-based workflow system.

**What you get:**

* Conversational order creation with guided field collection
* Real-time order status, key dates, and workflow activity logs
* Response streaming for live progress updates

[View appraisal order agent →](/ai-integrations/valuation-solutions/ai-agents#appraisal-order-agent)

***

### 4. Vendor panel management and assignment

**Business problem:** Matching appraisal orders to qualified, available vendors who meet geographic, licensing, and capacity requirements is a complex routing problem that AMCs often solve manually.

**With Cotality:** Use the **vendor order AI agent** to search, onboard, and manage appraiser panels through natural language. Configure auto-assignment rules, monitor capacity, track license and E\&O status, and surface at-risk expirations.

**What you get:**

* End-to-end vendor lifecycle management: search, onboard, panel, assign
* Auto-assignment rule configuration and capacity monitoring
* License and E\&O compliance tracking with expiration alerts

[View vendor order agent →](/ai-integrations/valuation-solutions/ai-agents#vendor-order-agent)

***

### 5. UAD compliance review

**Business problem:** Validating appraisal deliverables against UAD rules is time-consuming and error-prone when done manually, and costly when discovered late in the lending process.

**With Cotality:** Use the **compliance AI agent** to validate appraisal ZIP packages, run UAD rule checks, and retrieve structured findings — all through a conversational interface that guides correct tool sequencing.

**What you get:**

* Automated package validation (required files, structure, extensions)
* UAD rule execution against the full Cotality compliance rule set
* Detailed findings with rule-specific explanations and correction guidance

[View compliance agent →](/ai-integrations/valuation-solutions/ai-agents#compliance-agent)

***

## Integration paths

Choose the integration pattern that fits your architecture:

<Tabs>
  <Tab title="AI agent (conversational)">
    **Best for:** Teams building AI-powered AMC platforms, loan officer copilots, or compliance review assistants

    The valuation solutions AI agents communicate over the **A2A (agent-to-agent) protocol** and integrate with any orchestration framework that supports it, including Google ADK and LangChain.

    **Lifecycle:** <Badge color="purple">Alpha</Badge>

    **Steps:**

    1. Obtain A2A endpoint credentials from your Cotality account representative
    2. Register the agent card URL in your AI orchestration layer
    3. Send natural language instructions to the agent and receive streamed responses

    [Get started with AI agents →](/ai-integrations/valuation-solutions/ai-agents)
  </Tab>

  <Tab title="MCP server (AI-embedded)">
    **Best for:** Teams embedding property data lookup and analytics into an LLM-powered product or copilot

    The Cotality MCP server exposes property data, CLIP lookup, and analytics tools that any MCP-compatible AI client can discover and call at runtime.

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

    **Steps:**

    1. [Authenticate](/mcp/authentication) — Get your OAuth2 bearer token
    2. Connect your AI client (VS Code, Cursor, Claude Code, or Python SDK)
    3. Call `clip-find_property_by_full_address` → `pc-characteristics_by_clips_tool` → analytics

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

  <Tab title="REST API (direct integration)">
    **Best for:** Teams building server-side integrations, data pipelines, or hybrid architectures

    Access property data, valuation models, and market analytics through standard REST endpoints with structured JSON responses.

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

    **Steps:**

    1. Request API credentials from your Cotality account representative
    2. Authenticate using OAuth2 client credentials flow
    3. Call the Property API, Insight API, or WVS API as needed

    [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)                                             | Universal property identifier lookup — convert any address to a CLIP | <Badge color="green">GA</Badge>     |
| [Property characteristics](/mcp/property-data/tools/property-characteristics)                 | 200+ fields of physical, structural, ownership, and tax data         | <Badge color="green">GA</Badge>     |
| [Market trend analytics](/mcp/market-trend-analytics/tools/analytics)                         | Listing trends, HPI, rental data by ZIP / county / CBSA / state      | <Badge color="green">GA</Badge>     |
| [Appraisal order agent](/ai-integrations/valuation-solutions/ai-agents#appraisal-order-agent) | Conversational order management — create, track, review              | <Badge color="purple">Alpha</Badge> |
| [Vendor order agent](/ai-integrations/valuation-solutions/ai-agents#vendor-order-agent)       | Vendor lifecycle management and auto-assignment                      | <Badge color="purple">Alpha</Badge> |
| [Compliance agent](/ai-integrations/valuation-solutions/ai-agents#compliance-agent)           | UAD validation and compliance findings                               | <Badge color="purple">Alpha</Badge> |

***

## Industry standards alignment

Cotality property data conforms to the dominant standards used in the mortgage and valuation industry:

* **MISMO residential XML (v3.x)** — Structure elements and GLA fields map directly to MISMO's `VALUATION_RESPONSE` container
* **FHFA UAD standards** — Property characteristic fields align with FHFA appraisal dataset requirements
* **USPS publication 28** — Address fields are pre-standardized using USPS postal addressing standards

***

## Get started

<Steps>
  <Step title="Identify your workflow">
    Determine whether you need order management (AI agents), data-in-AI-product (MCP), or direct integration (REST API)
  </Step>

  <Step title="Authenticate">
    Obtain credentials and [get your first access token](/mcp/authentication) — takes under five minutes
  </Step>

  <Step title="Test with MCP inspector">
    Use the [MCP inspector](/mcp/quickstart) to call property data tools interactively and validate your use case before writing code
  </Step>

  <Step title="Integrate">
    Follow the relevant integration guide for your client: [VS code / Cursor / Claude code](/mcp/connect), [Python](/mcp/python), or REST
  </Step>
</Steps>