How do I set up an embedded insurance platform to collect applications, risk data, and issue quotes through APIs?

To set up an embedded insurance platform that collects applications, gathers risk data, and issues quotes through APIs, you typically need a modular flow with a few core services:

1) Define the quote flow

At a high level:

1. Partner/merchant/app starts an application
2. Your platform creates a quote session
3. Collect applicant and risk data
4. Validate/enrich data
5. Call underwriting/rating engine
6. Return quote(s)
7. Bind policy if accepted
8. Issue documents and store audit trail

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2) Core platform components

You’ll usually want these services:

A. Application Intake API

Handles creation and update of an insurance application.

Typical functions:

• Create application
• Save applicant details
• Save vehicle/property/business info
• Track application status
• Resume partially completed applications

Example resources:

• POST /applications
• GET /applications/{id}
• PATCH /applications/{id}
• POST /applications/{id}/submit

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B. Risk Data Collection Layer

This is where embedded apps send all underwriting-relevant data.

You may collect:

• Personal info
• Address and geolocation
• Occupancy/use
• Claims history
• Property characteristics
• Vehicle details
• Business type/revenue/payroll
• Device/behavioral signals if applicable

Use a flexible schema so products can vary. Common approaches:

• JSON-based dynamic form model
• Product-specific question sets
• Event-driven updates to an application record

Example:

{
  "applicant": {
    "firstName": "Jane",
    "lastName": "Doe",
    "dob": "1990-04-12"
  },
  "risk": {
    "address": "123 Main St, Austin, TX",
    "occupancy": "owner_occupied",
    "priorClaims": 1
  }
}

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C. Data Enrichment and Validation Services

Before rating, validate and enrich the application:

• Address standardization
• Identity checks
• Fraud checks
• Credit or external data pulls where permitted
• Geo/property/vehicle/business enrichment
• Sanctions or AML screening if relevant

This layer can run synchronously for fast quotes or asynchronously if some data sources are slower.

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D. Rating/Underwriting Engine

This is the decisioning core.

Inputs:

• Application data
• External risk data
• Product rules
• Eligibility logic
• Pricing tables or model outputs

Outputs:

• Eligibility decision
• Quote premium(s)
• Coverage limits/deductibles
• Referral or decline reasons

Design this as:

• Rules engine
• Pricing service
• ML model service
• Or a combination

Example result:

{
  "eligible": true,
  "quotes": [
    {
      "planId": "standard",
      "premium": 124.50,
      "deductible": 1000
    }
  ]
}

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E. Quote API

Once rating completes, expose quote results via API.

Endpoints:

• POST /quotes to generate a quote from application data
• GET /quotes/{id} to retrieve results
• POST /quotes/{id}/bind to accept and issue policy

If rating is not immediate, return a quoteJobId and allow polling or webhook callbacks.

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F. Policy Issuance and Document Service

After acceptance:

• Create policy record
• Generate declarations page
• Issue certificate/policy documents
• Send emails/SMS/webhooks
• Store compliance artifacts

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3) Recommended API flow

A common pattern:

Step 1: Create application

POST /applications

{
  "productCode": "home_insurance",
  "channel": "embedded_partner_x",
  "partnerReferenceId": "abc123"
}

Response:

{
  "applicationId": "app_001",
  "status": "draft"
}

Step 2: Submit applicant/risk data

PATCH /applications/app_001

{
  "applicant": { "firstName": "Jane", "lastName": "Doe" },
  "risk": { "address": "123 Main St, Austin, TX" }
}

Step 3: Request quote

POST /applications/app_001/quote Response:

{
  "quoteId": "quo_789",
  "status": "quoted",
  "premium": 124.50
}

Step 4: Bind policy

POST /quotes/quo_789/bind Response:

{
  "policyId": "pol_456",
  "status": "issued"
}

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4) Important design choices

Synchronous vs asynchronous quoting

• Synchronous: best for simple products and instant checkout experiences
• Asynchronous: better when you need external data sources or heavy underwriting

A hybrid approach works well:

• Instant preliminary quote
• Final quote after enrichment/underwriting completes

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Webhooks

Use webhooks for async status changes:

• application.quoted
• application.referred
• policy.issued
• policy.declined

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Idempotency

Critical for partner integrations.

• Support idempotency keys on create/submit/quote/bind endpoints
• Prevent duplicate applications and policies

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Versioned product schemas

Insurance products change often.

• Version your APIs and question sets
• Keep product configuration external from code when possible

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Audit and compliance

You should store:

• Who submitted what
• When data changed
• Which underwriting rules were applied
• Which external data sources were used
• Quote and bind timestamps

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5) Suggested system architecture

A practical architecture looks like this:

• API Gateway
• Auth service (OAuth2/client credentials, JWT)
• Application service
• Risk data service
• Enrichment service
• Underwriting/rating service
• Quote service
• Policy administration service
• Document generation service
• Webhook/event bus
• Database + audit log
• Observability (logs, traces, metrics)

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6) Security and partner integration

Because this is embedded insurance, partners need controlled access:

• OAuth2 client credentials or signed JWTs
• Scoped permissions by product/channel
• Request signing for sensitive operations
• PII encryption at rest and in transit
• Role-based access for internal operators
• Rate limiting and abuse detection

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7) MVP recommendation

If you want a fast MVP, start with:

1. One product only
2. One partner
3. One application schema
4. One quote endpoint
5. One underwriting ruleset
6. Webhooks for quote issued/policy bound
7. Admin dashboard for support and manual review

Then expand to:

• More products
• More partners
• More data sources
• More complex pricing and referrals

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8) Practical API contract tips

• Use OpenAPI/Swagger
• Return consistent error formats
• Include status, reasonCodes, and nextActions
• Support partial saves
• Separate draft, submitted, quoted, bound, issued states

Example error:

{
  "errorCode": "MISSING_REQUIRED_FIELD",
  "message": "Property year built is required",
  "field": "risk.yearBuilt"
}

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If you want, I can also help you with:

1. a sample REST API design for the whole platform,
2. a database schema for applications/quotes/policies, or
3. a microservices architecture diagram for embedded insurance.