Welcome to the Parcha Case Schema Documentation. This guide is designed to help you understand and effectively use Parcha’s API for case management in financial and regulatory compliance contexts.

Parcha’s case management system is built on three main schemas, each tailored to handle different types of entities:

  1. Business Schema (KYB - Know Your Business)
  2. Individual Schema (KYC - Know Your Customer)
  3. Associated Entity Schema (AE)

These schemas are designed to be flexible and adaptable to various use cases, from comprehensive due diligence to simpler categorization tasks. While our schemas support a wide range of fields to accommodate complex scenarios, many fields are optional. This allows you to provide only the information relevant to your specific use case.

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Schema Details

For detailed information about each schema, please refer to the following resources:

Business Schema (KYB)

Learn about the fields and structure of the Business Schema used for Know Your Business (KYB) processes.

Individual Schema (KYC)

Explore the Individual Schema used for Know Your Customer (KYC) processes and understand its components.

Associated Entity Schema

Understand how to structure information about entities associated with the main business or individual.

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Example Use Cases

Below are examples of how these schemas can be used in different scenarios:

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Simple Example: Industry Categorization

For simpler use cases, such as industry categorization, you might only need to provide minimal information. Here’s an example of how a request for industry categorization might look:

{
  "id": "example-industry-cat-1",
  "self_attested_data": {
    "website": "https://example.com"
  }
}

In this case, we’re only providing the case ID and the business website, which is often sufficient for basic industry categorization tasks.

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Simple KYC Example: Adverse Media Check

For individual-focused tasks like adverse media checks, you might need just a few key pieces of information about an individual. Here’s an example of a simple KYC case for an adverse media check:

{
  "id": "example-kyc-adverse-media-1",
  "associated_individuals": [
    {
      "id": "individual-1",
      "self_attested_data": {
        "first_name": "John",
        "last_name": "Doe",
        "date_of_birth": "YYYY-MM-DD",
        "country_of_residence": "US"
      }
    }
  ]
}

This example provides just enough information to perform an adverse media check on an individual: their name, date of birth, and country of residence.

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Comprehensive Example

For more complex use cases, such as full KYB/KYC processes, you might need to provide more detailed information. Below is an example of a more comprehensive case schema:

{
  "id": "example-agent-group-test",
  "self_attested_data": {
    "business_name": "Example Corp",
    "registered_business_name": "Example Corporation Inc.",
    "address_of_operation": {
      "street_1": "123 Main St",
      "street_2": "Suite 100",
      "city": "Anytown",
      "state": "ST",
      "country_code": "US",
      "postal_code": "12345"
    },
    "address_of_incorporation": {
      "street_1": "456 Business Ave",
      "city": "Corporateville",
      "state": "ST",
      "country_code": "US",
      "postal_code": "67890"
    },
    "website": "https://example.com",
    "business_purpose": "B2B Software as a Service",
    "description": "AI-powered software solutions for business automation.",
    "industry": "Technology",
    "tin_number": "XX-XXXXXXX",
    "incorporation_date": "YYYY-MM-DD",
    "partners": [
      "Partner Ventures"
    ],
    "customers": [
      "Customer Inc"
    ],
    "source_of_funds": [
      "Investment",
      "Revenue"
    ]
  },
  "associated_individuals": [
    {
      "id": "example-kyc-test-1",
      "self_attested_data": {
        "first_name": "John",
        "middle_name": "Michael",
        "last_name": "Doe",
        "date_of_birth": "YYYY-MM-DD",
        "address": {
          "street_1": "789 Residential St",
          "city": "Hometown",
          "state": "ST",
          "country_code": "US",
          "postal_code": "54321"
        },
        "country_of_nationality": "US",
        "country_of_residence": "US",
        "place_of_birth": "Birthtown, State",
        "sex": "Male",
        "email": "john@example.com",
        "phone": "+1234567890",
        "title": "CEO",
        "is_applicant": true,
        "is_business_owner": true,
        "business_ownership_percentage": 50
      }
    },
    {
      "id": "example-kyc-test-2",
      "self_attested_data": {
        "first_name": "Jane",
        "middle_name": "Elizabeth",
        "last_name": "Smith",
        "date_of_birth": "YYYY-MM-DD",
        "address": {
          "street_1": "101 Home Ave",
          "city": "Villagetown",
          "state": "ST",
          "country_code": "US",
          "postal_code": "98765"
        },
        "country_of_nationality": "US",
        "country_of_residence": "US",
        "place_of_birth": "Origintown, State",
        "sex": "Female",
        "email": "jane@example.com",
        "phone": "+0987654321",
        "title": "Chief Technology Officer",
        "is_applicant": false,
        "is_business_owner": true,
        "business_ownership_percentage": 50
      }
    }
  ],
  "associated_entities": [
    {
      "id": "example-ubo-test-1",
      "self_attested_data": {
        "business_name": "Partner Ventures",
        "is_trust": false,
        "address": {
          "street_1": "202 Investor Blvd",
          "street_2": "Floor 10",
          "city": "Metropolis",
          "state": "ST",
          "country_code": "US",
          "postal_code": "13579"
        },
        "industry": "Venture Capital",
        "tin_number": null,
        "business_ownership_percentage": 10,
        "country_code": "US",
        "website": "www.partnerventures.com",
        "description": "Partner Ventures is a venture capital firm based in Metropolis, State. The firm invests in various technology-based sectors including artificial intelligence, blockchain, and software as a service."
      }
    }
  ]
}

This comprehensive example showcases how you can provide detailed information about a business, its associated individuals, and related entities when needed for more complex compliance and due diligence processes.

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Next Steps

Now that you understand the structure of our case schemas, explore these resources to make the most of the Parcha API:

The Anatomy of a Parcha Agent

Learn about the components and structure of a Parcha Agent.

API Documentation

Dive into our comprehensive API documentation to understand all available endpoints and features.

Use Cases

Explore example KYB and KYC workflows to see how Parcha can enhance your compliance processes.

QuickstartAnatomy of a parcha agent