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

# Adverse Media Screening (Individual)

> Screen individuals for negative news and media coverage

The Individual Adverse Media Screening check searches for negative news articles, media coverage, and online content associated with an individual. This check helps identify reputational risks, criminal activities, and other adverse information.

## Overview

The check examines:

* Criminal convictions and charges
* Fraud and financial crimes
* Regulatory enforcement actions
* Civil litigation
* Corruption and bribery allegations
* Money laundering connections
* Terrorist financing links
* Human rights violations

## Running the Check

### API Endpoint

```bash theme={null}
POST https://api.parcha.ai/api/v1/startKYCAgentJob
```

<Warning>
  **Important**: You must use your own agent key, not a default or public agent key. Your agent key can be found in the Parcha dashboard under your agent's settings, or in the "Test API Integration" dialog.
</Warning>

### Request Parameters

<ParamField body="agent_key" type="string" required>
  Your KYC agent key from the Parcha dashboard. This is unique to your organization and agent configuration.
</ParamField>

<ParamField body="kyc_schema" type="object" required>
  The individual information for screening using the [KYC Schema](/schemas/individual-schema).

  <Expandable title="KYC Schema Properties">
    <ParamField body="id" type="string" required>
      A unique identifier for this KYC case.
    </ParamField>

    <ParamField body="self_attested_data" type="object" required>
      <ParamField body="first_name" type="string" required>
        Individual's first name.
      </ParamField>

      <ParamField body="last_name" type="string" required>
        Individual's last name.
      </ParamField>

      <ParamField body="middle_name" type="string">
        Individual's middle name.
      </ParamField>

      <ParamField body="date_of_birth" type="string">
        Date of birth (YYYY-MM-DD format) for better matching.
      </ParamField>

      <ParamField body="country_of_residence" type="string">
        Country of residence (ISO 3166-1 alpha-2).
      </ParamField>

      <ParamField body="address" type="object">
        Address information for context.
      </ParamField>
    </ParamField>
  </Expandable>
</ParamField>

<ParamField body="check_ids" type="array">
  Optional. To run only this specific check, include `["kyc.adverse_media_screening_check_v2"]`. If omitted, all checks configured in your agent will run.
</ParamField>

### Example Request

<CodeGroup>
  ```bash cURL theme={null}
  curl -X POST 'https://api.parcha.ai/api/v1/startKYCAgentJob' \
  -H 'Authorization: Bearer YOUR_API_KEY' \
  -H 'Content-Type: application/json' \
  -d '{
    "agent_key": "your-kyc-agent-key",
    "kyc_schema": {
      "id": "adverse-media-check-001",
      "self_attested_data": {
        "first_name": "John",
        "last_name": "Smith",
        "middle_name": "David",
        "date_of_birth": "1975-08-20",
        "country_of_residence": "US",
        "address": {
          "city": "Miami",
          "state": "FL",
          "country_code": "US"
        }
      }
    },
    "check_ids": ["kyc.adverse_media_screening_check_v2"]
  }'
  ```

  ```python Python theme={null}
  import requests

  api_key = 'YOUR_API_KEY'
  url = 'https://api.parcha.ai/api/v1/startKYCAgentJob'

  headers = {
      'Authorization': f'Bearer {api_key}',
      'Content-Type': 'application/json'
  }

  data = {
      'agent_key': 'your-kyc-agent-key',  # Replace with your actual agent key
      'kyc_schema': {
          'id': 'adverse-media-check-001',
          'self_attested_data': {
              'first_name': 'John',
              'last_name': 'Smith',
              'middle_name': 'David',
              'date_of_birth': '1975-08-20',
              'country_of_residence': 'US',
              'address': {
                  'city': 'Miami',
                  'state': 'FL',
                  'country_code': 'US'
              }
          }
      },
      'check_ids': ['kyc.adverse_media_screening_check_v2']  # Optional: run only this check
  }

  response = requests.post(url, json=data, headers=headers)
  print(response.json())
  ```

  ```typescript TypeScript theme={null}
  import axios from 'axios';

  const apiKey = 'YOUR_API_KEY';
  const url = 'https://api.parcha.ai/api/v1/startKYCAgentJob';

  const data = {
    agent_key: 'your-kyc-agent-key',  // Replace with your actual agent key
    kyc_schema: {
      id: 'adverse-media-check-001',
      self_attested_data: {
        first_name: 'John',
        last_name: 'Smith',
        middle_name: 'David',
        date_of_birth: '1975-08-20',
        country_of_residence: 'US',
        address: {
          city: 'Miami',
          state: 'FL',
          country_code: 'US'
        }
      }
    },
    check_ids: ['kyc.adverse_media_screening_check_v2']  // Optional: run only this check
  };

  axios.post(url, data, {
    headers: {
      'Authorization': `Bearer ${apiKey}`,
      'Content-Type': 'application/json'
    }
  })
  .then(response => console.log(response.data))
  .catch(error => console.error('Error:', error));
  ```
</CodeGroup>

### Initial Response

```json theme={null}
{
  "id": "job-abc123",
  "status": "PENDING",
  "created_at": "2024-02-15T10:30:00Z",
  "updated_at": "2024-02-15T10:30:00Z",
  "agent_id": "your-agent-key",
  "input_payload": {
    // Original request payload
  }
}
```

## Retrieving Check Results

Once the job is complete, retrieve the results using the job ID with the `getJobByID` endpoint. Make sure to include the `include_check_results=true` parameter to get the full check results.

```bash theme={null}
GET https://api.parcha.ai/api/v1/getJobByID?job_id=job-abc123&include_check_results=true
```

## Check Process

The adverse media screening check follows these steps:

1. **Media Search**
   * Searches news databases and archives
   * Queries legal and court records
   * Searches regulatory enforcement databases
   * Scans social media and online forums

2. **Content Analysis**
   * Identifies articles mentioning the individual
   * Analyzes context and severity
   * Categorizes adverse events
   * Filters out irrelevant or positive mentions

3. **Identity Verification**
   * Confirms the article refers to the screened individual
   * Cross-references location and dates
   * Evaluates name uniqueness
   * Reduces false positives

4. **Risk Assessment**
   * Categorizes findings by severity
   * Determines match confidence
   * Evaluates recency and relevance
   * Provides risk rating

## Check Results

### Response Structure

```typescript theme={null}
{
  type: "AdverseMediaScreeningCheckResult";
  passed: boolean;
  articles: Array<AdverseMediaArticle>;
  total_articles: number;
  summary: {
    high_severity_count: number;
    medium_severity_count: number;
    low_severity_count: number;
    categories: Array<string>;
  };
  screening_date: string;
}

type AdverseMediaArticle = {
  title: string;
  url?: string;
  publication_date: string;
  source: string;
  excerpt: string;
  match_rating: "strong_match" | "partial_match" | "weak_match" | "false_positive";
  match_score: number;
  category: string;
  severity: "high" | "medium" | "low";
  topics: Array<string>;
  locations?: Array<string>;
  individuals_mentioned?: Array<string>;
}
```

### Adverse Media Categories

* **Financial Crime**: Fraud, embezzlement, money laundering, tax evasion
* **Violent Crime**: Assault, murder, terrorism
* **Corruption**: Bribery, kickbacks, conflicts of interest
* **Regulatory Action**: SEC enforcement, banking violations, licensing actions
* **Civil Litigation**: Lawsuits, class actions, settlements
* **Sanctions/Watchlists**: Sanctions violations, watchlist additions
* **Cybercrime**: Hacking, data breaches, identity theft
* **Human Rights**: Forced labor, human trafficking, rights violations
* **Drug Trafficking**: Drug-related offenses and trafficking
* **Organized Crime**: Gang activity, racketeering, organized criminal enterprises

### Example Results

<CodeGroup>
  ```json Low Risk - No Adverse Media theme={null}
  {
    "type": "AdverseMediaScreeningCheckResult",
    "passed": true,
    "articles": [],
    "total_articles": 0,
    "summary": {
      "high_severity_count": 0,
      "medium_severity_count": 0,
      "low_severity_count": 0,
      "categories": []
    },
    "screening_date": "2024-02-15T10:30:00Z"
  }
  ```

  ```json Medium Risk - Old Minor Offense theme={null}
  {
    "type": "AdverseMediaScreeningCheckResult",
    "passed": true,
    "articles": [
      {
        "title": "Local Man Charged with DUI",
        "url": "https://example-news.com/article-123",
        "publication_date": "2015-06-12",
        "source": "Miami Herald",
        "excerpt": "John David Smith, 40, of Miami, was arrested last night on suspicion of driving under the influence...",
        "match_rating": "partial_match",
        "match_score": 78,
        "category": "Criminal Activity",
        "severity": "low",
        "topics": ["DUI", "Traffic Offense"],
        "locations": ["Miami, FL"],
        "individuals_mentioned": ["John David Smith"]
      }
    ],
    "total_articles": 1,
    "summary": {
      "high_severity_count": 0,
      "medium_severity_count": 0,
      "low_severity_count": 1,
      "categories": ["Criminal Activity"]
    },
    "screening_date": "2024-02-15T10:30:00Z"
  }
  ```

  ```json High Risk - Financial Crime theme={null}
  {
    "type": "AdverseMediaScreeningCheckResult",
    "passed": false,
    "articles": [
      {
        "title": "Former Bank Executive Convicted of Fraud",
        "url": "https://example-news.com/article-456",
        "publication_date": "2023-11-08",
        "source": "Wall Street Journal",
        "excerpt": "John David Smith, 48, a former senior executive at Global Bank, was convicted today on 15 counts of wire fraud and money laundering in connection with a $50 million embezzlement scheme...",
        "match_rating": "strong_match",
        "match_score": 95,
        "category": "Financial Crime",
        "severity": "high",
        "topics": ["Fraud", "Money Laundering", "Embezzlement"],
        "locations": ["Miami, FL", "New York, NY"],
        "individuals_mentioned": ["John David Smith", "Global Bank"]
      },
      {
        "title": "SEC Charges Smith with Securities Fraud",
        "url": "https://example-news.com/article-457",
        "publication_date": "2023-05-22",
        "source": "Reuters",
        "excerpt": "The Securities and Exchange Commission today charged John D. Smith with securities fraud for allegedly misleading investors...",
        "match_rating": "strong_match",
        "match_score": 92,
        "category": "Regulatory Action",
        "severity": "high",
        "topics": ["Securities Fraud", "SEC Enforcement"],
        "locations": ["Miami, FL"],
        "individuals_mentioned": ["John D. Smith"]
      }
    ],
    "total_articles": 2,
    "summary": {
      "high_severity_count": 2,
      "medium_severity_count": 0,
      "low_severity_count": 0,
      "categories": ["Financial Crime", "Regulatory Action"]
    },
    "screening_date": "2024-02-15T10:30:00Z"
  }
  ```
</CodeGroup>

## Risk Factors

The check may flag concerns if:

* Recent financial crime convictions or charges
* Money laundering or terrorist financing connections
* Regulatory enforcement actions
* Repeated patterns of adverse behavior
* High-severity crimes (violent crimes, serious fraud)
* Association with sanctioned entities or individuals
* Involvement in corruption or bribery schemes

## Search Strategies

The check can use multiple search strategies:

* **OPOINT**: Premium adverse media database
* **SERP\_GOOGLE\_NEWS**: Google News search
* **SERP\_GOOGLE\_SEARCH**: General web search
* **LEGAL\_DATABASES**: Court records and legal filings
* **REGULATORY\_DATABASES**: SEC, FINRA, other regulatory sources

## Best Practices

1. **Use Complete Names**: Include middle name for better matching
2. **Provide Location**: Helps filter false positives
3. **Set Age Cutoff**: Focus on recent news (typically 2-5 years)
4. **Review Match Quality**: Verify articles refer to the correct person
5. **Consider Context**: Not all adverse media is disqualifying
6. **Combine Checks**: Use with sanctions and PEP screening
7. **Update Regularly**: Rescreen periodically as new articles appear

## Configuration Options

* **article\_limit**: Maximum articles to analyze (default: 250)
* **search\_strategies**: Select search methods
* **age\_cutoff**: Years of historical data to search (default: 2)
* **vendor**: Choose screening vendor
* **filter\_non\_perpetrators**: Exclude articles where person is victim
* **adverse\_media\_topic\_filter**: Filter by specific topics
* **match\_addresses**: Cross-check addresses to improve accuracy
* **include\_civil\_cases**: Include civil litigation

## Related Checks

* [PEP Screening (Individual)](/checks/kyc-pep-screening-check) - Screen for PEP status
* [Sanctions Screening (Individual)](/checks/kyc-sanctions-screening-check) - Screen sanctions lists
* [Person Web Presence Check](/checks/kyc-person-web-presence-check) - Research online presence
* [Adverse Media Screening (Business)](/checks/adverse-media-screening) - Screen associated businesses