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

# Multi-Accounting

> Understanding and preventing multi-accounting fraud with Verisoul

<img style={{ borderRadius: '0.5rem', maxWidth: '100%' }} src="https://mintcdn.com/verisoul/wdkmEtsUGEUd5DIj/images/accounts_linked.png?fit=max&auto=format&n=wdkmEtsUGEUd5DIj&q=85&s=2fdf4a5665f7e0d9e2d497d659958f33" alt="Accounts linked graph showing connections between related accounts" width="1528" height="805" data-path="images/accounts_linked.png" />

<div className="mt-6 mb-8">
  <p className="text-lg">
    Multi-accounting (also known as duplicate accounts) occurs when a single person creates and operates multiple accounts on your platform. This is a common fraud pattern that can lead to significant losses through promotional abuse, collusion, and other fraudulent activities.
  </p>
</div>

## Why Multi-Accounting Is a Problem

<CardGroup cols={2}>
  <Card title="Promotional Abuse" icon="gift" iconType="duotone">
    Claiming welcome bonuses, referral rewards, or discounts multiple times
  </Card>

  <Card title="Collusion" icon="people-arrows" iconType="duotone">
    Unfair advantages in gaming, gambling, or marketplace platforms
  </Card>

  <Card title="Fake Engagement" icon="thumbs-up" iconType="duotone">
    Creating artificial engagement or fake reviews
  </Card>

  <Card title="Resource Abuse" icon="server" iconType="duotone">
    Consuming limited resources or free trials repeatedly
  </Card>
</CardGroup>

## Components of Verisoul's Multi-Accounting Detection

Verisoul's multi-accounting detection system consists of several interconnected components that work together to provide an accurate risk assessment.

<Steps>
  <Step title="Match Types">
    Verisoul identifies three primary match types between accounts:

    <CardGroup cols={1}>
      <Card title="Browser Match" icon="browser" iconType="duotone">
        <div className="space-y-2">
          <p>The only deterministic match type with zero false positives</p>
          <p>Always results in a score of 1 (highest confidence)</p>
          <p>Based on browser-specific identifiers</p>
        </div>
      </Card>

      <Card title="Device Match" icon="laptop" iconType="duotone">
        <div className="space-y-2">
          <p>Based on hardware and software characteristics</p>
          <p>Includes device fingerprinting techniques</p>
          <p>Probabilistic with varying confidence levels</p>
        </div>
      </Card>

      <Card title="Network Match" icon="network-wired" iconType="duotone">
        <div className="space-y-2">
          <p>Analysis of network patterns and characteristics</p>
          <p>Includes IP address analysis and packet inspection</p>
          <p>Probabilistic with varying confidence levels</p>
        </div>
      </Card>

      <Card title="Email Match" icon="envelope" iconType="duotone">
        <div className="space-y-2">
          <p>Analyzes string similarity of normalized email addresses</p>
          <p>Strips special characters like dots (.) and plus (+) signs</p>
          <p>Identifies users creating variations of the same email</p>
        </div>
      </Card>
    </CardGroup>
  </Step>

  <Step title="Account-to-Account Scores">
    Each potential connection between two accounts receives a score (0-1) based on several factors:

    <div className="mt-4 space-y-3">
      <div>
        <strong>Match type strength</strong>: Browser matches (score 1) > Device matches > Network matches
      </div>

      <div>
        <strong>Number of sessions matched</strong>: More matching sessions increase confidence
      </div>

      <div>
        <strong>Fingerprint uniqueness</strong>:

        <ul className="list-disc pl-6 mt-1">
          <li>Globally unique fingerprints provide higher confidence</li>
          <li>Common fingerprints (seen frequently across many users) provide lower confidence</li>
        </ul>
      </div>

      <div>
        <strong>Time between sessions</strong>:

        <ul className="list-disc pl-6 mt-1">
          <li>Sessions close together in time provide stronger signals</li>
          <li>Sessions weeks apart provide weaker signals</li>
        </ul>
      </div>
    </div>

    <Tip>
      Two accounts sharing a unique device fingerprint across multiple sessions within minutes would receive a high account-to-account score, while two accounts sharing only a common network characteristic weeks apart would receive a low score.
    </Tip>
  </Step>

  <Step title="Multi-Accounting Probability">
    The `multiple_accounts` field is the culmination of all account-to-account scores, representing the overall likelihood that an account is part of a multi-accounting scheme:

    <div className="mt-4 space-y-3">
      <div>
        <strong>Range</strong>: 0 (no risk) to 1 (highest risk)
      </div>

      <div>
        <strong>Primary risk indicator</strong>: This is the most important field for assessing multi-accounting risk
      </div>
    </div>

    <div className="mt-4">
      This probability is calculated by:

      <ol className="list-decimal pl-6 mt-2">
        <li>Evaluating all account-to-account scores</li>
        <li>Considering the number of linked accounts</li>
        <li>Applying the accounts linked threshold configuration</li>
      </ol>
    </div>
  </Step>
</Steps>

## Accounts Linked Threshold

<Note>
  The accounts linked threshold is a configurable parameter that affects how the `multiple_accounts` field is calculated:

  <div className="mt-3 space-y-2">
    <div><strong>Default value</strong>: 1 (a single perfect match results in probability of 1)</div>
    <div><strong>Custom values</strong>: Can be adjusted based on your business needs</div>
    <div><strong>Example</strong>: Setting to 3 allows users to have up to 3 accounts before triggering high probability scores</div>
    <div><strong>Purpose</strong>: Helps reduce false positives while still preventing scaled fraud</div>
  </div>

  <div className="mt-3">
    <strong>Contact the Verisoul team</strong> to configure the accounts\_linked\_threshold for your specific use case.
  </div>
</Note>

## Accounts Linked API Response

When you query the Verisoul API for accounts linked to a specific account, you'll receive data about potential multi-accounting:

```json theme={null}
{
  "accounts_linked": [
    {
      "account_id": "account_1",
      "score": 1,        // Certain match
      "match_type": [
        "browser",
        "network",
        "device"
      ],
      "email": "account_1@example.com",
      "lists": [
        "allow"
      ],
      "metadata": {}
    },
    {
      "account_id": "account_2",
      "score": 0.3,       // Low confidence match
      "match_type": [
        "network"
      ],
      "email": "account_2@example.com",
      "lists": [
        "block"
      ],
      "metadata": {}
    }
  ]
}
```

## How Scores Roll Up Into Multi-Accounting Probability

The relationship between account-to-account scores and multiple accounts score:

<div className="mt-4 space-y-3">
  <div>
    <strong>1. Strong matches dominate</strong>: A single strong match (especially a browser match with score 1) can result in a high probability
  </div>

  <div>
    <strong>2. Quantity vs. quality</strong>: Many weak matches may not significantly increase probability
  </div>

  <div>
    <strong>3. Threshold application</strong>: The accounts\_linked\_threshold determines how many strong matches are needed for a high probability
  </div>
</div>

### Risk Examples

<CardGroup cols={1}>
  <Card title="High Risk" icon="circle-exclamation" iconType="duotone" color="#ff4d4f">
    An account with one perfect browser match (score 1) would likely have a high `multiple_accounts` score (near 1)
  </Card>

  <Card title="Medium Risk" icon="circle-question" iconType="duotone" color="#faad14">
    An account with several medium-strength device matches (scores 0.4-0.6) might have a moderate `multiple_accounts` score
  </Card>

  <Card title="Low Risk" icon="circle-check" iconType="duotone" color="#52c41a">
    An account with many low-strength network matches (scores 0.1-0.3) would likely have a low `multiple_accounts` score
  </Card>
</CardGroup>

## Why Fingerprints Aren't Returned

<div className="space-y-3">
  <div>
    <strong>1. Fraud prevention effectiveness</strong>: Raw fingerprints are easily changed by fraudsters who modify device attributes
  </div>

  <div>
    <strong>2. Stability issues</strong>: Fingerprints aren't exact, can have false positives, and aren't always stable
  </div>

  <div>
    <strong>3. Complexity</strong>: Resolving and actioning a graph database is complex
  </div>

  <div>
    <strong>4. Automation</strong>: Verisoul automates this process while remaining flexible enough to tune to your ecosystem
  </div>
</div>

## Viewing Account Linkages

The graph of linked accounts is viewable in the Verisoul dashboard and can be retrieved at any time via the accounts linked API. This provides a visual representation of potential multi-accounting clusters.

<Frame>
  <img src="https://mintcdn.com/verisoul/wdkmEtsUGEUd5DIj/images/dashboard_accounts_linked.png?fit=max&auto=format&n=wdkmEtsUGEUd5DIj&q=85&s=80ed095c3e83479340becda3334c24d0" alt="Accounts linked graph showing connections between related accounts" width="3416" height="1938" data-path="images/dashboard_accounts_linked.png" />
</Frame>