> ## Documentation Index
> Fetch the complete documentation index at: https://docs.core3.io/llms.txt
> Use this file to discover all available pages before exploring further.

# CEX PoL Scoring Logic

> How exchange risk scores are calculated — category weighting, rationale, and the path from raw metrics to a single crypto risk score.

The centralized exchange probability of loss scoring logic is designed to provide a direct, transparent, and easily interpretable assessment of exchange-level risk. Unlike Project PoL, which must accommodate a wide variety of protocol structures, CEX risk factors are more standardized and therefore allow for a more straightforward scoring model.

The scoring system is based on three core risk categories, each assigned a fixed weight reflecting its relative impact on potential user loss.

## Category weighting — security, solvency, and transparency weights

The CEX PoL score is derived from a weighted aggregation of the following categories:

| Category         | Weight |
| ---------------- | ------ |
| **Security**     | 50%    |
| **Solvency**     | 30%    |
| **Transparency** | 20%    |

<Info>
  These weights are fixed and publicly disclosed to ensure predictability, comparability, and resistance to manipulation.
</Info>

## Why these weights — rationale behind the crypto risk metrics

<Tabs>
  <Tab title="Security (50%)">
    Security carries the highest weight due to the custodial nature of centralized exchanges. A failure in security controls can result in immediate and irreversible user fund losses.

    This category evaluates:

    * Infrastructure and operational security
    * User account protection mechanisms
    * Preventive and reactive security controls

    <Danger>
      Given historical loss patterns in the crypto market, security failures represent a significant amount of loss events for centralized exchanges, justifying the dominant weight. This weighting reflects the reality that digital asset security is the first line of defense against custodial loss.
    </Danger>
  </Tab>

  <Tab title="Solvency (30%)">
    Solvency reflects an exchange's ability to meet its financial obligations to users under both normal and stressed conditions.

    This category evaluates:

    * Existence and quality of proof-of-reserves audits
    * Ownership and scope of disclosed wallets
    * Coverage of user liabilities

    <Warning>
      While insolvency events may occur less frequently than security breaches, they tend to be systemic and market-wide, warranting a substantial but secondary weight.
    </Warning>
  </Tab>

  <Tab title="Transparency (20%)">
    Transparency assesses the exchange's willingness and ability to provide verifiable, up-to-date information that allows external stakeholders to independently assess risk.

    This category evaluates:

    * Live reserve disclosures
    * Liability snapshots and coverage ratios
    * Quality of public and institutional communication

    <Tip>
      Transparency acts as a risk amplifier or dampener—poor transparency increases uncertainty and loss severity, while strong transparency enables early detection and mitigation.
    </Tip>
  </Tab>
</Tabs>

## From raw metrics to a single crypto risk score

<Steps>
  <Step title="Category scoring" icon="calculator">
    Each category produces a normalized category score based on its constituent metrics.
  </Step>

  <Step title="Weighted aggregation" icon="scale-balanced">
    Category scores are combined using the predefined weights (50/30/20) to generate a single calculation score ranging from 0 to 100.
  </Step>

  <Step title="Inversion to PoL" icon="arrows-rotate">
    The calculation score is inverted to produce the final Probability of Loss (PoL):

    * **0 PoL** → Lowest probability of loss / highest confidence level
    * **100 PoL** → Highest probability of loss / lowest confidence level

    This inversion ensures intuitive interpretation: lower PoL scores indicate lower risk, while higher PoL scores signal elevated risk exposure.
  </Step>
</Steps>

## Use cases — from institutional risk frameworks to real-time monitoring

The simplicity of the CEX PoL scoring logic makes it particularly suitable for:

<Columns cols={2}>
  <Card title="Institutional risk frameworks" icon="landmark" horizontal>
    Integrate CEX PoL into portfolio risk management and counterparty evaluation workflows.
  </Card>

  <Card title="Regulatory oversight" icon="gavel" horizontal>
    Benchmark exchanges against each other using a standardized, audit-ready methodology.
  </Card>

  <Card title="Real-time monitoring" icon="bell" horizontal>
    Track score changes and receive alerts when exchange risk profiles shift.
  </Card>

  <Card title="API integrations" icon="code" horizontal>
    Feed PoL data into automated decision systems and third-party analytical tools.
  </Card>
</Columns>

<Check>
  By maintaining fixed weights and a deterministic calculation model, CORE3 ensures that CEX PoL scores remain stable, auditable, and resistant to subjective influence. This scoring approach supports crypto due diligence workflows where consistency and repeatability are non-negotiable.
</Check>