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

# Score Range and Interpretation

> How Avra delivers credit scores, probability of default, and embeddings — and how to use them.

## What you receive

Every credit prediction includes three artifacts:

<AccordionGroup>
  <Accordion title="Credit Score (0–1000)" icon="gauge-high">
    A transformed, calibrated score for easy integration with your existing decision engines and policy rules.

    * **1000** = lowest risk (probability of default approaches 0%)
    * **0** = highest risk (probability of default approaches 100%)
  </Accordion>

  <Accordion title="Probability of Default (PD)" icon="chart-line">
    The raw probability behind the score — calibrated to your delinquency definition.

    * **Direct interpretation** — "this entity has a 15% chance of defaulting under your definition"
    * **Pricing and reserves** — calibrated probabilities for risk-based pricing, IFRS 9 staging, and capital allocation
    * **Multi-horizon** — PD is returned across 30, 60, 90, 180, and 365-day windows so each decision uses the horizon that matches its policy
  </Accordion>

  <Accordion title="Avra Embeddings" icon="cube">
    1024-dimensional representations of each entity.

    * **Similarity analysis** — find entities with similar risk profiles
    * **Feature engineering** — enhance your own models with relationship-aware features
    * **Custom analytics** — segmentation, monitoring, and anomaly detection
  </Accordion>
</AccordionGroup>

## How the score is constructed

The 0–1000 score is derived from the underlying probability of default through a calibrated transformation. The relationship is monotonic — a higher score is always lower risk — and stable across model versions, so policy thresholds you set today continue to hold meaning as the underlying foundations improve.

```json theme={null}
{
  "score": 842,
  "pd_30d": 0.004,
  "pd_60d": 0.006,
  "pd_90d": 0.011,
  "pd_180d": 0.024,
  "pd_365d": 0.051,
  "risk_band": "low",
  "key_factors": [
    "Stable counterparty network",
    "Positive trajectory over last 6 months",
    "Sector health above baseline"
  ]
}
```

### Multi-horizon PD fields

| Field     | Horizon  | Use case                                |
| --------- | -------- | --------------------------------------- |
| `pd_30d`  | 30 days  | Short-term liquidity, payment timing    |
| `pd_60d`  | 60 days  | Trade credit, early delinquency         |
| `pd_90d`  | 90 days  | Standard credit bureau equivalent       |
| `pd_180d` | 180 days | Medium-term portfolio planning          |
| `pd_365d` | 365 days | Annual loss forecasting, IFRS 9 staging |

Each horizon is independently calibrated. The 30-day PD is not a scaled 365-day PD — different signals matter at different time scales, and the model exposes them separately so each policy can pick its own window.

## Defining delinquency

The definition of a "bad" outcome is **defined by you**. During onboarding we work with you to label your historical accounts as good or bad based on your operational definition. Common examples:

* **MOB 6 > 30** — account is more than 30 days past due in the 6th month on book
* **FPD 90** — first payment default after 90 days
* **Charge-off** — debt written off as a loss

The downstream credit model is trained on top of your RFM using your labels. The 0–1000 scale is calibrated to reflect the probability of *your* specific outcome, not a generic default definition.

## Score bands

To simplify decision-making, scores group into operational risk bands. The table below is a general guide; exact PD per band shifts with your delinquency definition, but the monotonic relationship (higher score = lower risk) always holds.

| Score Range    | Risk Band      | Interpretation & Recommended Action                                           |
| :------------- | :------------- | :---------------------------------------------------------------------------- |
| **900 – 1000** | Exceptional    | Prime profile; minimal risk. Suitable for automated approval, highest limits. |
| **800 – 899**  | Low Risk       | Very strong profile. Confidently approve with favorable terms.                |
| **700 – 799**  | Moderate Risk  | Good profile. Generally safe to approve, may consider standard terms.         |
| **600 – 699**  | Medium Risk    | Warrants caution. May require additional review, lower limits, or collateral. |
| **400 – 599**  | High Risk      | Significant risk of default. Requires strict terms, guarantees, or denial.    |
| **0 – 399**    | Very High Risk | Extreme risk. Not recommended for credit extension.                           |

## Why probability matters more than the score alone

The 0–1000 score is convenient for decision rules. The underlying probability is what gives you the business intelligence to:

* **Price accurately** — set rates based on actual expected loss
* **Manage portfolios** — calculate reserves and capital requirements
* **Monitor trends** — track how risk evolves over time
* **Compare segments** — understand variations across customer types