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

# Managing Fraud Score models

> Review Fraud Score model performance, choose a threshold, and approve new model versions in the Dashboard.

Go to **Fraud Score** > [**Models**](https://dashboard.fingerprint.com/fraud-score/models) to see your labels and their models. Use the **Web**, **iOS**, and **Android** tabs to switch between platforms.

The page has three sections:

* **Awaiting your approval**: new model versions ready for your review. Click **Review** to compare a version with the active model.
* **Needs attention**: issues that block training or reduce model quality, each with a suggested action.
* **Labels**: all your labels, with the latest model version, status, and the number of fraud and non-fraud events.

**issues in Needs attention**

| Issue | Description |
| - | - |
| **Uncategorized** | The label needs a category before it can train |
| **Requires data** | The label needs more fraud or non-fraud events to train |
| **Balance** | Too few events are labeled as non-fraud |
| **Same period** | Your non-fraud events don't cover enough of the period your fraud events cover |
| **Stale** | No new labels were submitted recently |
| **Expiry** | Many labeled events expire within a month |

**model statuses**

| Status | Description |
| - | - |
| **Requires data** | The label doesn't have enough labeled events to train |
| **Needs category** | The label needs a category before it can train |
| **Ready to train** | The label has enough data to train a new version |
| **Training** | Fingerprint is training a new version |
| **Under review** | Fingerprint is reviewing the new version for quality |
| **Pending approval** | The new version is ready for your review |
| **Active** | The model is scoring your events |

## Model details

Click a label to open its model details. Use the **Version** selector to switch between model versions.

The model details page shows:

* **Balance**: the number of fraud and non-fraud events the model trains on. Label at least as many non-fraud events as fraud events, and aim for about 10 non-fraud events for every fraud event.
* **Performance**: **Precision**, **Recall**, **PR-AUC**, **ROC-AUC**, and **F1**, measured on your labeled data. Expect lower precision on live traffic, where fraud is rarer than in your labeled data.
* **Health**: issues that affect this model, if any.
* **Top contributing signals**: the Smart Signals and device attributes that contributed most to the model's predictions.
* **Fraud score distribution**: where your recent traffic lands on the fraud score, and roughly how many events your current threshold flags.
* **Charts**: the ROC curve, the precision-recall curve, and precision, recall, and F1 at each threshold.
* **Version history**: past versions with their performance metrics. Discarded versions are on the **Discarded** tab.

## Choose a threshold

The threshold decides how high a score must be for Fraud Score to flag an event. A lower threshold catches more fraud but flags more legitimate events. A higher threshold flags fewer legitimate events but lets more fraud through.

To change it, open a label and select a **Threshold** option:

| Option | Use when |
| - | - |
| **Maximize recall** | You want to catch nearly all fraud |
| **Favor recall** | You lean toward catching fraud |
| **Balanced** | You want the best overall trade-off. A good default to start with. |
| **Favor precision** | You lean toward accurate flags |
| **Maximize precision** | You only want to flag near-certain fraud |

The threshold applies to all current and future models of the label, on all platforms. You can change it at any time.

## Review and approve a model version

When a new version is ready, it appears in **Awaiting your approval**. The active version keeps running until you approve the new one.

1. Click **Review** next to the version, or **Review changes** on the model details page.
2. Compare the new version with the active one. The changelog shows the change in labeled events, recall, false positive rate, precision, ROC-AUC, and PR-AUC.
3. Click **Approve changes** to make the new version active, or **Discard** to reject it. You must enter a reason to discard a version.

When you approve a version, the previous version is archived and stays in the version history. A discarded version stays in the version history but can't be used again.

## Auto-apply

To skip manual approval, select **Auto-apply safe models** in the review panel. Fingerprint then automatically applies future versions of the label that pass its internal safety checks. The setting applies to all platforms of the label.