# Provenance Impact Report

- Run ID: `20260807T140453Z-857303`
- State: **PUBLISHED**
- Started: 2026-08-07 14:04:53.120572+00:00
- Completed: 2026-08-07 14:04:58.493510+00:00

## Proposed Change

- Asset: `urn:li:dataset:(urn:li:dataPlatform:kafka,payments.authorized_transaction_events,PROD)`
- Source column: `device_trust_score`
- Scenario: device-trust-range-change
- Request: The device-risk producer will change device_trust_score from a 0–100 range to a 0–1 range without updating downstream expectations.
- Trigger event: `evt-dd8cd270-a249-4a94-9958-1328a6363c9d`
- Trigger source: `device-risk-deployment-agent`

## DataHub Context (through MCP)

- Source: `urn:li:dataset:(urn:li:dataPlatform:kafka,payments.authorized_transaction_events,PROD)` (payments.authorized_transaction_events)
- Selected field: `device_trust_score`
- Owners: `urn:li:corpGroup:payment-fraud-monitoring`
- Tags: Production, PaymentFraud, RealTimeML

### Complete lineage

| Hop | Upstream | Downstream | Relationship |
| ---: | --- | --- | --- |
| 1 | `urn:li:dataset:(urn:li:dataPlatform:kafka,payments.authorized_transaction_events,PROD)` | `urn:li:dataset:(urn:li:dataPlatform:postgres,fraud.realtime_payment_features,PROD)` | lineage |
| 2 | `urn:li:dataset:(urn:li:dataPlatform:postgres,fraud.realtime_payment_features,PROD)` | `urn:li:mlFeature:(realtime_payment_risk_features,device_trust_score)` | lineage |
| 3 | `urn:li:mlFeature:(realtime_payment_risk_features,device_trust_score)` | `urn:li:mlModel:(urn:li:dataPlatform:mlflow,payment_fraud_detector_v3,PROD)` | lineage |

### Affected models

- `urn:li:mlModel:(urn:li:dataPlatform:mlflow,payment_fraud_detector_v3,PROD)` ➔ payment_fraud_detector_v3

### Evidence URNs

- `urn:li:dataset:(urn:li:dataPlatform:kafka,payments.authorized_transaction_events,PROD)`
- `urn:li:dataset:(urn:li:dataPlatform:postgres,fraud.realtime_payment_features,PROD)`
- `urn:li:mlFeature:(realtime_payment_risk_features,device_trust_score)`
- `urn:li:mlModel:(urn:li:dataPlatform:mlflow,payment_fraud_detector_v3,PROD)`

## Experiment Plan

- Target asset: `urn:li:dataset:(urn:li:dataPlatform:kafka,payments.authorized_transaction_events,PROD)`
- Rationale Explanation: **_Reproduce the proposed device-score range change across the full evaluation population and measure its effect on the downstream fraud model._**
- Expected signals: AUC drop, prediction flip rate, mean absolute probability shift

| # | Operator | Column | Fraction | Value |
| ---: | --- | --- | ---: | --- |
| 1 | `scale_numeric` | `device_trust_score` | 1.0 | 0.01 |

## Observed Results

### Experiment 1: `scale_numeric`

- Column: `device_trust_score`
- Duration (_how long the mutation and mutated inference took_)[ms]: 17.902000000049156
- Error: n/a

| Metric | Observed value |
| --- | ---: |
| `baseline_auc` | 0.8092934782608696 |
| `mutated_auc` | 0.7495108695652174 |
| `auc_drop` | 0.05978260869565222 |
| `prediction_flip_rate` | 0.974 |
| `mean_absolute_probability_shift` | 0.8007552497510132 |
| `inference_error_rate` | 0.0 |

- Rows selected: 500 / 500
- Before summary: `{"maximum": 99.42, "mean": 72.66107999999998, "minimum": 22.51, "missing": 0}`
- After summary: `{"maximum": 0.9942000000000001, "mean": 0.7266107999999999, "minimum": 0.22510000000000002, "missing": 0}`

## Deterministic Decision

- Status: **BLOCK**
- Summary: Blocked by 2 deterministic safety rule(s).

### Triggered policy rules

| Experiment | Metric | Observed | Rule | Result | Reason |
| ---: | --- | ---: | --- | --- | --- |
| 1 | `auc_drop` | 0.05978260869565222 | > 0.05 | BLOCK | AUC drop 0.059783 exceeded block threshold 0.050000 |
| 1 | `prediction_flip_rate` | 0.974 | > 0.15 | BLOCK | Prediction flip rate 0.974000 exceeded block threshold 0.150000 |

## Publication

- Local JSON: `mockup_data/artifacts/runs/20260807T140453Z-857303.json`
- Local Markdown: `mockup_data/artifacts/runs/20260807T140453Z-857303.md`
- Remote succeeded: yes
- DataHub tag: Provenance-BLOCK
- DataHub document: urn:li:document:shared-1f1429aa-2bb7-42c8-b76b-d717065e3b58
- Remote error: n/a