# Fraud Detection

> Use to monitor, investigate, and prevent abuse within referral programs.

- Skill: `majiayu000/fraud-detection` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add majiayu000/fraud-detection`
- Raw SKILL.md: https://api.skillmd.com/api/skills/majiayu000/fraud-detection/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: majiayu000 (https://skillmd.com/u/majiayu000)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/majiayu000/fraud-detection

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# Referral Fraud Detection Skill

## When to Use
- Designing safeguards for new referral initiatives.
- Investigating suspicious referral spikes, duplicate accounts, or payout anomalies.
- Reporting on program integrity for finance, legal, or compliance teams.

## Framework
1. **Signal Collection** – IP/device matching, velocity checks, blacklist databases, manual reviews.
2. **Scoring Model** – assign risk scores by cohort (new accounts, high-volume referrers, geo mismatch).
3. **Workflow Automation** – auto-flag, queue for review, or pause rewards until verified.
4. **Investigation Runbook** – define evidence gathering, communication templates, and resolution paths.
5. **Feedback Loop** – update heuristics, adjust incentives, and communicate policy changes.

## Templates
- Fraud monitoring dashboard outline (metrics, thresholds, owners).
- Investigation log (case ID, referrer, signals, action taken, notes).
- Policy update checklist (legal, comms, ops, partner notifications).

## Tips
- Combine automated checks with random manual audits for accuracy.
- Align with legal/finance on clawback procedures before launch.
- Share learnings with `incentive-design` to discourage risky behavior.

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