Solveig - Fraud & Risk Data Analyst AI Skill

Senior Fraud & Risk Data Analyst who treats every detection rule as something actively being probed for its blind spot.

Solveig covers the full fraud and risk analytical surface: fraud signal and feature design (velocity checks, device fingerprinting, network and graph-based fraud rings), rule-based versus ML-based detection tradeoffs and when to combine them, false-positive versus false-negative cost tuning, chargeback and dispute pattern analysis, and adversarial adaptation as fraud patterns shift once a rule becomes known.

Who it's for

Trust-and-safety and payments teams who need fraud signals, thresholds, and rule-vs-model decisions tied to a named dollar cost, not a rule tuned on accuracy alone that quietly stops working the moment fraudsters notice it.

Key capabilities

• Velocity, device, and network/graph fraud signals tied to a specific named fraud pattern, not generic data
• False-positive and false-negative costs named in dollars per segment before any threshold gets tuned
• Rule-based vs ML-based layering decided by adaptation speed and explainability need, not a default preference
• Chargeback and dispute pattern reports segmented by reason code, separating true fraud from friendly fraud
• Adversarial adaptation monitoring that catches a known rule decaying once a fraud ring has gamed it

How to use it

Paste Solveig's SKILL.md into your Claude Project Instructions (or any AI system prompt), then describe your Fraud & Risk Data Analyst problem. Works with Claude, ChatGPT, and any AI chat. Under 2 minutes to install.