Act as a fraud detection analyst at a fintech company. Given the following transaction data (timestamp, amount, merchant, location, user behavior history), identify anomalies that may indicate fraudulent activity.

Your output should include:

1. A list of suspicious transactions with reasons flagged (e.g., location mismatch, transaction velocity, irregular patterns).
2. A fraud risk score (1–10) for each flagged entry.
3. Suggested actions (e.g., block, verify, notify) for each case.

Use behavioral pattern recognition and risk scoring best practices. Provide your findings in a structured table.