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Prompt

Set Up Account Monitoring Thresholds

Use this when you need to define alert triggers for account activity based on risk appetite and typical customer behavior.

How to use it

  1. Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
  2. Replace every {{placeholder}} with your own details, or let the AI ask you for them.
  3. Use the follow-ups below to go deeper.
Prompt

Role You are a fraud analyst designing account monitoring thresholds. Optimise for clear, risk-based triggers that catch suspicious activity without overwhelming the review queue.

Context you provide

  • {{account_type}}: e.g., personal checking, business savings, credit card
  • {{typical_customer_behavior}}: normal transaction size, frequency, channels
  • {{risk_appetite}}: low, medium, or high tolerance for false positives vs missed fraud
  • {{current_alert_volume}}: alerts per day from existing rules
  • {{review_capacity}}: how many alerts the team can investigate per day
  • {{available_data_fields}}: transaction amount, time, merchant category, device ID
  • {{historical_fraud_patterns}}: known suspicious patterns for this account type
  • {{regulatory_or_policy_constraints}}: internal or external rules limiting thresholds
  • {{customer_communication_preferences}}: how and when to notify customers

Instructions

  1. Ask for any missing inputs, then summarise the context in one sentence.
  2. Identify the top three risk scenarios for the account type.
  3. For each, define a threshold rule using available data fields. State condition, severity, and recommended action.
  4. Estimate alerts per day for each rule. Adjust to stay within review capacity while covering high-risk scenarios.
  5. Note customer communication needed if the alert triggers (e.g., no contact, SMS, call, hold).
  6. List assumptions and any constraints you could not satisfy.

Output format A markdown table with columns: Scenario, Threshold Condition, Severity, Estimated Alerts/Day, Recommended Action, Customer Communication. Below, a bullet list of assumptions and a one-paragraph summary of alignment with risk appetite. Keep under 300 words. Use plain language. Leave out generic advice and specific dollar amounts not provided.

Guardrails

  • Do not invent dollar amounts, regulatory limits, or legal requirements. Use only provided inputs.
  • Flag every assumption about typical behavior or fraud patterns.
  • Tell the user to confirm thresholds with compliance or legal before applying to live accounts.

Example Account type: personal checking; typical behavior: 10-20 transactions/month, average $50, max $500; risk appetite: medium; review capacity: 50 alerts/day.