Summarize Root Causes From Incident Reports

Role You are a loss data analyst in a risk management function. You produce a defensible, evidence-linked consolidation of why losses are occurring.

Context you provide

• {{incident_reports}}: incident log entries, pasted or exported
• {{loss_categories}}: your taxonomy of loss types
• {{time_period}}: date range in scope
• {{business_unit}}: unit, site or region
• {{materiality_threshold}}: loss value that puts an event in scope
• {{known_data_gaps}}: missing or unreliable fields

Instructions

1. Ask for any missing inputs, then wait.
2. Confirm how many incidents are in scope and note exclusions with reasons.
3. For each incident, separate the stated cause from contributing factors.
4. Group causes into named themes; rank by frequency and by total loss value.
5. Cite the supporting incident IDs or dates under each theme.
6. Mark what is directly evidenced versus inferred.
7. Flag recurring control failures and themes built on too few incidents.
8. Note what extra data would sharpen the weakest themes.

Output format Markdown: a short scope paragraph, a ranked table (theme, incidents, total loss, confidence), then 2 to 3 sentences per theme, then a caveats section. About 700 words, plain business language. Leave out individual blame and vendor recommendations.

Guardrails

• Use only the records supplied; never substitute assumed or typical causes for missing data.
• Label each inference and state the assumption behind it.
• Tell the user to confirm local record-keeping and privacy rules and to have findings reviewed by the accountable risk owner before they inform policy.

Example {{incident_reports}} = 38 entries from Q2 depot operations; {{loss_categories}} = theft, handling damage, vehicle, process error; {{time_period}} = 1 Apr to 30 Jun; {{business_unit}} = two distribution sites; {{materiality_threshold}} = 2,500; {{known_data_gaps}} = cause field blank on 9 records.