Use risk to order the review queue

Question for this chapter

Which of the 12 orders should a person review first?

Try it

Open the risk_assessment pipeline under refund_ops and select Run. The score combines past refund count, order amount, and customer tier on a 0.0–1.0 scale.

• Below 0.3: low
• 0.3 through 0.6: medium
• Above 0.6: high

Success looks like this

risk_assessed_orders contains 12 rows.

In the Data tab, expand SQL Scratch Pad, enter the query below, and select Run Query.

SELECT order_id, risk_score, risk_level
FROM `refund_ops`.`risk_assessed_orders`
ORDER BY risk_score DESC
LIMIT 5

The result lists the five orders by descending risk score.

The maximum 0.600 is still not high; the code requires a value above 0.6.

Trace one order relationship

Run ontology_materialization. It produces 10 customer rows, 12 order rows, 6 refund-request rows connected to current orders, and 18 relation rows.

1. In Graph Explorer, select this scenario's collection.
2. Select sales_order under Entities.
3. Select ORD-2025-0001 and confirm order_id in Node properties.
4. Inspect the refund-request and customer connections returned with the order.

The result should show RF-2025-005 → ORD-2025-0001 → CUS-001, placing risk and customer context around the same order.

Next decision

You have five orders to review first. Next, retrieve policy for a refund reason instead of deciding from the risk score alone.