Which Fraud Pattern Deserves the First Control?
Build frequency, loss and exposure-rate views; preserve a severe-event override; and choose a causal next step without claiming that a leading category is a root cause.
28 minutes
Scenario
A payment provider can fund one fraud-control experiment this quarter. Operations wants the most frequent category, finance wants the largest loss, and risk wants every severe event escalated. A detection rule changed halfway through the month, so raw counts are not directly comparable over time.
- Your role
- Fraud strategy analyst
- Method
- Pareto Analysis
Evidence pack
Account takeover
40 confirmed cases; €160,000 loss; 80,000 exposed remote-card transactions.
Merchant non-delivery
260 cases; €104,000 loss; 400,000 exposed purchase transactions.
Duplicate charge
190 cases; €19,000 loss; 500,000 exposed purchase transactions.
Cash withdrawal
12 cases; €144,000 loss; 40,000 exposed cash withdrawals.
Other
98 cases; €49,000 loss. The exposure population is mixed and 31% of records have no analyst note.
Detection change
A new account-takeover rule started on day 16; confirmed detections per day doubled while average loss per detected case fell 35%.
Risk threshold
Internal risk appetite requires immediate review of any single event above €25,000, regardless of category frequency.
Capacity
The experiment team can investigate one category deeply and add one low-effort containment control.
Constraints
- Frequency, total loss, loss per case and exposure rate answer different questions.
- Pre- and post-rule periods must be separated for account takeover.
- The Other category cannot be treated as homogeneous.
- A Pareto category is not a cause.
Case steps
Work through each prompt using the evidence pack. Answers and rubric weights stay protected in the interactive flow.
Choose the primary measure for this quarter's control investment and define two secondary views that protect against a misleading ranking.
Calculate loss per case and cases per 10,000 exposed transactions for e1–e4. Do not calculate a rate for Other.
Explain how e5–e7 limit a basic Pareto chart and specify the minimum data repair or stratification before committing the experiment.
Recommend one category for deep investigation and one low-effort containment control. Show why a reasonable analyst could choose differently.
Design the causal investigation and post-action measurement. Include a comparison group or period and a condition that would stop or redirect the experiment.