Optimize Credit-Card Strategy: Pricing, Limits, and Target Segments
Overview
This question evaluates a data scientist's ability to construct and analyze credit-card unit-economics and risk-adjusted profitability models that connect pricing, credit limits, and customer segmentation within an analytics and experimentation context.
OneMain Financial
Jul 12, 2025, 6:59 PM
Data Scientist
Onsite
Analytics & Experimentation
10
0
Credit-Card Business Optimization Case
Context
You are evaluating a new credit-card product. You have (or will estimate) per-segment cost, revenue, and risk inputs such as acquisition cost, APR options, credit-limit options, interchange and rewards rates, servicing and funding costs, default risk, and churn/retention. Your goal is to choose an optimal go-to-market strategy.
Task
- Define the objective and the core unit-economics model (e.g., CLV/NPV or risk-adjusted return) that links pricing (APR), credit limit, and target segment to expected profitability.
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Show how you would use the provided figures to select:
- Pricing (APR tier)
- Initial credit limit
- Target segment(s) Include constraints (risk appetite, regulatory caps, fairness) and how you’d solve the optimization.
- If concrete numbers are missing, illustrate with a small numeric example using plausible inputs to demonstrate the method.
- List the key metrics you would track post-launch to measure success and to guard against risk or compliance issues.
Hints
- Consider acquisition cost (CAC), lifetime value (CLV), default risk (PD/LGD), churn, utilization, revolve behavior, interchange and rewards, funding and servicing costs.
Solution
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