Assess Stripe Capital Strategy

Stripe is evaluating a merchant-financing product called Capital for existing merchants. Merchants are pre-qualified using Stripe's internal data. Approved merchants receive an upfront loan or cash advance, and repayment is collected automatically as 12% of the merchant's daily Stripe-processed revenue until the contracted total owed is repaid. Assume 12% is the repayment withholding rate, not an APR. As the data scientist supporting this product, answer the following: 1. Design a dashboard for Capital. What metrics would you track at the portfolio, cohort, and merchant level? Include growth, repayment health, credit risk, unit economics, and downstream merchant impact. Which metrics are leading indicators versus lagging indicators? 2. How would you decide that a pre-qualified merchant should not receive a loan offer? What early signals would you use to identify merchants who are unlikely to fully repay or whose repayment will be materially slower than expected? Discuss label definition, feature ideas, thresholding, and the trade-off between false positives and false negatives. 3. Stripe is considering offering merchants multiple loan options instead of a single pre-qualified amount. What are the pros and cons of multiple options versus a single option from the perspectives of merchant experience, risk selection, business performance, and operational complexity? How would you test which design is better? 4. Suppose Capital profitability declines. How would you diagnose the root cause in a structured way? Explain how you would separate the effects of demand, merchant mix, underwriting changes, repayment behavior, macro conditions, funding costs, seasonality, and possible measurement/accounting issues.