Strategy question

How might you think about implementing down payments for customers who cannot be approved for the full amount of a desired purchase?

Practice this question out loud. An AI interviewer asks it, follows up like a real interviewer would, and scores your answer. Type or speak.

What this question tests

Understanding of BNPL credit risk and how to design a partial-approval flow that still serves the customer and protects the lender.

Confirm why the customer was declined: a hard cap on exposure or a risk score below threshold, since the fix differs.
Define the target segment: near-prime borrowers Affirm rejects for the full ticket size but could serve at a lower amount.
Propose a partial-approval flow: approve a lower principal, require a down payment for the gap, and reassess after on-time payments.
Size the down payment by risk score, a higher risk borrower puts up a bigger upfront share to cut loss exposure.
Check merchant impact: does a partial approval still convert the sale, or does the added friction kill it.
State the guardrail: cap total exposure per borrower and monitor default rate on this new tier separately.

Ties the down payment percentage to risk tier, for example 20 percent for near-prime and 40 percent for subprime, as an assumption.
Notes this expands approval rate and merchant GMV while containing Affirm's loss rate, the real business tension.
Suggests testing with a small merchant cohort before a broad rollout.
Flags that repeat on-time payers should graduate to smaller down payments over time.

Chapters of the AI PM course that teach what this question tests.