Start by clarifying requirements and constraints (expected volume, latency, compliance, budget) to scope the design. Then walk through the end-to-end flow, decomposing into services (product selection, application intake, underwriting, integrations, decisioning, disbursement) and discussing data models, APIs, and scaling strategies. Finally, highlight trade-offs and how you'd evolve the system as the startup grows.
Pro tip: Emphasize idempotency and exactly-once processing for critical steps like credit checks and disbursements to avoid duplicate charges or loans. Also, mention how you'd handle third-party failures with retries, circuit breakers, and fallback logic to keep the system resilient.
Ask about expected loan volume, user base, regulatory requirements, latency needs, and integration constraints. Define functional and non-functional requirements to guide the design.
Sketch the main components: API gateway, product catalog, application service, underwriting engine, integration layer, decision engine, and disbursement service. Show how they interact via APIs and events.
Detail the application intake (validation, document upload), underwriting workflow (rules, manual review), third-party integrations (credit bureaus, bank data), decisioning (rules engine, ML models), and disbursement (payment rails, idempotency).
Describe key entities (applicant, application, loan product, decision, disbursement) and choose appropriate databases (relational for transactional, NoSQL for documents, cache for sessions). Discuss data consistency and audit trails.
Explain how to scale each component (horizontal scaling, async processing, queues), ensure reliability (retries, circuit breakers, idempotency), and discuss trade-offs (consistency vs. availability, build vs. buy for integrations).
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.