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Design banking payment scheduling system

Last updated: Mar 29, 2026

Quick Overview

This interview question evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer for Design banking payment scheduling system states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  • hard
  • Circle
  • System Design
  • Software Engineer

Design banking payment scheduling system

Company: Circle

Role: Software Engineer

Category: System Design

Difficulty: hard

Interview Round: Take-home Project

##### Question Design and implement a banking payment system that: Adds a cancelPayment operation able to cancel a previously-scheduled payment. Extends schedulePayment to report and persist both success and failure results. Removes obsolete payment cases as required. Produces a report of outgoing transactions sorted by total loss amount.

Quick Answer: This interview question evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer for Design banking payment scheduling system states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

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|Home/System Design/Circle

Design banking payment scheduling system

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Circle
Aug 4, 2025, 10:55 AM
hardSoftware EngineerTake-home ProjectSystem Design
13
0

Design banking payment scheduling system

System Design: Banking Payment System Enhancements

Context

You are building a minimal bank-transfer payment orchestration service (e.g., ACH/SEPA) that schedules and executes outgoing payments. The system persists all state and exposes a simple HTTP API. Payments move through a state machine (e.g., SCHEDULED → QUEUED → PROCESSING → SENT → SETTLED/FAILED), and are executed by background workers.

Requirements

Design and implement the following features:

  1. cancelPayment
    • Add an operation to cancel a previously scheduled payment.
    • Only payments that haven't been irreversibly sent downstream can be canceled.
    • Define idempotent behavior, allowed states for cancellation, and race-condition handling.
  2. Extend schedulePayment
    • Ensure schedulePayment reports and persists both success and failure results (for both the scheduling action itself and the downstream execution attempts).
    • Include idempotency for client retries and durable audit logs for all results.
  3. Remove obsolete payment cases
    • Identify and remove any legacy/obsolete payment states or code paths.
    • Propose a safe data and code migration plan so production data remains consistent.
  4. Reporting
    • Produce a report of outgoing transactions sorted by total loss amount.
    • Define "loss" precisely, including returns/chargebacks and fees, and how recoveries/refunds affect it.
    • Provide a query or computation plan that aggregates and sorts by loss.

Deliverables

  • API design for schedulePayment and cancelPayment (request/response, status codes, idempotency semantics).
  • Payment state machine and concurrency rules.
  • Data model (tables/entities) for payments, attempts, events/audit, fees/returns.
  • Reporting definition with a query that produces the loss-sorted report.
  • Edge cases and validation strategy.

Constraints & Assumptions

  • Preserve the scope, facts, inputs, and requested outputs from the prompt above.
  • If the prompt leaves a detail unspecified, state a reasonable assumption before relying on it.
  • Keep the answer interview-ready: concise enough to present, but concrete enough to implement or evaluate.

Clarifying Questions to Ask Guidance

  • Clarify users, core use cases, read/write patterns, scale, latency, availability, and data retention.
  • State explicit assumptions before making sizing or architecture decisions.
  • Prioritize the functional path first, then address reliability, security, observability, and rollout.

What a Strong Answer Covers Guidance

  • A scoped requirements summary with concrete non-goals and success metrics.
  • API, data model, architecture, consistency, capacity, and operations.
  • Reasoned trade-offs among simple and scalable designs, including bottlenecks and failure modes.
  • A validation, monitoring, migration, and launch plan appropriate for the risk level.

Follow-up Questions Guidance

  • What breaks first at 10x traffic or data volume?
  • How would you degrade gracefully during dependency failures?
  • What metrics and alerts would prove the design is healthy after launch?

Submit Your Answer to Earn 20XP

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