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Company focus

Afterpay

What caused the sudden 30% increase in failed transactions for Afterpay's "Pay in 4" installment plan last week?

Prepared by NextSprints

15 mins
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Data Analysis Problem Solving Technical Understanding Fintech E-commerce Payments Fintech Root Cause Analysis Payment Processing Transaction Failures System Updates
Product Management Root Cause Analysis Question: Investigating sudden increase in Afterpay's failed transactions

Introduction

The sudden 30% increase in failed transactions for Afterpay's "Pay in 4" installment plan last week is a critical issue that demands immediate attention. This analysis will systematically identify, validate, and address the root cause while considering both short-term fixes and long-term implications for the product.

I'll approach this problem by first clarifying the context, then ruling out external factors before diving deep into the product's user journey and metrics. We'll generate data-driven hypotheses, conduct root cause analysis, and propose a comprehensive validation and resolution plan.

Framework overview

This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.

Step 1

Clarifying Questions (3 minutes)

  • Looking at the timing, I'm thinking this could be related to a recent system update. Has there been any significant change to the "Pay in 4" system in the past month?

Why it matters: System changes often correlate with performance issues. Expected answer: Yes, a minor update was rolled out two weeks ago. Impact on approach: If confirmed, we'd focus on the update's components and rollout process.

  • Considering user segments, I'm curious about the distribution of these failed transactions. Are they concentrated in a particular user group or spread evenly across all users?

Why it matters: Helps identify if it's a systemic issue or specific to certain users. Expected answer: The increase is seen across all user segments. Impact on approach: If evenly spread, we'd look at core system issues rather than user-specific factors.

  • Given the scale of the increase, I'm wondering about any changes in transaction volume. Has there been a significant spike in overall transaction attempts during this period?

Why it matters: Helps distinguish between increased failure rate and increased usage. Expected answer: Transaction volume has remained relatively stable. Impact on approach: If volume is stable, we'd focus on failure rate causes rather than scaling issues.

  • Considering potential data anomalies, has there been any change in how failed transactions are measured or reported in the last month?

Why it matters: Ensures we're dealing with a real issue, not a reporting anomaly. Expected answer: No changes to measurement or reporting systems. Impact on approach: If confirmed, we can rule out data integrity issues and focus on actual transaction failures.

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Updated Jan 22, 2025