Why has the average loan approval time for KoinWorks' KoinPintar applicants increased from 2 days to 5 days over the past month?

Introduction

The recent increase in KoinWorks' KoinPintar loan approval time from 2 to 5 days is a critical issue that demands immediate attention. This analysis will systematically identify, validate, and address the root cause while considering both short-term and long-term implications for the product and business.

I'll approach this problem by first clarifying key details, ruling out external factors, and then diving deep into the product, user journey, and metrics. From there, I'll form data-driven hypotheses, conduct root cause analysis, and propose validation methods and solutions.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might have been recent changes to the loan approval process. Have there been any updates to KoinPintar's approval criteria or workflow in the past month?

Why it matters: Changes in the process could directly impact approval times. Expected answer: Yes, there were some updates to credit scoring models. Impact on approach: If confirmed, I'd focus on analyzing the new criteria and their implementation.

• Considering user segments, I'm curious if this increase is uniform across all applicant types. Are we seeing the same 5-day average for both new and returning borrowers?

Why it matters: Helps identify if the issue is systemic or specific to certain user groups. Expected answer: The increase is more pronounced for new borrowers. Impact on approach: I'd investigate factors specific to new applicant onboarding and verification.

• Given the significant jump in processing time, I'm wondering about our current approval rate. Has the percentage of approved loans changed along with the increased processing time?

Why it matters: Could indicate if stricter criteria are causing both longer times and lower approvals. Expected answer: Approval rates have remained stable. Impact on approach: If stable, I'd focus more on operational bottlenecks rather than policy changes.

• Thinking about potential technical issues, have there been any reported problems with the loan processing system or integrations in the last month?

Why it matters: Technical glitches could be causing delays in the approval pipeline. Expected answer: Some intermittent issues with third-party data providers. Impact on approach: I'd prioritize investigating these technical integrations and their impact on the process.