Why has the average time to close for Kiavi's fix-and-flip loans increased from 14 to 21 days in the past 60 days?

Introduction

The increase in average time to close for Kiavi's fix-and-flip loans from 14 to 21 days over the past 60 days is a significant operational challenge that requires immediate attention. This analysis will systematically identify, validate, and address the root cause while considering both short-term fixes and long-term strategic implications.

To tackle this issue, I'll follow a structured approach that covers issue identification, hypothesis generation, validation, and solution development. My goal is to provide a comprehensive analysis that not only resolves the current problem but also strengthens our processes for the future.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might be seasonal factors at play. Have we seen similar patterns in loan processing times during this period in previous years?

Why it matters: Seasonal trends could explain the increase and inform our solution approach. Expected answer: No significant seasonal patterns observed in previous years. Impact on approach: If seasonal, we'd focus on scaling resources during peak times; if not, we'd look deeper into internal processes.

• Considering the specific timeframe, I'm curious about any recent changes to our loan approval process. Have we implemented any new policies or technologies in the past 90 days?

Why it matters: Recent changes could directly impact processing times. Expected answer: A new risk assessment tool was implemented 75 days ago. Impact on approach: If changes were made, we'd scrutinize their impact; if not, we'd investigate other internal factors.

• Given the nature of fix-and-flip loans, I'm wondering about market conditions. Has there been a significant shift in the types of properties or borrowers we're seeing in the past 60 days?

Why it matters: Changes in market dynamics could affect loan complexity and processing times. Expected answer: Slight increase in higher-value properties, but no major shift. Impact on approach: If market changes are significant, we'd adapt our processes; if not, we'd focus on internal efficiencies.

• Thinking about our operational capacity, has there been any notable change in our loan processing team's size or structure recently?

Why it matters: Staffing changes could directly impact processing times. Expected answer: No significant changes in team size or structure. Impact on approach: If staffing is stable, we'd look at process inefficiencies; if not, we'd address resource allocation.

• Considering the possibility of data anomalies, can you confirm that the definition of "time to close" has remained consistent and that our measurement systems are functioning correctly?

Why it matters: Ensures we're addressing a real issue, not a measurement error. Expected answer: Definition and measurement systems are consistent and accurate. Impact on approach: If confirmed, we proceed with analysis; if not, we'd first address data integrity issues.