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Product Management Tradeoff Question: Balancing loan approval rates and default risk for Upstart's AI-powered lending platform
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Vinay

Updated Dec 28, 2024

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How should Upstart balance increasing loan approval rates versus maintaining low default rates for its personal loan product?

Product Trade-Off Hard Member-only
Data Analysis Risk Assessment Strategic Decision-Making Fintech Banking AI
Product Strategy Data Analysis Fintech Risk Management AI Lending

Introduction

Balancing loan approval rates and default rates is a critical trade-off for Upstart's personal loan product. This scenario involves weighing the potential for increased revenue against the risk of financial losses and reputational damage. I'll analyze this trade-off by examining key metrics, designing experiments, and proposing a decision framework to guide our strategy.

Analysis Approach

I'll start by asking clarifying questions, then dive into product understanding, metrics identification, and experiment design. We'll conclude with a data analysis plan and decision framework to guide our approach.

Step 1

Clarifying Questions (3 minutes)

  • Based on recent market trends, I'm thinking Upstart might be facing increased competition. Could you share how our market share has changed in the past 6-12 months?

Why it matters: Helps understand the urgency of increasing approval rates Expected answer: Slight decline in market share Impact on approach: Would prioritize aggressive growth strategies if market share is declining

  • Considering our revenue model, I assume we earn through origination fees and loan servicing. Is this correct, and are there any other significant revenue streams?

Why it matters: Clarifies the financial impact of increasing approvals Expected answer: Confirmation of revenue streams, possibly including interest income Impact on approach: Would influence the balance between short-term gains and long-term sustainability

  • Looking at user segments, I'm curious about our current approval rate distribution. Can you provide a breakdown of approval rates across different credit score ranges?

Why it matters: Identifies potential areas for improvement without significantly increasing risk Expected answer: Lower approval rates for mid-range credit scores Impact on approach: Would focus on optimizing approval criteria for specific segments

  • Regarding our risk assessment model, I'm wondering about its current performance. What's our model's accuracy in predicting defaults, and how has it evolved recently?

Why it matters: Assesses the reliability of our current risk assessment Expected answer: High accuracy with recent improvements Impact on approach: Would inform the level of confidence in expanding approval criteria

  • Considering resource allocation, I'm curious about our current capacity for handling increased loan volume. Do we have the operational bandwidth to process a significant increase in approvals?

Why it matters: Determines if we can support a substantial increase in loan approvals Expected answer: Some capacity, but may need to scale operations Impact on approach: Would influence the pace and scale of any approval rate increases

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