Introduction
The sudden increase in the average credit score of approved borrowers for Upstart's small business loans by 50 points since last quarter is a significant shift that warrants careful analysis. This change could have far-reaching implications for Upstart's business model, risk profile, and market positioning. To address this issue, I'll employ a systematic approach to identify potential root causes, validate hypotheses, and propose strategic solutions.
This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.
Step 1
Clarifying Questions (3 minutes)
Why it matters: This could directly explain the shift in approved borrower credit scores. Expected answer: Yes, there was a recent tightening of credit requirements. Impact on approach: If confirmed, we'd focus on understanding the rationale and implications of this change.
Why it matters: External factors could be influencing who's applying for loans. Expected answer: There's been an increase in applications from more established businesses. Impact on approach: This would lead us to investigate broader economic factors and market trends.
Why it matters: Changes in the AI model could significantly impact approval decisions. Expected answer: The model was recently updated with new data. Impact on approach: We'd need to dive deep into the model's performance and potential biases.
Why it matters: Data integrity issues could lead to misleading conclusions. Expected answer: No changes in data sources or processing. Impact on approach: If confirmed, we'd focus on other factors affecting the credit score increase.
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