How can Modalku balance increasing interest rates for higher returns versus maintaining competitive rates to attract borrowers?

Introduction

Balancing interest rates for Modalku presents a critical trade-off between maximizing returns and maintaining borrower attraction. This scenario involves weighing the potential for increased revenue against the risk of losing market share. I'll analyze this trade-off by examining key metrics, designing experiments, and providing a data-driven recommendation.

Step 1

Clarifying Questions (3 minutes)

• Context: I'm thinking about Modalku's current market position. Could you share our current market share and how it compares to our main competitors?

Why it matters: Helps assess the risk of losing borrowers to competitors. Expected answer: We're a top 3 player with 20-30% market share. Impact on approach: If we're the market leader, we might have more flexibility to increase rates.

• Business Context: Based on our financial reports, I assume interest income is our primary revenue source. Is this correct, and what percentage of our total revenue does it represent?

Why it matters: Determines the potential impact of rate changes on overall business performance. Expected answer: Yes, it's 80-90% of our revenue. Impact on approach: A high percentage would justify a more cautious approach to rate increases.

• User Impact: I'm curious about our borrower segments. Can you tell me about our main borrower types and their sensitivity to interest rates?

Why it matters: Different segments may react differently to rate changes. Expected answer: We serve SMEs and individuals with varying rate sensitivities. Impact on approach: Would inform a potential segmented approach to rate adjustments.

• Technical: Considering our platform's capabilities, how quickly can we implement and test different interest rate structures?

Why it matters: Affects our ability to experiment and iterate rapidly. Expected answer: We can implement changes within 1-2 weeks. Impact on approach: Fast implementation would allow for more agile testing strategies.

• Resource: What's our current capacity for analyzing the impacts of rate changes across our borrower base?

Why it matters: Determines our ability to thoroughly assess outcomes. Expected answer: We have a dedicated data science team available. Impact on approach: Strong analytical resources would enable more complex experimentation.