For Citizens Bank's mortgage products, how do we weigh offering more flexible terms to increase approvals versus maintaining stricter criteria to reduce risk?

Introduction

The trade-off between offering more flexible mortgage terms to increase approvals versus maintaining stricter criteria to reduce risk is a critical decision for Citizens Bank's mortgage products. This scenario involves balancing customer acquisition and growth against financial stability and risk management. I'll analyze this trade-off by examining the product ecosystem, stakeholder impacts, and potential outcomes, ultimately providing a data-driven recommendation.

Step 1

Clarifying Questions (3 minutes)

• Based on recent market trends, I'm thinking there might be increased pressure on mortgage approvals. Could you provide some context on the current approval rates and how they compare to industry benchmarks?

Why it matters: Helps understand the urgency and scale of the problem Expected answer: Approval rates below industry average Impact on approach: Would prioritize flexibility options if significantly below benchmarks

• Considering our revenue model, I assume mortgage products are a significant contributor. Can you confirm the percentage of overall revenue they represent and any growth targets for this segment?

Why it matters: Aligns solution with business priorities Expected answer: 30-40% of revenue, with 10% YoY growth target Impact on approach: Higher revenue share would justify more aggressive flexibility measures

• Looking at user segments, I'm curious about the profile of applicants we're currently declining. Do we have data on the most common reasons for rejection and the potential lifetime value of these customers?

Why it matters: Identifies opportunities for targeted flexibility Expected answer: Credit score and debt-to-income ratio main factors; high LTV potential Impact on approach: Would focus on adjusting criteria in these specific areas

• Regarding our risk assessment capabilities, have we recently upgraded our models or data sources? This could impact our ability to accurately predict default risk with more flexible terms.

Why it matters: Determines technical feasibility of more nuanced approvals Expected answer: Recent implementation of machine learning models Impact on approach: Advanced models would support more granular flexibility options

• Considering regulatory constraints, are there any upcoming changes in lending regulations that might impact our ability to adjust approval criteria?

Why it matters: Ensures compliance and avoids future issues Expected answer: Potential changes in debt-to-income requirements Impact on approach: Would factor in regulatory trends when designing flexibility options