Ensure Fairness Beyond Gender Parity in Lending Practices

Q: Ensure Fairness Beyond Gender Parity in Lending Practices

This question evaluates a data scientist's understanding of fair lending principles, statistical fairness metrics, funnel and selection-rate analyses, ethical judgment in model-driven decisions, and behavioral leadership communication within the Behavioral & Leadership category.

Q: How do I approach Behavioral & Leadership interview questions?

Behavioral & Leadership questions require understanding of core concepts and practice. PracHub provides solutions with explanations to help you master behavioral & leadership interviews.

Question

Fair Lending Behavioral Interview Prompt

Scenario

You are discussing fair lending practices during an on-site behavioral interview.

Questions

The current portfolio issues 50% of loans to women and 50% to men. Does this guarantee fair lending? Explain why or why not.
What additional analyses would you perform to assess fairness?
Why are you interested in machine learning?
Describe a past failure and what you would do differently.

Considerations (Hints)

Qualified-applicant mix and stage-by-stage funnel analysis
Acceptance rates and selection-rate parity
Pricing parity and risk-adjusted pricing
Disparate impact tests (e.g., 80% rule) and fairness metrics

Ensure Fairness Beyond Gender Parity in Lending Practices

Fair Lending Behavioral Interview Prompt

Scenario

Questions

Considerations (Hints)

Solution

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