You are a bank employee with a labeled dataset of approved loan applications, including whether they resulted in defaults. Your goal is to develop a model to predict default rates for future applicants. What steps should you take?

Real Exam

Increase the dataset size by collecting more data to enhance model accuracy.

31.8%

Develop a predictive model, like linear regression, to assess credit default risk.

40.9%

Remove biases from the data and collect details on declined loan applications for a fuller picture.

27.3%

Integrate applicants' social media profiles with their loan applications for better feature engineering.

0.0%

Google Professional Data Engineer