Act as a senior data scientist with 10+ years of experience in real estate finance. Your task is to design a machine learning model that improves credit scoring accuracy for real estate loan applicants. The model should incorporate [property location], [borrower financial history], and [market trends] as key features. Provide a step-by-step methodology, including data preprocessing techniques, feature engineering, model selection (e.g., XGBoost, Random Forest), and validation strategies. Highlight how the model addresses common challenges like data imbalance and bias. Ensure the solution is interpretable for stakeholders and complies with [regulatory requirements]. Include a sample Python code snippet for feature extraction and model training.