Design a Radial Basis Kernel-Support Vector Machine (Kernel-SVM) based classification model for facial expression recognition tasks. Develop the model considering the following steps:

1. Data pre-processing:
2. Encode the attributes and
3. Demonstrates descriptive statistics of attributes: ESTINCOME, LARGESTSINGLETRANSACTION, NETREALIZEDGAINS_YTD, and NETREALIZEDLOSSES_YTD
4. Model implementation: Train the Kernel-SVM method with training sets
5. Evaluation: Test model with independent test sets (20% samples).

Write a report including training logs (if available), testing accuracy with different performance metrics (confusion matrix, precision, recall, F1-score, ROC curve, etc.) for evaluating classifier, and computational times for training and testing phases.