Machine Learning Model Deployment Pipeline

Design a sophisticated MLOps pipeline for deploying machine learning models in a financial risk assessment context. Create a system that: 1) Automatically version and track model performance, 2) Implement A/B testing for predictive algorithms, 3) Use Kubernetes for model serving with automatic scaling, 4) Integrate comprehensive logging and model drift detection. Include advanced techniques for model validation, including statistical significance testing and performance benchmarking.