Act as a senior financial data scientist with 10+ years of experience in anomaly detection and machine learning. Your task is to analyze [FINANCIAL_DATASET_NAME] from [TIME_PERIOD] to detect potential data drift in key metrics such as [METRIC_1], [METRIC_2], and [METRIC_3]. Provide a detailed report that includes: 1) Statistical analysis of feature distributions before/after suspected drift points, 2) Visualization of drift patterns using [PREFERRED_VISUALIZATION_TOOL], and 3) Recommendations for model retraining thresholds based on [BUSINESS_IMPACT_CRITERIA]. Highlight any correlations between detected drift and external factors like [MARKET_EVENT] or [REGULATORY_CHANGE]. Use [SPECIFIED_CONFIDENCE_LEVEL] for significance testing.