agents/risk_scoring_agent.py

"""Risk Scoring Agent - Combines signals into final fraud risk score."""

from typing import Dict, List, Any


class RiskScoringAgent:
    """Calculates final fraud risk score."""
    
    def __init__(self):
        self.name = "RiskScoringAgent"
        self.version = "1.0"
        self.investigation_threshold = 0.7
    
    def process(
        self,
        pattern_results: Dict[str, Any],
        anomaly_results: Dict[str, Any]
    ) -> Dict[str, Any]:
        """Calculate final fraud risk score."""
        
        # Weighted combination
        pattern_score = pattern_results.get("overall_pattern_score", 0.0)
        anomaly_score = anomaly_results.get("anomaly_score", 0.0)
        
        # 60% patterns, 40% anomalies
        final_score = (pattern_score * 0.6) + (anomaly_score * 0.4)
        
        # Determine risk level
        if final_score >= 0.7:
            risk_level = "high"
            recommended_action = "immediate_investigation"
        elif final_score >= 0.4:
            risk_level = "medium"
            recommended_action = "enhanced_review"
        else:
            risk_level = "low"
            recommended_action = "standard_processing"
        
        # Collect all indicators
        fraud_indicators = []
        fraud_indicators.extend(pattern_results.get("detected_patterns", []))
        fraud_indicators.extend(anomaly_results.get("anomalies_detected", []))
        
        return {
            "fraud_score": final_score,
            "risk_level": risk_level,
            "fraud_indicators": fraud_indicators,
            "recommended_action": recommended_action,
            "requires_investigation": final_score >= self.investigation_threshold,
            "confidence": 0.88
        }
    
    def get_trace(self) -> Dict[str, Any]:
        return {
            "agent": self.name,
            "version": self.version,
            "timestamp": "2024-12-31T01:00:00Z",
            "status": "completed"
        }