Fintech AI: Reshaping the Financial Services Ecosystem

Real-time Fraud Detection Solution

class FraudDetectionSystem:
    """Real-time financial fraud detection system"""
    
    def __init__(self, llm_api, risk_db):
        self.llm = llm_api
        self.risk_db = risk_db
        self.threshold = 0.85
        
    def analyze_transaction(self, transaction):
        """Analyze transaction risk"""
        # 1. Feature extraction
        features = self.extract_features(transaction)
        
        # 2. Historical behavior analysis
        user_profile = self.get_user_profile(transaction['user_id'])
        
        # 3. Anomaly detection
        anomaly_score = self.detect_anomaly(features, user_profile)
        
        # 4. In-depth LLM analysis
        if anomaly_score > 0.6:
            risk_analysis = self.llm.analyze(f"""
            Analyze the risk of the following transaction:
            Transaction: {transaction}
            User profile: {user_profile}
            Anomaly score: {anomaly_score}
            
            Please evaluate:
            1. Fraud likelihood (0-1)
            2. Risk type
            3. Recommended actions
            """)
            
            return self.parse_risk_result(risk_analysis)
    
    def real_time_monitoring(self):
        """Real-time monitoring"""
        for transaction in self.transaction_stream():
            risk = self.analyze_transaction(transaction)
            
            if risk['score'] > self.threshold:
                self.trigger_alert(transaction, risk)
                self.block_transaction(transaction)
            elif risk['score'] > 0.6:
                self.flag_for_review(transaction, risk)

Regulatory Requirements for Financial AI