Treasury ALM Risk Controller

def calculate_fx_counterparty_risk(exposures: str) -> str:
    """
    Calculate FX and counterparty credit risk exposures.
    
    Args:
        exposures: Cash placements, investments, and FX positions with counterparty details
    
    Returns:
        FX and counterparty risk assessment report
    """
    try:
        import json
        
        if isinstance(exposures, str):
            try:
                data = json.loads(exposures)
            except json.JSONDecodeError:
                return "Error: Invalid JSON format for exposures"
        else:
            data = exposures
        
        positions = data.get('positions', [])
        
        "color: #6b7280;"># Aggregate by counterparty and currency
        counterparty_exposure = {}
        currency_exposure = {}
        
        for pos in positions:
            counterparty = pos.get('counterparty', 'Unknown')
            currency = pos.get('currency', 'USD')
            amount = pos.get('amount', 0)
            
            "color: #6b7280;"># Counterparty aggregation
            if counterparty not in counterparty_exposure:
                counterparty_exposure[counterparty] = 0
            counterparty_exposure[counterparty] += amount
            
            "color: #6b7280;"># Currency aggregation
            if currency not in currency_exposure:
                currency_exposure[currency] = 0
            currency_exposure[currency] += amount
        
        total_exposure = sum(counterparty_exposure.values())
        
        report = "=== FX & COUNTERPARTY RISK ASSESSMENT ===\n\n"
        
        "color: #6b7280;"># Counterparty concentration
        report += "COUNTERPARTY EXPOSURE:\n"
        report += f"{'Counterparty':<30} {'Exposure':>15} {'% of Total':>12} {'Status':>10}\n"
        report += "-" * 67 + "\n"
        
        for counterparty, exposure in sorted(counterparty_exposure.items(), key=lambda x: x[1], reverse=True):
            pct = exposure / total_exposure * 100 if total_exposure > 0 else 0
            status = "⚠️" if pct > 10 else "✓"
            report += f"{counterparty:<30} {exposure:>15,.2f} {pct:>11.1f}% {status:>10}\n"
        
        "color: #6b7280;"># Currency exposure
        report += "\nFX EXPOSURE BY CURRENCY:\n"
        report += f"{'Currency':<15} {'Net Position':>15} {'% of Total':>12}\n"
        report += "-" * 42 + "\n"
        
        for currency, position in sorted(currency_exposure.items(), key=lambda x: abs(x[1]), reverse=True):
            pct = abs(position) / total_exposure * 100 if total_exposure > 0 else 0
            report += f"{currency:<15} {position:>15,.2f} {pct:>11.1f}%\n"
        
        "color: #6b7280;"># Risk assessment
        report += "\n=== RISK ASSESSMENT ===\n"
        
        high_concentration = [cp for cp, exp in counterparty_exposure.items() if exp / total_exposure > 0.10]
        if high_concentration:
            report += f"\n⚠️ High counterparty concentration detected: {', '.join(high_concentration)}\n"
            report += "Recommendation: Diversify counterparty exposures to reduce concentration risk.\n"
        
        non_base_currency = sum(abs(exp) for curr, exp in currency_exposure.items() if curr != 'USD')
        fx_ratio = non_base_currency / total_exposure if total_exposure > 0 else 0
        
        if fx_ratio > 0.20:
            report += f"\n⚠️ Significant FX exposure: {fx_ratio*100:.1f}% in non-base currencies.\n"
            report += "Recommendation: Consider FX hedging strategies(forwards, options, natural hedges).\n"
        
        if not high_concentration and fx_ratio <= 0.20:
            report += "\n✓ Counterparty and FX risks within acceptable limits.\n"
            report += "Continue monitoring exposures regularly.\n"
        
        return report
        
    except Exception as e:
        return f"Error calculating FX counterparty risk: {str(e)}"

def calculate_alm_metrics(balance_sheet_data: str) -> str:
    """
    Calculate comprehensive ALM metrics.
    
    Args:
        balance_sheet_data: Complete balance sheet with all required data
    
    Returns:
        Comprehensive ALM metrics report
    """
    try:
        import json
        
        if isinstance(balance_sheet_data, str):
            try:
                data = json.loads(balance_sheet_data)
            except json.JSONDecodeError:
                return "Error: Invalid JSON format"
        else:
            data = balance_sheet_data
        
        "color: #6b7280;"># Extract data
        assets = data.get('assets', [])
        liabilities = data.get('liabilities', [])
        capital = data.get('capital', {})
        
        total_assets = sum(a.get('amount', 0) for a in assets)
        total_liabilities = sum(l.get('amount', 0) for l in liabilities)
        
        "color: #6b7280;"># Liquidity metrics
        liquid_assets = sum(a.get('amount', 0) for a in assets if a.get('liquid', False))
        stable_funding = sum(l.get('amount', 0) for l in liabilities if l.get('stable', True))
        
        lcr = liquid_assets / (total_liabilities * 0.30) if total_liabilities > 0 else 0  "color: #6b7280;"># Simplified LCR
        nsfr = stable_funding / total_assets if total_assets > 0 else 0  "color: #6b7280;"># Simplified NSFR
        
        "color: #6b7280;"># Capital metrics
        rwa = sum(a.get('amount', 0) * a.get('risk_weight', 1.0) for a in assets)
        total_capital = sum(capital.values()) if isinstance(capital, dict) else capital
        
        cet1_ratio = (capital.get('cet1', 0) / rwa * 100) if rwa > 0 else 0
        tier1_ratio = ((capital.get('cet1', 0) + capital.get('at1', 0)) / rwa * 100) if rwa > 0 else 0
        total_capital_ratio = (total_capital / rwa * 100) if rwa > 0 else 0
        leverage_ratio = (total_capital / total_assets * 100) if total_assets > 0 else 0
        
        "color: #6b7280;"># Interest rate metrics
        asset_duration = sum(a.get('amount', 0) * a.get('duration', 3) for a in assets) / total_assets if total_assets > 0 else 0
        liability_duration = sum(l.get('amount', 0) * l.get('duration', 2) for l in liabilities) / total_liabilities if total_liabilities > 0 else 0
        duration_gap = asset_duration - liability_duration
        
        report = "=== COMPREHENSIVE ALM METRICS ===\n\n"
        
        "color: #6b7280;"># Liquidity Metrics
        report += "LIQUIDITY METRICS:\n"
        report += f"  Liquidity Coverage Ratio(LCR): {lcr*100:.1f}% (Minimum: 100%)\n"
        report += f"  Net Stable Funding Ratio(NSFR): {nsfr*100:.1f}% (Minimum: 100%)\n"
        report += f"  Liquid Assets: {liquid_assets:,.2f}\n\n"
        
        "color: #6b7280;"># Capital Metrics
        report += "CAPITAL METRICS:\n"
        report += f"  CET1 Ratio: {cet1_ratio:.2f}% (Minimum: 8%)\n"
        report += f"  Tier 1 Ratio: {tier1_ratio:.2f}% (Minimum: 10%)\n"
        report += f"  Total Capital Ratio: {total_capital_ratio:.2f}% (Minimum: 12%)\n"
        report += f"  Leverage Ratio: {leverage_ratio:.2f}% (Minimum: 3%)\n\n"
        
        "color: #6b7280;"># Interest Rate Risk
        report += "INTEREST RATE RISK METRICS:\n"
        report += f"  Asset Duration: {asset_duration:.2f} years\n"
        report += f"  Liability Duration: {liability_duration:.2f} years\n"
        report += f"  Duration Gap: {duration_gap:.2f} years\n\n"
        
        "color: #6b7280;"># Compliance assessment
        report += "=== COMPLIANCE STATUS ===\n"
        
        issues = []
        if lcr < 1.0:
            issues.append("⚠️ LCR below 100% minimum")
        if nsfr < 1.0:
            issues.append("⚠️ NSFR below 100% minimum")
        if cet1_ratio < 8:
            issues.append("⚠️ CET1 ratio below 8% minimum")
        if tier1_ratio < 10:
            issues.append("⚠️ Tier 1 ratio below 10% minimum")
        if leverage_ratio < 3:
            issues.append("⚠️ Leverage ratio below 3% minimum")
        
        if issues:
            report += "\nREGULATORY ISSUES DETECTED:\n"
            for issue in issues:
                report += f"{issue}\n"
            report += "\nRecommendation: Immediate action required to restore compliance.\n"
        else:
            report += "✓ All regulatory metrics within required thresholds.\n"
            report += "ALM position is compliant with current regulations.\n"
        
        "color: #6b7280;"># Duration gap assessment
        report += "\n=== INTEREST RATE POSITIONING ===\n"
        if abs(duration_gap) > 2:
            report += f"⚠️ Significant duration gap: {duration_gap:.2f} years\n"
            report += "Recommendation: Consider duration matching or hedging strategies.\n"
        else:
            report += f"✓ Duration gap within acceptable range: {duration_gap:.2f} years\n"
        
        return report
        
    except Exception as e:
        return f"Error calculating ALM metrics: {str(e)}"