Solvency Capital Strategist

def simulate_contingency_funding(funding_gap: float, available_sources: str) -> str:
    """
    Simulate contingency funding plan activation.
    
    Args:
        funding_gap: Size of funding shortfall
        available_sources: JSON string with available contingency sources
    
    Returns:
        Contingency funding plan with recommended actions
    """
    try:
        import json
        
        "color: #6b7280;"># Parse available sources
        if isinstance(available_sources, str):
            try:
                sources = json.loads(available_sources)
            except json.JSONDecodeError:
                sources = {
                    'liquid_assets': 0,
                    'credit_lines': 0,
                    'central_bank': 0
                }
        else:
            sources = available_sources
        
        liquid_assets = sources.get('liquid_assets', 0)
        credit_lines = sources.get('credit_lines', 0)
        central_bank = sources.get('central_bank', 0)
        
        report = "=== CONTINGENCY FUNDING PLAN ===\n\n"
        report += f"Funding Gap: {funding_gap:,.2f}\n\n"
        
        report += "Available Contingency Sources:\n"
        report += f"  1. Liquid Assets: {liquid_assets:,.2f}\n"
        report += f"  2. Committed Credit Lines: {credit_lines:,.2f}\n"
        report += f"  3. Central Bank Facilities: {central_bank:,.2f}\n"
        report += f"  Total Available: {liquid_assets + credit_lines + central_bank:,.2f}\n\n"
        
        report += "=== RECOMMENDED ACTION HIERARCHY ===\n\n"
        
        remaining_gap = funding_gap
        actions = []
        
        "color: #6b7280;"># Step 1: Use liquid assets
        if remaining_gap > 0 and liquid_assets > 0:
            use_liquid = min(remaining_gap, liquid_assets)
            actions.append(f"1. Liquidate {use_liquid:,.2f} from liquid asset buffer")
            remaining_gap -= use_liquid
        
        "color: #6b7280;"># Step 2: Access credit lines
        if remaining_gap > 0 and credit_lines > 0:
            use_credit = min(remaining_gap, credit_lines)
            actions.append(f"2. Draw {use_credit:,.2f} from committed credit lines")
            remaining_gap -= use_credit
        
        "color: #6b7280;"># Step 3: Central bank facilities
        if remaining_gap > 0 and central_bank > 0:
            use_central = min(remaining_gap, central_bank)
            actions.append(f"3. Access {use_central:,.2f} from central bank facilities")
            remaining_gap -= use_central
        
        for action in actions:
            report += f"{action}\n"
        
        report += "\n=== FUNDING GAP COVERAGE ===\n"
        
        if remaining_gap <= 0:
            report += "✓ Funding gap fully covered by contingency sources.\n"
            report += f"Surplus capacity: {abs(remaining_gap):,.2f}\n"
        else:
            report += f"⚠️ CRITICAL: Funding gap of {remaining_gap:,.2f} remains uncovered.\n"
            report += "Recommendation: Activate additional emergency measures or reduce balance sheet size.\n"
        
        return report
        
    except Exception as e:
        return f"Error simulating contingency funding: {str(e)}"

def optimize_balance_sheet(balance_sheet: str, objectives: str = "maximize_capital_efficiency") -> str:
    """
    Optimize balance sheet structure for capital efficiency.
    
    Args:
        balance_sheet: Current balance sheet structure with assets and liabilities
        objectives: Optimization objectives(e.g., maximize_capital_efficiency, minimize_risk_weighted_assets)
    
    Returns:
        Balance sheet optimization recommendations
    """
    try:
        import json
        
        if isinstance(balance_sheet, str):
            try:
                data = json.loads(balance_sheet)
            except json.JSONDecodeError:
                return "Error: Invalid JSON format for balance sheet"
        else:
            data = balance_sheet
        
        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)
        total_capital = sum(capital.values()) if isinstance(capital, dict) else capital
        
        "color: #6b7280;"># Calculate current ratios
        rwa = sum(a.get('amount', 0) * a.get('risk_weight', 1.0) for a in assets)
        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
        
        report = "=== BALANCE SHEET OPTIMIZATION ===\n\n"
        report += "Current Capital Ratios:\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"
        
        report += "=== OPTIMIZATION RECOMMENDATIONS ===\n\n"
        
        "color: #6b7280;"># Recommendations based on ratios
        if cet1_ratio < 10:
            report += "⚠️ CET1 ratio near regulatory minimum.\n"
            report += "Recommendation: Reduce risk-weighted assets(RWA) by:\n"
            report += "  - Increasing allocation to low-risk assets(government bonds)\n"
            report += "  - Reducing concentration in high-risk assets\n"
            report += "  - Consider securitization of loan portfolio\n\n"
        
        if leverage_ratio < 4:
            report += "⚠️ Leverage ratio could be improved.\n"
            report += "Recommendation: Increase total capital or reduce total assets.\n\n"
        
        "color: #6b7280;"># Asset allocation recommendations
        high_risk_assets = sum(a.get('amount', 0) for a in assets if a.get('risk_weight', 0) > 0.5)
        if high_risk_assets / total_assets > 0.6:
            report += "⚠️ High concentration in risk-weighted assets.\n"
            report += "Recommendation: Rebalance toward lower RWA assets to improve capital efficiency.\n\n"
        
        if all([cet1_ratio >= 10, tier1_ratio >= 12, total_capital_ratio >= 14, leverage_ratio >= 4]):
            report += "✓ All capital ratios exceed minimum requirements with healthy buffers.\n"
            report += "Balance sheet structure is optimized for current regulatory environment.\n"
        
        return report
        
    except Exception as e:
        return f"Error optimizing balance sheet: {str(e)}"