┌─────────────────────────────────────────────────────────────────────────────┐
│                    RISK APPETITE FRAMEWORK                                │
├─────────────────────────────────────────────────────────────────────────────┤
│                                                                             │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │                    STRATEGIC OBJECTIVES                             │   │
│  │  (Business goals and objectives)                                   │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                    │                                        │
│                                    v                                        │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │                    RISK APPETITE STATEMENT                          │   │
│  │  (Overall risk appetite)                                            │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                    │                                        │
│                                    v                                        │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │                    RISK TOLERANCES                                  │   │
│  │  (Specific limits by risk category)                                 │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                    │                                        │
│                                    v                                        │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │                    LIMITS & ESCALATION                             │   │
│  │  (Breaches, escalation procedures)                                  │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                                                             │
└─────────────────────────────────────────────────────────────────────────────┘

# ===================================================================
# MODULE 8, LESSON 8: RISK CULTURE AND GOVERNANCE
# ===================================================================

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from datetime import datetime
import warnings
warnings.filterwarnings('ignore')

print("="*70)
print("RISK CULTURE AND GOVERNANCE IN DIGITAL BANKING")
print("="*70)

# ----------------------------------------------------------------
# PART A: RISK CULTURE ASSESSMENT
# ----------------------------------------------------------------

print("\n" + "-"*60)
print("PART A: Risk Culture Assessment")
print("-"*60)

culture_dimensions = {
    'Leadership Commitment': {'Current Score': 3, 'Target Score': 5, 'Priority': 'High'},
    'Accountability': {'Current Score': 3, 'Target Score': 5, 'Priority': 'High'},
    'Transparency': {'Current Score': 3, 'Target Score': 5, 'Priority': 'High'},
    'Training and Awareness': {'Current Score': 3, 'Target Score': 5, 'Priority': 'High'},
    'Incentives and Rewards': {'Current Score': 2, 'Target Score': 4, 'Priority': 'Medium'},
    'Consequences': {'Current Score': 3, 'Target Score': 5, 'Priority': 'High'},
    'Communication': {'Current Score': 3, 'Target Score': 5, 'Priority': 'High'},
    'Learning Culture': {'Current Score': 2, 'Target Score': 4, 'Priority': 'Medium'}
}

culture_df = pd.DataFrame(culture_dimensions).T
print("Risk Culture Assessment:")
print(culture_df)

# Visualise
fig, ax = plt.subplots(figsize=(10, 6))
dimensions = list(culture_df.index)
current = culture_df['Current Score'].tolist()
target = culture_df['Target Score'].tolist()

x = np.arange(len(dimensions))
width = 0.35

ax.barh(x - width/2, current, width, label='Current', color='blue', alpha=0.7)
ax.barh(x + width/2, target, width, label='Target', color='green', alpha=0.7)

ax.set_yticks(x)
ax.set_yticklabels(dimensions)
ax.set_xlabel('Maturity Score (1-5)')
ax.set_title('Risk Culture Assessment')
ax.legend()
ax.grid(True, alpha=0.3, axis='x')

plt.tight_layout()
plt.savefig('risk_culture.png', dpi=300, bbox_inches='tight')
plt.show()
print("Risk culture visualisation saved as 'risk_culture.png'")

# ----------------------------------------------------------------
# PART B: RISK GOVERNANCE STRUCTURE
# ----------------------------------------------------------------

print("\n" + "-"*60)
print("PART B: Risk Governance Structure")
print("-"*60)

governance_structure = {
    "Board of Directors": {
        "Responsibilities": ["Approve risk strategy", "Oversee risk management", "Review reports"]
    },
    "Risk Committee": {
        "Responsibilities": ["Oversee risk activities", "Review risk appetite", "Monitor compliance"]
    },
    "Chief Risk Officer (CRO)": {
        "Responsibilities": ["Lead risk function", "Report to board", "Manage risk teams"]
    },
    "Risk Management Function": {
        "Responsibilities": ["Risk assessment", "Risk monitoring", "Risk reporting"]
    },
    "Business Units (1st Line)": {
        "Responsibilities": ["Own and manage risks", "Implement controls", "Comply with policies"]
    },
    "Internal Audit (3rd Line)": {
        "Responsibilities": ["Independent assurance", "Audit risk processes", "Report findings"]
    }
}

print("Risk Governance Structure:")
for role, details in governance_structure.items():
    print(f"\n{role}:")
    print("  Responsibilities:")
    for resp in details['Responsibilities']:
        print(f"    • {resp}")

# ----------------------------------------------------------------
# PART C: RISK APPETITE STATEMENT
# ----------------------------------------------------------------

print("\n" + "-"*60)
print("PART C: Risk Appetite Statement")
print("-"*60)

risk_appetite = pd.DataFrame({
    'Risk Category': ['Credit', 'Market', 'Operational', 'Liquidity', 'Cybersecurity', 'Model', 'Third-Party'],
    'Risk Appetite': ['Moderate', 'Low', 'Low', 'Low', 'Very Low', 'Low', 'Low'],
    'Risk Tolerance': [
        'PD < 3%',
        'VaR < 5%',
        'Loss < $10M',
        'LCR > 100%',
        'Zero breaches',
        'Model error < 0.5%',
        'Vendor failures < 2'
    ],
    'Current Status': ['Within', 'Within', 'Within', 'Exceeded', 'Within', 'Within', 'Within']
})

print("Risk Appetite Statement:")
print(risk_appetite.to_string(index=False))

# ----------------------------------------------------------------
# PART D: RISK INCIDENT REPORTING
# ----------------------------------------------------------------

print("\n" + "-"*60)
print("PART D: Risk Incident Reporting")
print("-"*60)

# Simulate incident data
np.random.seed(42)
n_incidents = 50

incident_data = pd.DataFrame({
    'incident_id': range(1, n_incidents + 1),
    'date': [datetime.now() - timedelta(days=np.random.randint(0, 365)) for _ in range(n_incidents)],
    'category': np.random.choice(['Credit', 'Market', 'Operational', 'Liquidity', 'Cybersecurity', 'Model', 'Third-Party'], n_incidents),
    'severity': np.random.choice(['Low', 'Medium', 'High', 'Critical'], n_incidents, p=[0.3, 0.3, 0.25, 0.15]),
    'status': np.random.choice(['Closed', 'Resolved', 'In Progress', 'Open'], n_incidents, p=[0.4, 0.3, 0.2, 0.1]),
    'time_to_resolve': np.random.gamma(2, 3, n_incidents).clip(0.1, 24)
})

print("Incident Data Sample:")
print(incident_data.head())

# Summary
incident_summary = incident_data.groupby('category').agg({
    'incident_id': 'count',
    'severity': lambda x: x.value_counts().index[0],
    'time_to_resolve': 'mean'
}).round(2)
incident_summary.columns = ['Count', 'Most Common Severity', 'Avg Time to Resolve (hours)']

print("\nIncident Summary:")
print(incident_summary)

# Visualise
fig, axes = plt.subplots(2, 2, figsize=(14, 10))

# Incidents by Category
ax = axes[0, 0]
category_counts = incident_data['category'].value_counts()
ax.bar(category_counts.index, category_counts.values, color='teal', alpha=0.7)
ax.set_xlabel('Category')
ax.set_ylabel('Count')
ax.set_title('Incidents by Category')
ax.tick_params(axis='x', rotation=45)
ax.grid(True, alpha=0.3)

# Severity Distribution
ax = axes[0, 1]
severity_counts = incident_data['severity'].value_counts()
colors = {'Low': 'green', 'Medium': 'orange', 'High': 'red', 'Critical': 'darkred'}
ax.bar(severity_counts.index, severity_counts.values, 
       color=[colors.get(s, 'gray') for s in severity_counts.index], alpha=0.7)
ax.set_xlabel('Severity')
ax.set_ylabel('Count')
ax.set_title('Incident Severity')
ax.grid(True, alpha=0.3)

# Resolution Time by Severity
ax = axes[1, 0]
incident_data.boxplot(column='time_to_resolve', by='severity', ax=ax)
ax.set_title('Resolution Time by Severity')
ax.set_xlabel('Severity')
ax.set_ylabel('Time to Resolve (hours)')
ax.grid(True, alpha=0.3)

# Status Distribution
ax = axes[1, 1]
status_counts = incident_data['status'].value_counts()
ax.pie(status_counts.values, labels=status_counts.index, autopct='%1.1f%%')
ax.set_title('Incident Status')

plt.tight_layout()
plt.savefig('incident_reporting.png', dpi=300, bbox_inches='tight')
plt.show()
print("Incident reporting visualisation saved as 'incident_reporting.png'")

# ----------------------------------------------------------------
# PART E: RISK CULTURE METRICS
# ----------------------------------------------------------------

print("\n" + "-"*60)
print("PART E: Risk Culture Metrics Dashboard")
print("-"*60)

culture_metrics = pd.DataFrame({
    'Metric': [
        'Risk Awareness Score',
        'Risk Training Completion',
        'Risk Incident Reporting Rate',
        'Whistleblowing Rate',
        'Risk Culture Score',
        'Leadership Commitment Score',
        'Accountability Score',
        'Transparency Score'
    ],
    'Current Value': [
        '78%',
        '72%',
        '3.2/5',
        '1.2%',
        '3.6/5',
        '3.8/5',
        '3.5/5',
        '3.2/5'
    ],
    'Target Value': [
        '> 90%',
        '> 95%',
        '> 4.0/5',
        '> 2.0%',
        '> 4.5/5',
        '> 4.5/5',
        '> 4.5/5',
        '> 4.5/5'
    ],
    'Status': ['🟡', '🟡', '🟡', '🟡', '🟡', '🟡', '🟡', '🟡']
})

print("Risk Culture Metrics Dashboard:")
print(culture_metrics.to_string(index=False))

# ----------------------------------------------------------------
# PART F: RISK CULTURE ROADMAP
# ----------------------------------------------------------------

print("\n" + "-"*60)
print("PART F: Risk Culture Roadmap")
print("-"*60)

roadmap = {
    "Phase 1 (0-6 months) – Foundation": {
        "Focus": "Build risk culture foundation.",
        "Activities": [
            "Establish risk appetite statement.",
            "Implement risk training programme.",
            "Build risk reporting and escalation.",
            "Establish accountability framework."
        ],
        "Success Metrics": ["Risk culture score > 3.5", "Training completion > 80%"]
    },
    "Phase 2 (6-12 months) – Scale": {
        "Focus": "Scale risk culture.",
        "Activities": [
            "Embed risk in decision-making.",
            "Enhance risk communication.",
            "Implement incentives and rewards.",
            "Conduct regular risk culture surveys."
        ],
        "Success Metrics": ["Risk culture score > 4.0", "Incident reporting > 3.5/5"]
    },
    "Phase 3 (12-24 months) – Advanced": {
        "Focus": "Advanced risk culture.",
        "Activities": [
            "Implement AI-powered risk insights.",
            "Deploy predictive risk analytics.",
            "Build risk culture dashboards.",
            "Achieve regulatory excellence."
        ],
        "Success Metrics": ["Risk culture score > 4.5", "Industry-leading risk culture"]
    },
    "Phase 4 (24+ months) – Leadership": {
        "Focus": "Industry-leading risk culture.",
        "Activities": [
            "Lead industry risk culture.",
            "Build global risk culture.",
            "Achieve risk culture leadership.",
            "Continuous improvement."
        ],
        "Success Metrics": ["Industry-leading risk culture", "Continuous improvement"]
    }
}

for phase, details in roadmap.items():
    print(f"\n{phase}:")
    print(f"  Focus: {details['Focus']}")
    print("  Activities:")
    for activity in details['Activities']:
        print(f"    • {activity}")
    print("  Success Metrics:")
    for metric in details['Success Metrics']:
        print(f"    • {metric}")

# ----------------------------------------------------------------
# PART G: SUMMARY AND RECOMMENDATIONS
# ----------------------------------------------------------------

print("\n" + "="*70)
print("PART G: Summary and Recommendations")
print("="*70)

print("""
Risk Culture and Governance – Key Takeaways:

1. Risk culture is the set of values and behaviours shaping risk management.
2. Key elements: tone from the top, accountability, transparency, training, incentives.
3. Governance framework: board oversight, risk committee, CRO, risk function, business units.
4. Risk appetite statement defines the amount of risk the bank is willing to take.
5. Risk tolerance sets specific limits for each risk category.
6. Key metrics: risk awareness, training completion, incident reporting, culture score.
7. Roadmap: foundation → scale → advanced → leadership.

Recommendations:
  - Establish a risk appetite statement.
  - Implement risk training and awareness programmes.
  - Build risk reporting and escalation.
  - Embed risk in decision-making.
  - Measure and monitor risk culture.
  - Foster a risk-aware culture from the top.
""")

print("="*70)
print("END OF LESSON 8 – MODULE 8")
print("="*70)
print("END OF MODULE 8")
print("="*70)