Overview of Financial Risks and Regulatory Frameworks › Regulatory Frameworks
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Financial regulation has evolved dramatically since the 2008 crisis. While the details vary by jurisdiction and institution type, the Basel framework provides the global template for bank regulation and influences risk management practices throughout the financial industry.
The Basel Accords
The Basel Committee on Banking Supervision has issued a series of accords that establish international standards for bank capital adequacy:
- Basel I (1988): Established minimum capital requirements based on risk-weighted assets, primarily focused on credit risk
- Basel II (2004): Introduced more sophisticated risk weights, incorporated operational risk, and allowed internal models for capital calculation
- Basel III (2010-2017): Substantially increased capital requirements, introduced leverage ratios, and added liquidity requirements in response to the 2008 crisis
The central concept underlying these accords is the idea of risk-weighted assets (RWA). Rather than requiring banks to hold capital against their total assets, regulators require capital against assets weighted by their riskiness. This approach serves two purposes: it ensures that riskier activities require more capital cushion, and it provides incentives for banks to shift toward safer activities.
The following code calculates risk-weighted assets (RWA) for a simplified bank balance sheet based on Basel-style asset categories.
# Simplified illustration of risk-weighted assets calculation
risk_weights = {
"Cash": 0.00,
"Government Bonds": 0.00,
"Residential Mortgages": 0.35,
"Corporate Loans (IG)": 0.65,
"Corporate Loans (HY)": 1.00,
"Equity Holdings": 1.50,
}
# Example bank balance sheet (simplified)
balance_sheet = {
"Cash": 50,
"Government Bonds": 200,
"Residential Mortgages": 400,
"Corporate Loans (IG)": 250,
"Corporate Loans (HY)": 75,
"Equity Holdings": 25,
}
# Calculate risk-weighted assets
rwa_components = {}
for asset, exposure in balance_sheet.items():
rw = risk_weights[asset]
rwa = exposure * rw
rwa_components[asset] = {
"Exposure": exposure,
"Risk_Weight": rw,
"RWA": rwa,
}
rwa_df = pd.DataFrame(rwa_components).T
total_assets = rwa_df["Exposure"].sum()
total_rwa = rwa_df["RWA"].sum()
# Calculate capital metrics
rwa_ratio = (total_rwa / total_assets) * 100
required_capital = total_rwa * 0.08
capital_assets_ratio = (required_capital / total_assets) * 100Risk-Weighted Assets Calculation
============================================================
Exposure Risk_Weight RWA
Cash 50.0 0.00 0.0
Government Bonds 200.0 0.00 0.0
Residential Mortgages 400.0 0.35 140.0
Corporate Loans (IG) 250.0 0.65 162.5
Corporate Loans (HY) 75.0 1.00 75.0
Equity Holdings 25.0 1.50 37.5
------------------------------------------------------------
Total Assets: $1000M
Total Risk-Weighted Assets: $415M
RWA / Assets Ratio: 41.5%
Required Capital (8% of RWA): $33.2M
Capital as % of Total Assets: 3.3%

This simplified example shows how risk weights convert a $1,000 million balance sheet into $415 million of risk-weighted assets. The regulatory capital requirement applies to RWA, not total assets, which means riskier portfolios require proportionally more capital. Notice how cash and government bonds carry zero risk weight, which reflects their presumed safety, while equity holdings carry a 150% risk weight, which reflects their higher volatility and loss potential.