Regulatory Capital Vs. Economic Capital

Unlike a corporation, the role of capital within a bank is not that of an additional source of funding. Banks are primarily deposit taking institutions which then lend this money in the form of loans and other activities. To expand their exposure, it’s fairly easy for a bank to increase their deposit. Instead the capital plays a more serious role in that it acts as a cover to protect the bank by absorbing excess losses, protecting depositors and others from a run on the bank, and increase investor confidence.

The capital maintained by a bank should therefore reflect the support for the overall risk faced by the bank including credit risk, market risk, and operational risk.

There are three types of capital:

Economic Capital: Economic capital is the amount of capital that a bank needs to run the business and remain solvent. Also called the risk capital, it is defined as a capital required to absorb the impact of unexpected losses during a time horizon at a certain level of confidence. This is calculated by banks themselves using their own risk models.

Regulatory Capital: In most countries, the country regulators specify the amount of capital that a bank is required to hold. This acts as a buffer in place of economic capital.

Book Capital: This is the actual capital that the bank has, which is primarily the equity capital, but can also include other debt.

Most banks, in practice, maintain their book capital above the calculated economic capital or stated regulatory capital, in order to be safe. Also note that both economic capital and regulator capital are designed to cover unexpected loss, however, they are different as described above.

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Data Science in Finance: 9-Book Bundle

Data Science in Finance Book Bundle

Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
  • Derivatives with R
  • Credit Risk Modelling With R
  • Python for Data Science
  • Machine Learning in Finance using Python

Each book comes with PDFs, detailed explanations, step-by-step instructions, data files, and complete downloadable R code for all examples.