Fractional Reserve Banking System

The banking system operates as a fractional reserve system in which only a portion of the banks deposits are held in reserve.

The Fed sets a lower limit for the fraction of deposits that must be held in reserve: the reserve requirement ratio. Since banks earn profit by lending at higher interest rates than they give on deposits, the reserve requirement is generally a binding limit.

This video explains the fractional reserve banking system and the money multiplier effect.

Let’s take a look at how the Fed maintains reserve requirements. The Federal Reserve Act authorizes the board to set reserve requirements between ranges to implement monetary policies on certain types of deposits. This guideline applies to liabilities of depository institutions as well.

Liability types covered by reserve requirements include net transaction accounts, non-personal time deposits and Eurocurrency liabilities.

The Fractional Reserve Banking system is to protect banks from a bank run. The Federal Reserve instructs banks to maintain a required reserve ratio. This ratio is the percentage of account deposits held by the bank as a reserve and cannot be lent. The Fed Reserve uses fractional reserve banking as a tool of the monetary money supply. The impact of the Fed reducing the reserve requirements is that there is more money supply. An increase in reserves leads to a lowering of the Money Multiplier. This change impacts the supply of money in the market.

The Fed Reserve does not have complete control over the monetary supply since banks may continue to have high reserves and issue lower loans and vice versa. Households may choose to hold more cash and reduce the money supply. This phenomenon is not under the control of the Fed Reserve.

In response to COVID-19 pandemic, the Federal Reserve shifted to a 0% reserve requirement. As a result, banks were no longer required to maintain balances or accounts of the reserves. This policy change increases liquidity in banks which allows them to fund households and businesses.

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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.