Banking: Introduction to Leverage

This article explains the concept of leverage from a bank's perspective. It talks about what leverage is, and why it is good and bad. It also explains the relation between leverage and insolvency.

Leveraging is a key part of banking. Banks enable leveraging for individuals and institutions. Leverage is also called gearing. Leverage simply means how much of their assets are funded through debt. Higher leverage means the debt relative to each dollar of equity is higher.

For example, let’s say a bank has an equity of $300, and total assets of $1000. There is leverage in their balance sheet because they have used the depositors money to give loans to borrowers. One measure of leverage is Assets:Equity, which is 10:3 in this example.

How much leverage?

How much leverage is desirable then? A firm can avail cheaper funding of its assets by opting for a certain amount of debt. Since debt is tax-deductible, leveraging within limits can be useful for a firm. However over leveraging can prove to be dangerous to a firm. This is especially true when a firm cannot service its debts through its existing cash flow from its assets. This can result in writing off of some part of the equity of shareholders or a complete sell-out of the firm. There is a point beyond which taking debt is dangerous. There is a line beyond which the benefits of tax-advantages overrule the risk of bankruptcy.

Similarly, banks too are leveraged though their gearing is far higher than a firm. If a firm has a leverage ratio of 50:50, debt to equity, in banks it can be as high as 95:5. Banks collect household savings and other surplus funds and provide firms access to these funds, enabling better investment and at reasonable cost. Naturally, there is a risk when banks are so highly leveraged.

In order to counter this risk, governments have regulations about banks maintaining minimum requirements of capital, and liquidity. Banks are expected to maintain risk management measures, audits and several internal controls to monitor their debt/equity ratio.

Measures to Control Leverage

Two of the measures to control leverage are capital adequacy requirements and minimum leverage ratios. Capital adequacy ratio measures if the bank has sufficient capital relative to the risk being undertaken for various business activities. It is measured by dividing the core capital (Tier I and Tier II) of the bank, with its Risk Weighted Assets.

CAR=Tier 1 capital+Tier 2 capitalRisk weighted assetsCAR = \frac{\text{Tier 1 capital} + \text{Tier 2 capital}}{\text{Risk weighted assets}}

  • Tier 1 = (Paid up capital + Disclosed free reserves + Statutory reserves) - (Equity investments in subsidiaries + Intangible assets + Current and brought forward losses)
  • Tier 2 = Undisclosed reserves + General loss reserves + Hybrid debt capital instruments and subordinated debts
  • Risk Weighted Assets = Assets weighted by their risk. For the weights, the risk coefficients are based on the credit ratings and other factors of bank assets. For example, a mortgage (with collateral) is considered less risky than an unsecure loan.

As per Basel III, capital adequacy ratio should be 10%. This number is set after consultation and agreement with various participating members of Basel III.

CAR measures the capacity of the bank to take losses if any of their investments go bad. They help measure different types of risk like operational risk and credit risk.

The other measure, leverage ratios, assess how much of the bank’s assets have been financed with equity. The nature of the assets is not important. It allows for a cap on borrowings as a multiple of the banks’ equity.

The use of a risk management framework while extremely useful is not in itself adequate to measure and control leverage. It is possible that all risk factors are not inputted at the appraisal stage. An under measurement of risk can lead to several faulty investments.

Role of Basel III

Basel III aims at removing these gaps through various recommendations.

It has incorporated these changes based on the Banking Crisis and hopes that in introducing these measures it will help banks become more robust and resilient in their operations and investments. There is not much change on how balance sheet assets are treated. It has focused on the treatment of exposures of repos, derivatives and loan commitments.

Netting of Securities Financing Transactions is allowed to a certain degree, when fixed criteria are met. This netting criteria has been reworked to meet international compatibility, since various accounting standards have different criteria. In doing so the actual degree of leverage is better understood.

Secondly, variation margins can be netted against derivative exposures when the margin is paid in cash. This helps measure the leverage since cash margin payments are settlements of liabilities. Taking cash collateral against derivative exposures are a good risk management practice and in conforming with regulatory reforms.

Banks are allowed to net long and short credit derivatives on the same underlying (security or asset that provides cash flow to the derivative). Both the hedge and the underlying must have the same maturity period.

The measure of off-balance sheet items are their credit equivalent value. This helps reflect the true degree of leverage in these transactions.

Basel III has also recommended a disclosure template in which gross and net information for SFTs, and the gross notional and credit equivalents of off-balance sheet items can be shared.

Banks now have to declare their leverage ratios, starting from 2015. Banks are encouraged to have a strong risk management framework, where leverage ratios simply work as a support and not the deciding factor. In having prudential controls banks will not overleverage themselves to the point of excessiveness. Banks have to use both the risk framework and leverage ratios in tandem to maintain the right level of leverage.

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Data Science in Finance: 9-Book Bundle

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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
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  • 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.