Asset and Liability Management for Banks and Insurance Companies

 
 
Wiley-ISTE (Verlag)
  • erschienen am 5. August 2015
  • |
  • 166 Seiten
 
E-Book | ePUB mit Adobe-DRM | Systemvoraussetzungen
978-1-119-18461-4 (ISBN)
 
This book introduces ALM in the context of banks and insurance companies. Although this strategy has a core of fundamental frameworks, models may vary between banks and insurance companies because of the different risks and goals involved. The authors compare and contrast these methodologies to draw parallels between the commonalities and divergences of these two services and thereby provide a deeper understanding of ALM in general.
1. Auflage
  • Englisch
  • Hoboken
  • |
  • USA
John Wiley & Sons
  • 3,24 MB
978-1-119-18461-4 (9781119184614)
weitere Ausgaben werden ermittelt
  • Intro
  • Table of Contents
  • Title
  • Copyright
  • Introduction
  • 1: Definition of ALM in the Banking and Insurance Areas
  • 1.1. Introduction
  • 1.2. Brief history of ALM for banks and insurance companies
  • 1.3. Missions of the ALM department
  • 1.4. Conclusion
  • 2: Risks Studied in ALM
  • 2.1. Introduction
  • 2.2. Risks studied in a bank in the framework of Basel II and III
  • 2.3. Stress tests
  • 2.4. Risks studied in an insurance company in the framework of Solvency II
  • 2.5. Commonalities and differences between banks and insurance companies' problems
  • 2.6. Conclusion
  • 3: Durations (Revisited) and Scenarios for ALM
  • 3.1. Introduction
  • 3.2. Duration and convexity risk indicators
  • 3.3. Scenario on the cash amounts of the flow
  • 3.4. Scenario on the time maturities of the flow
  • 3.5. Matching asset and liability
  • 3.6. Matching with flow scenarios
  • 3.7. ALM with the yield curve
  • 3.8. Matching with two rates
  • 3.9. Equity sensitivity
  • 3.10. ALM and management of the bank
  • 3.11. Duration of a portfolio
  • 3.12. Conclusion
  • 4: Building and Use of an ALM Internal Model in Insurance Companies
  • 4.1. Introduction
  • 4.2. Asset model
  • 4.3. Liability model
  • 4.4. Structure of an ALM study
  • 4.5. Case study
  • 4.6. Conclusion
  • 5: Building and Use of ALM Internal Models in Banks
  • 5.1. Introduction
  • 5.2. Case 1: Reduction of gaps
  • 5.3. Case 2: A stochastic internal model
  • 5.4. Calibration of the models
  • 5.5. Example
  • 5.6. Key points for building internal models
  • 5.7. Conclusion
  • Conclusion
  • Bibliography
  • Index
  • Wiley End User License Agreement

1
Definition of ALM in the Banking and Insurance Areas


1.1. Introduction


In recent years, the technique known as asset and liability management (ALM) has enjoyed remarkable popularity. Initially pioneered by English-speaking financial institutions during the 1970s as an actuarial and cash flow matching technique, ALM has grown into an essential framework for banks and insurance companies.

The objective of ALM is to ensure the proper coordination between assets and liabilities to achieve the financial targets for a specified level of risk and under predefined constraints. The ALM department, whether in an insurance company or in a bank, is therefore responsible for producing studies providing recommendations on marketing strategy and asset allocation.

In recent years, the ALM department has become increasingly important in a bank or an insurance company for three main reasons. First, modeling tools are increasingly sophisticated, facilitating making relevant cash flow projections. Second, accounting standards, which are central in ALM business, are constantly evolving. Last, but not least, financial communication is increasingly regulated.

This chapter is devoted to the definition of ALM in the banking and insurance areas. We will specifically focus on the history of ALM and the missions of an ALM department.

1.2. Brief history of ALM for banks and insurance companies


Prior to the 1970s, interest rates in developed countries varied little and thus losses caused by asset and liability mismatches were low. The proceeds of their liabilities (for example deposits, life insurance policies or annuities) were invested in assets such as loans, bonds or real estate. All assets and liabilities were held at book value, hiding possible financial risks if assets and liabilities were to diverge suddenly.

In the 1970s, a period of volatile interest rates started and continued until the early 1980s. This volatility had dangerous implications for financial institutions. US regulation, which had capped the interest rates that banks could pay depositors, was abandoned to arise a migration overseas of the market for USD deposits. As most firms used accrual accounting, the emerging risk was slow to be recognized. Firms gradually accrued financial losses over the subsequent 5 or 10 years.

The most famous example is that of Equitable, a US mutual life insurance company. During the early 1980s, the USD yield curve was inverted. Equitable sold a number of long-term Guaranteed Interest Contracts (GICs) guaranteeing rates of around 16% for periods up to 10 years. During this period, GICs were routinely exchanged with a principal of USD 100MM or more. Equitable invested in short-term interest rates to pay the lower longterm high interest rates they guaranteed to their clients. But short-term interest rates soon collapsed. When Equitable had to reinvest, they could not get a sufficiently high interest rate to pay their GICs, and the firm was crippled. Ultimately, Equitable had to demutualize and was then acquired by the Axa Group.

Learning the lessons from Equitable, managers of financial firms focused on developing a sounder ALM. They sought ways to manage balance sheets in order to maintain a mix of loans and deposits consistent with the bank's goals for long-term growth and risk management. Thus, they started developing new financial techniques such as gap analysis, duration analysis or scenario analysis.

ALM practices have evolved since the early 1980s. Today, financial firms, particularly investment banks that enter trading operations daily, are increasingly using market-value accounting for certain business lines. For trading books, techniques of market risk management (for example Value-at-Risk) are more appropriate than techniques of ALM. In financial firms, ALM is used for the management of assets and liabilities that must be accounted on an accrual basis. This includes bank lending, deposit taking and essentially all traditional insurance activities.

ALM techniques have also evolved. The growth of derivatives markets has facilitated a variety of hedging strategies. A significant development has been securitization, which facilitates firms to directly address asset and liability risk by substantially removing assets or liabilities from their balance sheets. This not only reduces asset and liability risk but also frees up the balance sheet for new business.

The scope of ALM activities has widened. Today, ALM departments are addressing a wider variety of risks, including foreign exchange risks. Also, ALM has extended to non-financial firms. Corporations have adopted some of the ALM techniques to manage interest-rate exposures, liquidity risks and foreign exchange risks. They also use related techniques to address commodities risks.

Nowadays, the process of ALM is at the crossroads between risk management and strategic planning. It not only offers solutions to mitigate or hedge the risks arising from the interaction of assets and liabilities, but also conducts the bank or the insurance company from a long-term perspective.

1.3. Missions of the ALM department


The objective of this chapter is to define the different missions of an ALM department in a bank or an insurance company. These two entities share the same goals, which are to analyze economic risks (mainly market risk), to produce studies providing recommendations on marketing strategy and asset allocation, and to monitor the implementation of those strategies. However, the underlying business is not the same between banks and insurance companies, and therefore the missions of their ALM department can differ.

1.3.1. Missions of the ALM department for banks


The first mission of ALM was essentially to manage interest risks and liquidity risks to prevent mismatches between the cash flows of the assets and the cash flows of the liabilities. This is why ALM uses concepts such as liquidity gap to quantify liquidity risks, and more mathematical indicators such as duration or convexity introduced a long time ago by McCauley. This led to the ALM policy of immunization which aimed to structure financial cash flows in a way that minimizes their sensitivity to small changes of the underlying interest rates. Thus, the ALM committee had to work hand in hand with the other departments of the bank and soon played a central role within the structure of the bank.

In 1988, the first Basel rules extended the field of application of ALM even more. They gave the ALM department supervision of other financial risks such as the equity risks, in addition to the traditional liquidity and interest rates risks. Therefore, progressively, ALM gained a central position in the management of the bank, often inside the risk management department. However, the ALM department must keep, as far as possible, a total independence within the firm.

In summary, ALM aims to coordinate the financial decisions of a firm so that the structure of its assets and liabilities optimizes both the financial benefits and the underlying risks, while respecting the prudential rules imposed by the regulators.

As we will see in Chapters 3 and 5, different deterministic or stochastic models exist which are particularly useful for risk managers.

1.3.1.1. Deterministic models

In a deterministic model, the evolution of the different financial variables (such as interest rates, equity volatility, etc.) during a given period of time is deterministic. This defines a single scenario, called the central scenario. This central scenario is used to project the cash flows generated by the firm's assets and the cash flows generated by the firm's liabilities and to study the discrepancies between these two series of cash flows. Of course, this initial study has to be complete with the consideration of other possible scenarios for the considered cash flows.

Nevertheless, deterministic models are useful to quickly detect the weak and strong points of hedging strategies and to have a basic understanding on how to reduce the eventual mismatches.

1.3.1.2. Stochastic models

To face the uncertainty of economic, financial and social evolution in the future, the use of stochastic models is necessary. However, stochastic models simple enough to be easily implemented and parameterized tend to rely on strong assumptions which are unfortunately sometimes unrealistic.

Nowadays, the models used in ALM are directly borrowed from quantitative finance. In Chapter 5, we will see how we can build such a model for the evolution of equities.

These models are also quite useful for the VaR computation. The VaR is an indicator of solvability recommended by the Basel authorities as well as by Solvency II for insurance companies.

Stochastic models are also used for the simulation of possible scenarios, and for each of them, basic risk and profit indicators can be computed.

1.3.1.3. Mission of the bank ALM department

The ALM department has to coordinate the management of assets and liabilities in such a way that benefits are optimized under an acceptable level of risk. This level of risk is now imposed by the regulatory authorities. This implies that the ALM department must have an overall, long-term view of the financial activity of the bank. Using different economic scenarios, the ALM department gives the necessary information to the Board of Directors of the bank so that they can soundly plan future financial investments.

The coordination of assets and liabilities was...

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