ERM Chapter 25 Flashcards
Why may it not be possible to apply quantitative techniques to liquidity risk?
- historic data on liquidity crises is limited
- the degree and nature of every organisation’s exposure to liquidity is different, so industry data or other analogues may not be useful
What are the main sources of cash inflows for a bank?
- revenues/income generated by assets and liabilities
- proceeds from the sale of assets
- drawing upon sources of liquidity e.g. issue of new debt or equity
Outline the key challenges in modelling cash inflows for a bank.
- revenue/income generated by assets can be modelled with a reasonable degree of confidence
- there is less confidence regarding the cash proceeds generated from the sale of assets (sale may be forced, or made during a time of depressed asset prices)
- much of a bank’s asset base is in the form of long-term mortgages that are not readily converted into cash
- it is important to allow for factors limiting the extent and speed of liquidity transfers within an organisation and between distinct entities. Such factors may be legal, regulatory or operational in nature
- it may be difficult to model the issue of new debt or equity reliably due to poor demand from the capital markets for these assets as a result of poor credit rating and/or business results
Scenario testing should be used to examine scenarios where cash outflows exceed available cash at future points in time. These should be considered for both short-term and long-term scenarios.
Describe seven specific scenarios that should be considered for banks and insurance companies.
- Rising interest rates - banks may find depositors transfer funds elsewhere in search of higher returns.
- Ratings downgrade - banks may find depositors transfer funds to a more secure institution.
- Large operational loss - resulting in a sudden reduction in cash-like assets
- Large single insurance claim or a large set of claims from associated events - resulting in a sudden reduction of cash assets
- Loss of control over a key distribution channel - resulting in a loss of expected revenues
- Impaired capital markets - equity investors or bondholders may be unable to provide fresh capital where required
- Sudden termination of a large reinsurance contract - leaving an insurer exposed to large cash outflows, but without expected inflows from the reinsurance contract
Define demographic risk.
- Risk arising from population changes (e.g. mortality rates) that impact on both customers and employment.
- Demographic risk can be broken down into:
> level risk - the risk that the particular underlying population’s claims incidence and intensity is not as expected over the immediate future e.g. due to shortcoming in the underwriting process
> reserving risk:
> volatility risk - uncertainty with regard to the actual future immediate mortality experience. Arises due to having a finite pool of policies
> catastrophe risk - an extreme form of volatility risk e.g. the occurrence of a natural disaster resulting in a large number of deaths
> trend risk - the risk of future changes in claims incidence and intensity
Describe the distinct methods used to determine the current underlying level of mortality.
- Experience rating:
Examining the number of deaths in a portfolio of lives to determine the initial mortality rate or central mortality rate - Risk rating:
Modelling the mortality rate of each homogeneous group as a function of the shared characteristics of their members. e.g. postcode rating
Credibility weighting:
- Combining the experience rating and risk rating methods. Using a subjective credibility weighting factor Z, and combining the two mortality rates in the proportion Z and 1-Z.
- Relies on the data being divided into homogeneous groups, and data being collected over a period which is sufficiently long to generate adequate data, but not so long that the mortality rates could have varied greatly.
How is volatility risk assessed?
- volatility risk can be modelled probabilistically or stochastically assuming some underlying statistical process e.g. binomial or Poisson
- assessment process should reflect that volatility risk varies by age
How is catastrophe risk assessed?
- the risk of sudden, temporary increases in mortality is best modelled using scenario analysis e.g. a scenario where there is a 20% increase in mortality at all ages
- more complex dependencies can be modelled by copulas e.g. consider multiple sources of mortality as separate risk factors with their own probability distribution
What are the subsets of non-life insurance risk?
- Level risk
- Reserving risk:
> volatility risk
> catastrophe risk
> trend or cycle risk
How does the nature of non-life insurance risk differ from demographic risk?
- trend or non cycle risk is more likely to correspond to the economic cycle, and so is best assessed using scenario analysis
- generally non-life insurance risks have a shorter period of exposure than life insurance risks so longer term changes in risk factors are less important than a correct assessment of the risk factors themselves
- unlike demographic risks, non-life insurance risks can be divided into high frequency risks (e.g. motor) and low frequency risks (e.g. XoL reinsurance)
- intensity of claims also need to be assessed for non-life insurance claims
- non-life insurance risks may experience more than one claim and move through different states over the lifetime of the policy
Under the Basel Accords, banks must maintain which sufficient liquid resources?
Liquidity Coverage Ratio (LCR) - designed to ensure that banks can survive a one-month stress scenario
Net Stable Funding Ratio (NSFR) - designed to consider funding over a one=-year time horizon
