Module 21: Uses of models in ERM Flashcards
3 Main uses of models
- to enable the actuary or risk manager to give an organisation appropriate advice so that it can manage its risks in a sound financial way (avoiding sub-optimal decisions)
- to assist in the day-to-day running of the company, eg assist in
- – decision making,
- – product pricing,
- – capital allocation,
- – project evaluation, etc
- to help determine suitable checks and controls on the business.
parameter risk
refers to the use of inappropriate or inaccurate parameters or assumptions within models
model risk
(a type of operational risk)
risk arising from the use of an inappropriate or inaccurate model when assessing or managing risks.
Use of inappropriate or inaccurate models and/or parameters might be due to: (4)
- stochastic uncertainty arising from the randomness of a finite set of observations
- erroneous, incomplete and/or heterogeneous data
- insufficient investigation into alternatives
- over-simplification or inappropriate complexity (lack of parsimony)
How might parameter uncertainty be allowed for? (2)
By dynamically simulating the parameters, using either:
- a multivariate normal distribution (if a covariance matrix is available), or
- a joint distribution for the parameters (simulated by repeatedly re-fitting parameters to sets of data points each modelled using the original data set).
6 Features of a good actuarial model specific to an ERM application
- amenable to an analysis of the impact of parameter uncertainty or incorrectly-specified parameter values
- exhibit behaviour in simulations that is consistent with the past, but should not exclude different but plausible future scenarios
- reflect the dynamics of the organisation, now and as expected to develop in the future, allowing for wider external factors
- be defined to be comprehensive across all important well-defined risks
- produce outcomes that are balanced, ie not unduly exaggerated or unduly smooth
- any shortcomings of the modelling scheme should be clearly stated.
10 Steps in developing and applying a model
- specify the purpose
- collect data then group or modify as necessary
- choose the form of the model, identifying its parameters and variables
- select the appropriate period for calculating cashflows
- estimate parameters and correlations
- ensure acceptable goodness of fit
- ensure that the model is able to project all required cashflows and other outputs, including interactions between them
- run the model using the estimated variables or stochastic simulations
- output the results in an appropriate format
- perform sensitivity tests
The ERM model should produce a range of outputs: (3)
- deterministic plus ranges / sensitivities
- stochastic distribution
- economic value added (EVA) and other risk-adjusted metrics
The review and discussion of the outputs needs to reflect: (5)
- corporate risk policy
- corporate risk appetite
- corporate risk preferences - to select between options on the efficient frontier
- risk preferences and other investment opportunities of the company’s owners - if a market-consistent approach is adopted - but in practice, external and internal perspectives are important
- qualitative factors, judgement and intuition
Define: model
A model is a mathematical representation of real-world processes.
The representation will be imperfect.
Stochastic uncertainty
Arises from the randomness of a finite set of observations.
As the number of observations increases, then the certainty in any model, its parameters and its predictions also increases.
Stochastic models acknowledge the presence of this uncertainty by producing a range of results, rather than a single (deterministic) answer.
3 Assumptions that can be made in relation to the choice of model:
- The true model or class of models is known.
- The model used is a SIMPLIFICATION of a KNOWN, more complex reality.
- The model used as an APPROXIMATION to an UNKNOWN, more complex reality.
Outline the main requirements for a good GENERAL actuarial model
Valid, rigorous for its purpose and adequately documented
Adequately reflect the distribution of the business being modelled
Components of the model must allow for those features of the business being modelled that could significantly affect the advice being given
The workings of the model should be easy to appreciate and communicate. The results should be displayed clearly.
The outputs from the model should be capable of independent verification for reasonableness and should be readily communicable to those to whom advice will be given.
The model should be capable of subsequent development and refinement - nothing complex can be successfully designed and built in a single attempt.
The model, however, must not be overly complex so that either the results become difficult to interpret and communicate or the model becomes too long or expensive to run, unless this is required by the purpose of the model. It is important to avoid the impression that everything can be modelled.
Outline why an organisation might build a model for ERM decision-making
- pricing of products of services
- assessment of the economic value of the company
- estimation of capital adequacy requirements, including regulatory requirements and internal economic capital assessments
- projection of the future capital or solvency position
- assessment of the effect of risk management and mitigation techniques on both profits and capital requirements
- assessment of the effect of other strategic decisions, eg changes in investments or new business strategy
- valuation of projects
Economic value
The present value of all future shareholder profits, determined on a realistic economic basis.
