Financial planning practice

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Risk of unemployment/business failure : The vast majority of pre-retirement clients rely on income from employment or self-employment to maintain their standard of living. Planners should recommend that clients put in place an emergency fund to provide for them in the short term should they ever lose their job or their business fails, as most people will find state benefits inadequate to meet their cost of living. Typically, an emergency fund would cover 3-6 month’s net income. It is also possible to arrange unemployment insurance, which essentially is short term income protection for a period of 12 or 24 months. These are however only temporary measures and long term loss of income will have more far-reaching effects

Risk to home: Most clients’ main asset is their home - where the home and its contents are not insured or underinsured, the client could face a significant financial loss. Planners should ensure that clients are adequately covered in this area.

Risk of death (Mortality Risk): Planners can make provision for the financial consequences of the client’s death to their family, for example using life assurance and/ or trusts.

Risk of illness or disability (Morbidity risk):   Clients could experience a significant drop in income should they be unable to work due to illness, accident or disability, particularly over the longer term once any employer sick pay or emergency fund runs out. Even where no longer of working age the client could face significant additional expenditure as a result of any such illness or disability, such as the cost of care or adjustments to their home. Again, the planner can arrange insurance for the client for these eventualities.

Investment Risk

One of the fundamentals of investing is the trade-off between risk and returns. Investment risk could be considered to be the risk of an investment falling in value, of the client losing all of their money or of them not achieving their objective(s). It is important that the planner reaches a mutual understanding with the client regarding investment risk, as the client’s understanding may be very different to theirs.

Taking on little to no investment risk, by for example keeping your money in cash deposits, will almost certainly lead to very modest returns over the longer term. Once inflation is taken into account this may even produce negative ‘real’ returns, particularly in the current economic environment.

Where a greater level of investment risk is taken then there is a better chance of higher returns over the longer term, however at the same time there will also be a greater possibility that the investment could lose money in the shorter term.

Risk Premium

The difference between the expected return on a ‘risk free’ (or less risky) asset and the expected return on a riskier one, is often described as the ‘risk premium’. This is the potential ‘compensation’ an investor might receive in exchange for the risk taken and each individual will have a different view on what level of risk premium is worth taking the risk for. This is where examples of typical returns from different portfolios can be very useful, such as those produced via stochastic modelling (which is covered later on in this chapter).

The planner must therefore determine what level of risk the client is prepared to take, i.e. what level of losses they are prepared to accept in exchange for potential returns. They must also establish what risk means to the client and what effect any losses would have on their standard of living. The general term for this process is ‘Risk Profiling’ which is also covered later on in the chapter.

The potential portfolio returns should then be calculated for a given risk profile and the planner can then determine whether or not the returns are likely to be sufficient to meet the client’s objectives. Where the potential returns are insufficient to meet the client’s objectives, then these objectives may have to be revised. Alternatively, the potential returns may be higher than required, in which case the client can actually afford to take a lower level of risk.

Measuring Investment Risk

Volatility

There are several different dimensions to investment risk, however the default measure of the risk of any investment tends to be volatility. Indeed, volatility is sometimes used as the sole measure of risk, which was a serious concern highlighted by former regulator the FSA on their guidance paper entitled “Assessing suitability: Establishing the risk a customer is willing and able to take and making a suitable investment selection”. This is available to download here  and outlines a number of examples of both good and poor practice on how risk and capacity for loss (which is covered later in the chapter) should be established and is a very useful tool for reference.

The main reason why using volatility as the sole measure of investment risk is inadequate is because it ignores the other elements of risk inherent in investments, such as:

Inflation risk

Interest rate risk

Reinvestment risk

Credit or counterparty risk

Currency Risk

Liquidity risk

Political risk

Economic risk

Event risk.

Standard Deviation

An investment’s volatility is based on the ‘standard deviation’ of returns, which is the extent to which actual returns on an investment deviate (historically) from the mean average return. The greater the deviation then the greater the volatility and the more ‘risky’ the investment is classed.

Whilst there is an obvious danger in using past returns to try and predict those in the future, the use of standard deviation does at least enable the planner to give clients a predicted range of returns to help quantify the risk they are taking on.

Without going into the mathematics behind the calculations, the theory is that returns should be within one standard deviation around 68% of the time, within 2 standard deviations 95% of the time and 3 standard deviations 99% of the time. In other words, if the standard deviation on an investment is 4% and the mean return 6%, then the expected range of returns should be:

2% -10%

68% of the time

-0.16

95% of the time

-0.24

99% of the time

Advantages of volatility/standard deviation as a measure of risk

Provides a set of parameters for expected returns

Gives client likely potential outcomes

Helps quantify the risk being taken on

Disadvantages

Based on past performance statistics, which may be very different to actual fluctuations in the future

Standard calculations assume a normal distribution of returns: some research suggests that a normal distribution curve is not a valid basis of describing investment markets

Severe market conditions, such as those during the financial crisis in 2008, can lead to returns way beyond 3 standard deviations of the mean, which questions the validity of the method as a whole

Drawdown

Drawdown is a simpler method of measuring risk, which measures the loss an investor would have suffered had they invested at the high point (peak) of an investment and sold...

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Some questionnaires are used alongside model asset allocations and investment portfolios, with each risk profile linked to a particular model. These models are most commonly generated using stochastic modelling (also known as Monte Carlo simulations).

There are, however, some major drawbacks with this approach and the planner should bear in mind the following:

Model asset allocation and portfolios linked solely to a client’s risk score do not usually take into account a client’s capacity for loss. Where capacity for loss is limited or non-existent then relying on the output alone would lead to clients being invested in too high a risk portfolio than if the planner had considered the full circumstances

Questionnaires and tools provided by product providers may well be biased in favour of their own funds

The models do not take into account any existing investments the client may have and could lead to them being overexposed in certain sectors or asset classes

They do not take into account any sector preferences or ethical views a client may have

Stochastic modelling is used in many other fields besides investment and is used to try to predict the effects of future events. Stochastic models for asset allocation are based on past performance and volatility data, as well as assumptions around future interest and inflation rates, bond yields etc. The model will produce a range of portfolios and forecast the most likely returns from each, together with the probability of achieving these outcomes.

The range of returns for each portfolio will usually be displayed graphically in a kind of diamond shaped figure, with the middle, wider part of the diamond representing the most likely potential return and the top and bottom points of the diamond the highest and lowest likely returns. The greater the distance between the high and low points of the diamond then the greater the range of likely returns.

The benefit of these models is that they can help the client to understand the relationship between risk and reward by showing them a range of likely returns.

Hypothetical output from a stochastic modeller: Investment of £100,000 over 20 years

Key:

A:  Most likely outcome/Average Growth

B:  Most optimistic outcome/Very good growth (<5% probability/95 th percentile)

C: Most pessimistic outcome/Very poor growth (<5% probability/5 th percentile)

Portfolio A (10% Equities)

Outcome

Potential return

A

£150,000

B

£300,000

C

£125,000

Portfolio B (40% Equities)

Outcome

Potential return

A

£250,000

B

£380,000

C

£175,000

Portfolio C (60% Equities)

Outcome

Potential return

A

£300,000

B

£500,000

C

£180,000

Advantages of stochastic modelling

Gives clients a better idea of the relationship between risk and reward

Gives clients an educated forecast of the kind of returns to be expected from each risk profile

Disadvantages

Clients may misinterpret the top and bottom end of the range of returns as actual maximums and minimums

Clients may place too much reliance on the figures and be disappointed if the most likely return is not achieved

Forecasts are based on past performance data and a number of assumptions – the chances of accurately predicting future returns are, of course, remote

Assumptions used in stochastic modelling

The main assumptions required for stochastic modelling and (financial planning modelling in general) will be assumptions about future rates of:

Inflation

Equities (rates of growth, dividends and volatility)

Property (as above)

Gilts/Fixed Interest (as above)

Deposit rates

Earnings

It goes without saying that these rates need to be regularly reviewed as conditions change. As an example, the assumed rate of inflation may start at 2.5% but require regular adjustment as economic conditions change.

The basic principles on using assumptions are that they are reasonable, realistic and consistent. A default growth rate for UK equities for example may currently be 5% per annum - if an assumption of 10% pa were used instead this would be considered overly optimistic, whilst a rate of 2% would be overly pessimistic. Both assumptions would significantly impact and distort the model produced compared to a model produced using the default rate.

Models may base their assumptions on predicted future trends, historical data or a mix of both. These are really the only avenues available to us, however both methods have their own drawbacks:

Historical data:

Rates that applied in the past are highly unlikely to reoccur exactly in the future. Ever changing economic and world conditions will have more of an effect that what happened in the past

Variability - rates based on past data will vary greatly depending on the time period used, i.e. average equity returns over 5 years compared to 10 years or 20 years

Future trends

Heavily reliant on the forecaster and how realistic and informed their predictions and assumptions are

Future predictions have the capacity to vary much more widely (renowned experts in the same field may disagree significantly)

Where the planner is using third party software they must familiarise themselves with the assumptions used and ensure that they are comfortable with the rates, how they are produced and also how they are reviewed.

Changing risk profiles

Once a client’s risk profile has been assessed initially, it may not remain static throughout their lifetime and will need to be regularly reassessed, typically at an annual review of their financial plan. Common factors that may alter their risk profile and capacity for loss would be:

Experience: As an investor becomes more used to dealing with the ups and downs of  stock markets, the level of risk they are prepared to take may increase. Conversely, a bad first experience may have the opposite effect.

Personal Circumstances: A change in the client’s health, employment or family situation may alter the level of risk they are prepared to tolerate as will the inheritance of capital.

Change in objectives: a change in the client’s objectives may lead to an objective being met earlier or later, or perhaps becoming unachievable, based on the assumptions made in the financial plan.

Shortfall Risk

Shortfall risk is the risk that the client may not achieve the rate of return required to meet their objective, such as a certain level of income in retirement. This may be because the capital available and expected rate of return combined would simply not be enough to produce the target fund, or in the case of an existing financial plan it may be that the investment has badly underperformed.

In such a scenario the client essentially has four choices:

Invest additional funds (if available)

Increase the term of the investment

Accept a lower target fund/standard of living in retirement

Increase the level of risk to try and achieve higher returns and a higher target fund.

Clearly, the fourth option is a very risky strategy, which invites the possibility of creating an even larger shortfall than the one that currently exists should the riskier investment(s) perform badly. It could also lead to compliance problems and should rarely be employed.

How often would returns be expected to be within 2 standard deviations on an investment?

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Once all the information has been gathered, which is likely to be in various formats including paper correspondence, emails, faxes, photocopied or scanned documents and file notes of telephone conversations, it will need to be assembled and organised in a manner that makes it practical and simple for the planner to analyse.

One very effective way of preparing data for a...

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Many planners prefer to design their own systems and produce more customised reports to aid them in their analysis, using the likes of Microsoft Word and Excel. Whichever system is used, the goal will be the same, namely the ability to quickly and efficiently produce the relevant (and only the relevant) information for further analysis once gathered.

Aside from the factfind document, in what other formats might you expect client information to be gathered?

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Some examples of discrepancies that could arise, which the planner would then query with the client and/or third parties, could be:

The client’s tax return shows a much higher...

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The client believes their life assurance policy is written under trust but the information from the provider says otherwise. Where such a discrepancy arises the planner should attempt to get a copy of any original documentation the client may have and investigate further whilst asking the provider to double check their records.

Where a client’s income tax bill is much higher than the planner expects, what might this be a sign of?

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