Monte Carlo simulation in financial planning: a guide for advisers

Most advisers know what a Monte Carlo is. But if you've ever struggled to explain what it's for or why run it when you already have a plan, this article is for you.

The FCA's guidance on cashflow modelling says there is a risk that clients see a detailed projection of their finances as a certainty. It also says firms have historically explained poorly that cashflow modelling is based on assumptions. Showing plausible alternative scenarios helps address both.

Monte Carlo simulation helps here. It tests a plan against many possible market outcomes and shows the range, not a single result. It is now available in FE CashCalc as well as the net modeller, which makes this a good moment to cover the basics.

This guide explains what Monte Carlo simulation is, what it can and cannot tell you, how to read the results and how FE CashCalc runs it.

What is Monte Carlo simulation?

Monte Carlo is a type of stochastic model. It's a stress test that runs a plan many times, each time with a different sequence of market returns. A standard cashflow projection assumes a fixed rate of return each year, so it shows one outcome. Monte Carlo shows a distribution of outcomes.
A Monte Carlo test runs a large number of possible market scenarios, each reflecting different combinations of returns, volatility and economic conditions. Each simulation is a plausible version of the future, from favourable markets through to adverse ones.

The result is a range. It lets an adviser and client see how the plan performs across that range, rather than relying on a single assumed path.

What does Monte Carlo tell you, and what does it not?

Monte Carlo tells you how a plan behaves across many outcomes. That makes it useful for three things:

Showing the range. Clients see the spread, not one line.
Highlighting the downside. The weaker outcomes are visible, which supports a conversation about risk.
Testing decisions. You can change the plan and run it again to see the effect.

It does not predict the future. Simulations rest on assumptions and give insight into possible outcomes, not certainty. The FCA adds that firms should have a reasonable and justifiable basis for their assumptions, and that projections based only on past patterns of returns are unlikely to mirror the future.

That means the quality of the result depends on the quality of the inputs: the client data, the return assumptions, the charges and the tax. Professional judgement stays central to the advice.

How do you read Monte Carlo results?

Reading the output well is what turns a simulation into a useful client conversation. In FE CashCalc, the results show a graph of a random 200 of the scenarios and a yearly breakdown at three levels.

Percentile	What it shows	How to use it in a meeting
25th	The pessimistic outcome	Talk about the downside and what the client could change
50th	The average outcome	Use it as the reference point
75th	The optimistic outcome	Show the upside, but do not lead with it

The FCA's guidance suggests highlighting lower percentile outcomes in stochastic output. That is why the 25th percentile deserves attention in the meeting.

In practice, this looks like the following.

1. Start with the graph. It plots a random 200 of the scenarios, so you can see the spread at a glance.

2. Look at the 25th percentile. Check how the plan holds up if markets are weaker than expected.

3. Compare it with the 50th percentile, which is the middle outcome.

4. Look at the 75th percentile to see the upside.

5. Read the yearly breakdown for money in, money out and the charges applied.

6. Check the minimum threshold, which tests whether the plan reaches the figure the client needs.

7. Change the plan and run it again, for example by changing which pots are included.

Take the reading one level at a time. A client who sees all three percentiles at once may focus on the best figure, so lead with the weaker outcome and then widen the view.

How does FE CashCalc run Monte Carlo?

Monte Carlo sits in the stress testing section of the FE CashCalc gross cashflow modeller. It was already available in the net modeller and works in the same way in both. If you are choosing between the two, our guide to gross and net cashflow blog explains when to use each.

Choose the pots to include. Select one pot, any combination or all of them.
Set the asset allocation that informs the growth template, the age to run the simulation for and a minimum threshold.
Run 10,000 simulations.

You can run one simulation across all pots or any combination of them. FE CashCalc takes the contributions, withdrawals and charges from your gross cashflow and applies them to the combined pot. Percentage charges are blended: it works out the charge for each pot, adds them together and divides the total by the combined value.

The gross modeller also calculates the tax due on the figures you enter before tax, so the stress test sits on a plan that already includes it. You can run Monte Carlo straight from your gross plan with no rekeying, save the simulation, change the pots and run it again, and print a report listing the pots, parameters, charges and money in and out.

Put it to work on your next review

Monte Carlo is most useful when it is part of the conversation, not an appendix. Start with the graph, lead with the 25th percentile and use the yearly breakdown to explain what is driving the outcome.

You can run it on any saved gross cashflow model, so your next annual review is a natural place to try it. There is no need to rebuild the plan in another modeller.

Try Monte Carlo in FE CashCalc, our cashflow planning software, and see how your clients' plans look across the full range of outcomes.

Try Monte Carlo in your gross plans

Monte Carlo in the gross cashflow modeller gives you a stress test across any combination of pots, with no rekeying, a yearly breakdown at three percentiles and a printable report. It is included in your existing FE CashCalc subscription, so you can use it on your next client plan.

Explore FE CashCalc

FAQs

Frequently asked questions

Monte Carlo simulation tests a plan against many possible market outcomes, each with a different sequence of returns. It shows a range of results instead of a single projection.

FE CashCalc runs 10,000 simulations. The results show a graph of a random 200 of the scenarios and a yearly breakdown at the 25th, 50th and 75th percentiles.

The 25th percentile is the pessimistic outcome, the 50th is the average outcome and the 75th is the optimistic outcome. Together they show the spread of results across the simulations.

No. Monte Carlo shows possible outcomes based on the assumptions you use. It gives insight into the range of results, not certainty, so professional judgement stays central.

In the UK, Monte Carlo is available in both the gross and net cashflow modellers. In the gross modeller, you can run it on any saved gross cashflow model.