Financial Planning Insights
4 minute read time
One of the tools advisors use to help clients navigate the complex territory of financial planning is Monte Carlo simulations. This widely used method calculates a probability score that suggests how well your financial plan will stand up to varying market conditions. Planners understandably attempt to get their client’s Monte Carlo score as high as possible, but equating a high Monte Carlo score to a successful plan is at best an oversimplification and at worst, bad planning.
The critical question is what does a high Monte Carlo score mean? What it means is the probability that (1) based on the assumptions built into the plan, and (2) no alterations in spending or saving, (3) the client’s chosen planning goals will be achieved. The higher the score, the more confidence clients should feel that their chosen goals will be met. In isolation, that is positive. But it’s also incomplete. If an advisor’s Monte Carlo analysis shows a 90% chance of success (a very “good” Monte Carlo score), what next? For many advisors, there would be no “next.” They define their role as building bulletproof financial strategies, and 90% is about as certain as a plan gets in an immanently uncertain world.
I would politely, but firmly challenge that underlying assumption. The advisor role is less being an insurer of “set it and forget it” certainty, but rather an ever present financial sherpa leading clients to their personal financial summits over treacherous terrain. Let me explain what I mean by that.
The place to start is what really is a financial plan and how does it differ from financial planning?
A financial plan, like a Monte Carlo analysis, is a static financial analysis. It is meant to deliver information. That information is based on a set of assumptions and behaviors, will you be able to accomplish financial goals. That analysis creates a very helpful tool, it provides advisors with financial support for the advice they can ultimately give to their clients. And as such, that plan is really an advisor tool.
But financial planning, and financial advice (the client facing output of that planning) is different. Financial advice is designed to align the client’s resources (money, time, energy, creativity) to what truly matters to that client. For example, if what a client wants to achieve in life is financial independence, the advisor spends time with the client defining what financial independence means to that client, uses the financial plan to analyze the necessary behaviors to achieve that independence and then advises the client as to what needs to be done to achieve it.
Here is where the Monte Carlo can be limiting tool if used incorrectly. Let’s assume the advisor runs that analysis and calculates that the client’s current actions create a 95% probability of achieving the client’s independence goals. If “insuring success” is the advisor value proposition, the planning is complete. The advisor would tell the client to continue with his or her current behaviors. But if the advisor’s value proposition is to allow the client to define and build the biggest life that the client’s resources allow, then the advisor would share with the client that a 95 Monte Carlo score truly allows the client to dream bigger, buy more goals and make more impact.
It then becomes the adviser’s role to “walk beside the client” on a regular basis to make sure that the client makes the financial decisions to make that greater impact.
One critical aspect that Monte Carlo simulations overlook is the emotional dimension of financial planning. Humans are generally not adept at emotional self-reflection, which is crucial for defining values and setting realistic goals. A skilled advisor should therefore not only guide clients toward a clearer understanding of their values but should also encourage the evolution of these benchmarks.
Monte Carlo simulations typically do not consider the timing of expenditures relative to market conditions, something a well-advised client would naturally do. For instance, they might choose to liquidate investments when markets are strong, or cut back on discretionary spending when markets are weak. In both scenarios, the Monte Carlo score becomes less informative.
While a Monte Carlo score offers vital information and removes fear, it also needs to be viewed as a means to an end. It should be folded into a financial strategy that accounts for evolving goals, market timing, and most importantly, the nuances of human emotion and aspiration.
The number itself is not the goal … and higher is not always better.
Joe Maier is Senior Vice President and Director of Wealth Strategy, Johnson Financial Group.
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