The Gamification Of Monte Carlo: How To Incentivize Proactive (Not Reactive) Retirement Spending Goals

The Gamification Of Monte Carlo: How To Incentivize Proactive (Not Reactive) Retirement Spending Goals

In recent years, Monte Carlo simulation has become a popular tool for financial advisors to motivate their clients to follow recommendations. By presenting a single probability-of-success percentage, Monte Carlo analyses give clients a simple, instantaneous metric on the state of their financial plan. And because many clients naturally like to challenge themselves to do better and score higher, they are incentivized to take action that will increase their plan’s probability of success. The idea of using the same fun and appealing motivating elements found in games that people like to play (e.g., accomplishment, empowerment, and unpredictability) to encourage them to take action on other aspects of their lives is a concept known as “gamification”.

Yet, as many advisors know, the end goal of financial planning is not necessarily to achieve the highest possible Monte Carlo probability-of-success result, as a 100% Monte Carlo success rate effectively guarantees that the client will have excess money left over at the end of their lives (likely more than they would need to have at the end of their plan, and otherwise could have spent and enjoyed earlier in their life). Which means that, while Monte Carlo incentivizes clients to achieve higher and higher probabilities of success, actually working to achieve the ‘best’ success probability of 100% may push clients toward outcomes that are out of line with their goals for spending, giving, and leaving behind assets during their lifetimes.

Fortunately, several ways exist for advisors to use the gamification power of Monte Carlo simulation to motivate clients to follow their recommendations. First, advisors can reframe how outcomes are measured by shifting the focus from an acceptable probability of success to a more dynamic concept of probability of adjustment, to emphasize the fact that ever-higher probabilities of success do not necessarily equate to desirable outcomes for the client and that lower probabilities of success can actually be more sustainable than they may sound, when factoring in a client’s ability and willingness to make spending adjustments along the way.

Alternatively, advisors and their clients could pre-define a range of acceptable probabilities (in other words, implement a risk-based guardrail strategy) which allows the probability of success to float up or down with market movements over time, and specifies the point at which the client would need to cut spending if the probability drops too low (or conversely, increase spending if the probability increases above the target range), which serves to help the client understand the long-term ongoing nature of their plan, and that the plan shouldn’t be considered as a one-time blueprint for all future spending up to (and beyond) retirement. Going further, advisors using a guardrails-based approach could even consider shifting the focus away from probability of success entirely, and toward more concrete metrics such as actual dollar figures (e.g., to reflect spending, portfolio balances, etc.) since, to the client, what ultimately matters is not their plan’s probability of success itself, but instead, the actions (e.g., the level of spending) that allow them to achieve that probability of success!

Ultimately, what makes Monte Carlo simulation so powerful for clients is the ability to visualize how they can impact their plan’s long-term outcome through the actions they take. However, without first defining the range of probabilities – and whether they serve as metrics for success or adjustment – that will best achieve the client’s goals, the instinct will be to pursue ever-higher probabilities of success (and correspondingly more conservative plans). Advisors can help harness the gamification power of Monte Carlo in a way that is better aligned with the client’s goals by framing the range of desirable outcomes and reorienting the conversation away from probability of success and toward the client’s concrete actions.

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