2024, Vol. 7, Issue 1

All over the world, there are constant questions around the best way to ensure that elderly citizens enjoy their later years with significant Retirement Funds, not marred by the downturns of the economy.

The United States stands at a demographic and fiscal crossroads, characterized by an aging population, rising healthcare expenditures and increasing pressure on public and private retirement systems.

Within this challenging context, a pressing problem emerges: millions of Americans are projected to face significant financial insecurity in their retirement years, threatening both individual well-being and broader economic stability. Let’s paint what the future potentially looks like: retirement systems are unable to support millions of Americans in their retirement, which means a fall in purchasing power, which in turn triggers an economic crisis. Of course the US Government could begin sending out Stimulus packages to these individuals but it wouldn't work for too long and would be too expensive.

This impending crisis exposes a significant issue in prevailing retirement planning frameworks, which predominantly rely on static, deterministic models. These models, often based on linear projections and historical assumption, fail to capture the dynamic, non-linear and highly uncertain nature of a retiree’s financial journey, which is subject to market volatility, health shocks, longevity risk and evolving economic policies. Take the current US economic climate, with Tariffs and the subsequent surge in food prices, the economy is evidently harder than it may have been six months ago or two years ago.

The problem? The US retirement systems don't take any of these external factors into account in its planning, which in turn leaves the Retirees at the mercy of brutal economic downturns.

The problem can be traced to the nature of retirement planning models which are static, not predictive or dynamic. These systems do not evolve in response to external circumstances affecting the economy.

This study proposes a paradigm shift by leveraging the power of AI and predictive analysis to develop a dynamic, probabilistic model for individual retirement preparedness and financial resilience.

By integrating diverse datasets including: market performance, health statistics, macroeconomic indicators, and personal financial record, machine learning algorithms can generate personalized, forward-looking assessments of retirement outcomes under a diverse set of future states.