Retirement planning in a financial context refers to process of making financial provision for retirement prior to reaching retirement age. This normally results in the purposeful setting aside of money or other assets with the intention of deriving an income from those assets at retirement into old age. The ultimate method of retirement planning doesn't necessarily result in the use a retirement plan as alternative methods of investing may be more appropriate.
The goal of retirement planning (if defined) may be to achieve financial independence, so that the need to be gainfully employed is optional rather than a necessity. Retirement planning is a part of financial planning addressing one purpose. The process of retirement planning aims to: (1) assess a client's readiness-to-retire given a desired retirement age and lifestyle,i.e. do they have sufficient money to afford to retire; and (2) to identify client decisions or actions to improve readiness-to-retire.
Retirement finances touch upon a motley of distinct subject areas or financial domains of client importance, including: investments (i.e. stocks, bonds, mutual funds); real estate; debt; taxes; cash flow (income and expense) analysis; insurance; defined benefits (e.g. social security, traditional pensions). From an analytic perspective, each domain can be formally characterized and modeled using a different class (computer science) representation, as defined by a domain's unique set of attributes and behaviors. Domain models require definition only at a level of abstraction necessary for decision analysis. Since planning is about the future, domains need to extend beyond current state description and address uncertainty, volatility, change dynamics (i.e. constancy or determinism is not assumed). Together, these factors raise significant challenges to any current producer claim of model predictability or certainty. Some might even adopt fatalism -- that the full scope of client issues, non-financial included, render the entire problem indeterminate, unsolvable, and meaningless.
Nonetheless, efforts continue for those interested in control of their own destiny. The Monte Carlo method is a perhaps the most common form of a mathematical model that is applied to predict long-term investment behavior for a client's retirement planning. Its use helps to identify adequacy of client's investment to attain retirement readiness and to clarify strategic choices and actions. Yet, the investment domain is only financial domain and therefore is incomplete. Depending on client context and despite popular press, the investment domain may have very little importance in relation to a client's other domains - e.g. a client who is predisposed to the use of real estate as primary source of retirement funding.
Contemporary retirement planning models have yet to be validated in the sense that the models purport to project a future that has yet to manifest itself. The criticism with contemporary models are some of the same levied against Neoclassical economics. The critic argues that contemporary models may only have proven validity retrospectively, whereas it is the indeterminate future that needs solution. A more moderate school believes that retirement planning methods must further evolve by adopting a more robust and integrated set of tools from the field of complexity science.