Brandon Flicker (GradCertActSt, MActSt), President and CEO,
Note : Since prospective clients who read this brochure are unlikely to recognize the term "actuarialist," ™ I offer the following definitional and biographical notes to enhance transparency and to establish my bona fides.
What, then, is an actuarialist ™? In layman's terms, using the same stochastic and other statistical models as an actual actuary, an actuarialist offers consultations to private parties which provide accurate data relevant to specific plans and dreams, including, where relevant, data for life expectancy. The actuarialist thereby facilitates realistic estimates of clients' chances of bringing said plans and dreams to fruition, with or without considerations of mortality.
In 2002, after a nine-year stint in the insurance "game," which followed immediately upon graduation from college, nine years which constituted my entire, unique opportunity to experience, for better or worse, the state of being a twenty-something ... I had had it! Nine years of brain-frying study through a series of eleven grueling examinations which together brought me to maximum rank and salary in what has been rated the first or second-most desirable profession (ha!) in this, our great nation. Nine years of significantly bloating the bottom line of a major conglomerate (the name-brand recognition of which I will not now enhance by either identification or excoriation) which specializes in annuities and in property and casualty insurance. Nine years of stochastically calibrating rates for policies ranging from property and liability for a large, modern, wooden vacation structure with concrete-block foundation and no cellar, eight-hundred yards from the ocean in an environment of moderate-to-high hurricane activity; to a term annuity with survivors' rights for a fifty-something who is currently fit and practicing a healthy lifestyle, but who smoked cigarettes (an average of 1.7 packs per day, filtered) from age sixteen until he suffered a minor infarction at forty-one, and whose family tree features on both primary branches rates of smoking-related lung cancer and coronary disease which are of statistically significant elevation. In short, to repeat, I had had it!
Note: In order to provide prospective clients with some sense of the parameters of what an actuarialist can and cannot do, I offer four examples of consultations performed for previous clients (2.1-2.4) and one (2.5) which was designed, but not carried out.
Before proceeding to these examples, however, I must issue the following three disclaimers, the first two adapted in paraphrase from the Exposure Draft of October 15, 1999, International Actuarial Association, and the third, a caveat suggested by counsel as standard practice:
—Principle 3.5. Avoidance of Failure: For most risk-management estimates with specified success criteria, there is a set of parameters such that a combination of values of the probabilistic criteria reduces the failure probability, as estimated by a valid actuarial model, to below a specified positive level.
—Principle 3.6. Degree of Actuarial Soundness: For most risk-management estimates, there is a set of parameters such that a combination of values produces a degree of actuarial soundness, as estimated by a valid actuarial model, that exceeds a specified level less than one.
—Caveat: The examples which follow are intended solely to illustrate prior practice, and are not intended for use in any way, shape or form in the creation of plans or dreams by readers of this prospectus. In light of Principles 3.5 and 3.6 supra, any reader who attempts to use directly, or to extrapolate from, said examples, does so at his or her own risk. In that event, Actuarialist Life Solutions, Inc.™ shall incur no legal liability whatsoever. In other words, don't try these in your own home or office!
Example 2.1. A 62-year old, six-foot tall, physically fit, diet-and-exercise-conscious, highly successful, black male advertising executive in excellent health, aside from very mild age-related scoliosis and a history of hypertension and diabetes on the maternal branch, asked whether the Norfolk pine in his living room, currently 5'10" high and just sprouting its newest layer, will outgrow him.
client's life expectancy (factored for likelihood of continued good health and for median life expectancy for African-American males age 62, 84.4): 85.39
mean growth rate of Norfolk pines: one layer every 1.17 years
mean height of each layer of this particular tree: four inches (4")*
* Strictly speaking, this number, 4", refers to the height of the section of the tree's stem between all produced, but not necessarily remaining, layers, since lower layers tend to fall off, especially in unhealthy trees, such as those which have been traumatized by events like ceiling collapse.
actuarialistic assessment of likelihood of pine outpacing man: barring unforeseen disease of, or accident to, tree, as close to certain as anything in this world can be.
advice to client: Count on it.
comment: In one way, this consultation was anomalous, since the client appeared to seek the information for no purpose other than some obscure mental or emotional satisfaction
Example 2.2. A client in the 98th percentile for wealth, but with no other relevant demographic characteristics, asked me to determine the likelihood that the marriage of his daughter and only child (white, Episcopalian, age 20) to an immigrant from a war-torn African nation on his last year in the U.S. on a student visa (black, Baptist/animist, age ?27) will end in divorce, and, if so, the likelihood that this divorce will occur before or after the couple has produced a child or children.
divorce rate from American wives for all males of this man's nationality (i.e., "tribe") on student visas in U.S: data unavailable
divorce rate from American wives for all males from this man's country on student visas in U.S.: 27% (est. margin of error: 12%)
mean duration of all terminated marriages: 5.6 years (est. margin of error: 12%)
mean time elapsed between marriage and production of (first) child in all terminated marriages: 2.6 years (est. margin of error: 12%)
other relevant data: the client has, himself, been divorced six times; his daughter's mother, twice; 87% of all members of the client's family have been divorced at least once, as have 63% of all members of his daughter's mother's family; in 94% of all divorces on both sides, an average of 2.4 children were produced prior to divorce and, in only 0.73 per cent, no children.
advice to client: The worst-case scenario (divorce after the production of a child or children) seems virtually certain. Deal.
caveat to client: [See Principle 3.6. Degree of Actuarial Soundness (supra)]. On the 0-1 scale, this prediction achieves only 0.347. To approach 0.750, the generally acceptable level of soundness in cases such as these, where the human factors are, alas, somewhat indeterminate, one would have to garner information relevant to at least two further random variables: cultural attitudes toward marriage and divorce within the groom's particular nationality, and divorce rates within both the groom's nuclear and extended families. Although obtaining both sets of information would be possible, the task would require at least two subcontractors: a private investigator within, or with access to, the groom's home country; and an anthropologist (cultural) cognizant of patterns of marriage and divorce within the groom's nationality. After a short deliberation, the client decided not to sign a second contract for these additional services. Quote: "No, that's okay, I get the picture."
Example 2.3. A farmer (truck and dairy) who depends for a significant proportion of his income on an elaborate, well-maintained farm stand which is situated directly beside the road just to the left of his large (3000 cubic-foot) barn asked for a cursory (i.e. inexpensive) study of whether he should repaint the sides and back of the barn as well as the front. It was a given that the barn needed painting. It was also a given that the degree of actuarial soundness he could expect from this study would be commensurate with the cost. In other words, the stochastic model, in this case, would be by no means deterministic.
principal determinant (1): comparison of sales volumes at farm stands proximate to buildings painted, unpainted, and partially painted. The ratio is 1 to .4 to .7 .
principal determinant (2): cost of painting ($1700) and of partially painting ($950)* said barn.
* Given that the farmer has no children or other relatives residing in the area from whom he might extract free or barter labor, and given that both he and his wife "already have our hands full," $1700/$950 were the (sole) estimates for the job, as provided by two young, moderately experienced local men who are reputed to be honest, capable, and in possession of all necessary equipment.
actuarialistic estimate: the most cost-effective solution would be to paint only the front of the barn plus the side visible from the stand (the left side, from the vantage of the road and the entrance to the stand). Fortunately, the other (right) side faces an impenetrable grove of alders. It was also estimated (by intuition) that almost no customers who happen to wander around behind the barn to "sightsee" are likely to be deterred by the unpainted back of the barn from purchasing the produce, dairy products, jams and baked goods for which this farm stand is renowned
advice to client: Get the boys out there before the weather (fair and cool) and the season (late-August) turn.
conclusion: This was one of my favorite consultations. Since the barn was (partially) repainted two years ago,** sales from the stand, rather than declining, have actually increased 1.7% p.a.***
** actually costing, in the event, $936.28, or $13.72 below estimate.
*** Professional standards compel me to point out, however, that unexamined random variables render absurd any assertion of a causal relationship between the paint job and the increase in sales.
Example 2.4. A seventy-one year-old woman (white, in excellent health) asked me to determine whether she will have time to knit a sweater for her unborn grandchild before either she (the grandmother) dies or the world ends.
client's remaining life expectancy: 13.4 years
minimal "life expectancy" for Earth: 46 years.*
* Our best available estimate for the end of the world comes from the emerging science of econophysics, a movement among physicists which models economic systems using techniques and concepts initially developed to analyze the out-of-equilibrium dynamics of complex systems. Econophysicists have recently confirmed Sir Isaac Newton's famous Bible-based estimate that the world will end c.2050. The corroborating estimate is based upon a singular convergence of many long-term demographic, economic and financial series.
client's projected time frame for project: 6-18 months
additional factor significantly impacting actuarialistic assessment of project's coming to fruition: Over the past two years, the client's daughter, 34, and the daughter's live-in "other" (male, 31) have mentioned with increasing frequency their desire to produce a child "soon."
advice to client: Pick a pattern, buy the wool. The "baby" will be in his/her forties by the time the world ends, by which time he/she will have outgrown this and, presumably, many other sweaters.
Example 2.5. A 31 year-old woman wished to discover the likelihood that her neutered eight year-old Tom cat will attack the man who has been her lover for one month, while the man is sleeping. The cat has already inflicted several superficial scratches and one small bite while the man was awake.
No further data available*
* This consultation did not occur. Not that the question was by any means unanswerable, but in order to establish adequate random variables (i.e., to assign numerical values to the likelihood of attacks of various severity and of a non-attack), and subsequently to quantify all probabilistic outcomes (i.e., to assign a number between zero and one to the likelihood of attacks of various severity and of a non-attack), I estimated 20 hours of work at my usual fee of $180 per hour (see Section 3, below), whereupon the client decided not to proceed. In my own defense, let me explain that the random variables for this study would have been complex and subtle: for example, previous behavior by the cat toward prior boyfriends and any others who had been perceived (presumably) as rivals for the client's affection; plus the time frame of attack patterns by cats—to wit, longitudinal data concerning the increase or decrease of jealousy aggression behavior among cats of various ages and sub-species—if such data even exist.
3. Fee Structure (see attached pamphlet)
On a personal note: suffice it to say that, since my private life is virtually synonymous with my professional one, I am now happy. Rashly ignoring any and all projected health factors and all projected local, national, continental, planetary or cosmic disasters, whether induced by humans or so-called acts of God, I expect to remain same (happy) for 44.4 more years* (based upon current life expectancy for 32 year-old white males in the U.S.).
* which, I note—not without a certain ambivalence—would bring me to A.D./C.E. 2048.
Circa 1960, a guy in my dorm mentioned that his career aspiration was to become an actuary. I remember my initial reactions: 1. How nerdy! 2. Wow! big bucks! 3. He must be really good in Math. 4. How funny that they can cost out things like hurricanes and heart attacks. In 2004, it occurred to me that, these days, many people in the rich world "actuarialize" much of their lives: estate and other financial planning, scientific dating and mate selection, wedding planning, micromanaging diet and other health concerns, etc. I see all this as hedging your bets against mortality and mischance. Try googling "actuary" and you'll be amazed: scientific estimates of when the world will end is the least of it.
Actuarial jargon and all data which are real, rather than invented, come from National Vital Statistics Reports for 2000 and from the web sites of several actuarial schools and professional organizations.