Department of Mathematics & Statistics
Actuarial Science at Texas Tech University
Actuarial Science (AS) is an interdisciplinary field combining knowledge and methods from: statistics, mathematics, finance, and economics. The core function of an actuary's job is to assess and quantify financial/economic risk.
AS is increasingly viewed as a desirable career by students in the mathematical sciences. The high starting salaries, which reflect the rigorous and lengthy training demanded of the prospective actuary, are part of the reason for this interest. This training requires one to pass a series of established (society) exams, leading to the two major milestones of: Associateship (at least 5 exams), and Fellowship (several more exams). For life, health, and pension actuaries, exams are given by the Society of Actuaries (SOA). For property and casualty actuaries, the exams are administered by the Casualty Actuarial Society (CAS). Candidates will need to specialize their training early on in their career path, either SOA or CAS.
The purpose of this site is to concisely describe the options available to TTU students in order to prepare for a career in AS. Links to other sites that more fully explain the functions and other details of the profession are provided.
Preparing for a Career in Actuarial Science (U.S.A.)
In order to secure an entry-level position, a candidate is currently expected to have passed at least one of the preliminary exams, as well as have acquired validation through education experience (VEE) credits in 3 areas (required by SOA). The exams are offered at appropriate times (twice each year in the Spring and Fall) and locations (most major cities and college campuses). The VEE credits can be acquired by taking appropriate college courses.
- Preliminary exams (CAS/SOA):
- 1/P (Probability)
- 2/FM (Mathematics of Finance)
- 3F-3L/MFE-MLC (Actuarial Modeling)
- 4/C (Construction and Evaluation of Actuarial Models)
- VEE credits (required by SOA):
- Applied Statistical Methods
- Corporate Finance
CAS exams 1,2, and 4 are the same as SOA exams P, FM, and C, respectively. But CAS exam 3F-3L does not correspond exactly to SOA exam MFE-MLC, so at this point the candidate may already have to choose a specialty, either SOA or CAS.
The Mathematics & Statistics Department now offers a minor in Actuarial Science; these students are advised by Dr. Alex Trindade. The minor requirements can be satisfied by taking any 6 courses from the following list, where boldface courses are required (prerequisites are shown for quick reference):
- MATH: 2356 (prereq=1351 or 1331); 4342 (prereq=2350); 4343 (prereq=4342)
- ECO: 2301 (or AAEC 2305); 2302 (prereq=2301), and 4305 (or AAEC 4302)
- FIN: 3320 (prereq=ACCT 2300-2301, ECO 2301-2302, MATH 2345); 3322 (prereq=3320); 4329 (prereq=3320, 3323)
Notes. ECO 2301 and AAEC 2305 cannot both be counted. Similarly with ECO 4305 and AAEC 4302. The ACCT 2300-2301 prerequisite for FIN 3320 is waived for MATH majors. Keep in mind that any given course cannot simultaneously be counted toward the major and the minor (i.e. there must be no overlap between the major and minor lists of courses).
As an example, a typical MATH major, after picking up all the necessary prerequisites, might satisfy the minor by taking the following (not necessarily in this order): ECO 2301, ECO 2302, MATH 2356, FIN 3320, FIN 3322, MATH 4342.
In order to fit the minor into your graduation plan, note/check carefully the prerequisites for each course, and when these courses are offered. MATH 2356 (Quantitative Theory of Interest) is a new course that will be offered for the first time in Spring 2010. In fact, AS-aspiring students should plan to take all of these courses, since:
- MATH 4342 (and part of 4343) covers the syllabus for Exam 1/P
- MATH 2356 & FIN 4329 cover the syllabus for Exam 2/FM
- FIN 3320 & FIN 3322 satisfy the VEE credit in Corporate Finance
- ECO 2301 & ECO 2302 satisfy the VEE credit in Economics (AAEC 2305 can be substituted for ECO 2301.)
- ECO 4305 satisfies the VEE credit in Applied Statistical Methods (AAEC 4302 can be substituted for ECO 4305)
To officially obtain VEE credit for a given subject, the student may have to apply for it through SOA after taking the courses.
Graduate PreparationFor those that are serious about AS but are not in a hurry to start working, or perhaps have not been able to secure an entry-level position, completing a Masters degree in Statistics is good idea. Here are a few compelling reasons:
- Exams 3 & 4 require the study of advanced topics in
probability, statistical inference, and statistical modeling. These topics, which are too advanced for
undergraduates, include primarily:
- reliability/survival analysis
- mathematical statistics (graduate-level)
- time series and regression analysis (also required for the VEE in applied statistics)
- Bayesian statistics
- stochastic differential equations
- Monte Carlo methods
- stochastic processes
- While studying for the Masters (or soon thereafter), one can finish
taking the rest of the preliminary exams, thereby entering the profession at a
higher level (and commensurately higher salary), than one who has entered with
only 1 or 2 exams. The latter individuals will in any case have to study VERY
hard to make it past the rest of the preliminary exams, a task whose difficulty is
- The difficulty of the material
- The fact that they will be doing it on their own
- The fact that they will concurrently be working
(although some, but not all, companies will give time off for study toward exams)
- In the Scandinavian countries one becomes an actuary by doing the equivalent of a Masters degree in Statistics, with coursework also in financial mathematics, insurance, and economics.
- A doctoral degree (in Statistics) may not be the best use of your time. Beyond exam 4 the material becomes increasingly specialized, and direct job-related experience is required.
For those undergraduates wishing to pursue the Masters option, the Mathematics & Statistics Department offers a 150-hour combined B.A.-M.S. or B.S.-M.S. degree program, as well as a stand alone M.S. in Statistics.