1. Congratulations!
Congratulations! Well done! Your journey as an actuary working on life insurance in R was a success. You managed to help both the Incredible family as well as Cynthia Rose and her friends with the actuarial questions they were facing in daily life.
2. What you've learned
The course kicked off with a chapter on designing cash flow vectors, and their valuation with discount functions. After studying this chapter, you were already able to help Mr Incredible with the calculations relevant for his car loan.
Then you moved on with life tables and a probabilistic model for human mortality. This chapter taught you the necessary probabilistic tools to calculate survival and death probabilities, and also life expectancies no longer hold any secrets for you!
The valuation principles from chapter 1 and the probabilistic view on mortality from chapter 2 nicely integrated in your work on life insurance products or life contingent risks. First, you worked on life annuities which are relevant for premium payments and retirement plans. A life annuity pays a benefit contingent on the survival of the annuitant. Second, you designed life insurance products where a death benefit is paid upon death of the policyholder.
3. Want to know more?
If you are looking for an in depth discussion of life insurance mathematics, we recommend the classic textbooks of Gerber, Dickson, Hardy and Waters or Promislow. And if you are a student working with one of these books, this DataCamp course offered you a wide range of useful R commands and exercises. See it as a hands-on version of a typical course on life insurance mathematics!
4. What else is there?
Of course, actuaries work on many more challenging topics beyond the content of this course. Follow-up courses on life insurance may put focus on the calculation of policy values or reserves, as well as the design of insurance products on multiple lives, instead of the single life as you studied in this course. The combination of the pure insurance policies examined here with investment strategies is another challenging topic and would require you to dust off your financial mathematics skills.
Beyond life insurance, actuaries study statistical models for the frequency of insured events and their impact or severity, in case such an event happens. Knowledge of a wide range of distributions and regression models then comes in handy. As in many fields, the actuary as a data cruncher, equipped with an extensive toolbox from data science, is a recipe for a bright and inspiring career in the analysis of the financial costs of risk and uncertainty!
5. Enjoy your journey as an actuary!
All the best from here on. Enjoy your journey as an actuary!