Date: 20 June 2022

Book Description

Like the companion book Loss Data Analytics, this book on life contingencies will be an interactive, online, freely available text.

  • The online version will contain many interactive objects (quizzes, computer demonstrations, interactive graphs, video, and the like) to promote deeper learning. A subset of the book will be available for offline reading in pdf and EPUB formats.
  • Will focus on data and statistical aspects of life contingent events.
  • Will emphasize cash flow fundamentals, an approach that allows users to easily adapt approaches to handle complex products.
  • This modular approach emphasizing data and cash flow fundamentals has additional advantages:
    • computational aspects become practically relevant through spreadsheet (e.g., Microsoft Excel) and numerical (R) examples, and
    • an emphasis on the foundations provides an easy entry point for learners who wish an introduction to the field.

How will the text be used?

This book will be useful in actuarial curricula worldwide. Our primary target audience is second or third year undergraduates with little to no experience in insurance. Learners may be international; although the book will be in English, we do not expect knowledge of native idiosyncrasies that might be used in the classroom. It will cover the learning objectives of the major actuarial organizations. Thus, it will be suitable for classroom use at universities as well as for use by independent learners seeking to pass professional actuarial examinations.

A secondary audience is the actuarial practitioner (perhaps international) who wishes to retool and learn about modern approaches in the risk management of life contingent events. Thus, the text will also be useful for the continuing professional development of actuaries and other professionals in insurance and related financial risk management industries.

Why is this good for the profession?

An online text is a type of open educational resource (OER). One important benefit of an OER is that it equalizes access to knowledge, thus permitting a broader community to learn about the actuarial profession. Moreover, it has the capacity to engage viewers through active learning that deepens the learning process, producing analysts more capable of solid actuarial work.

Why is this good for students and teachers and others involved in the learning process? Cost is often cited as an important factor for students and teachers in textbook selection (see a recent post on the $400 textbook). Students will also appreciate the ability to “carry the book around” on their mobile devices.

Life Contingent Calculations

Life contingences is a quantitative discipline, enjoying the rigor and discipline of mathematics. Like any mathematical discipline, one traditionally learns about it through the development of formulaic expressions, that is, their proofs, special cases, analysis of special features, and so on. Users of this text find that we do not shy away from presenting summaries of main conclusions using formulaic expressions. Nonetheless, rather than developing insights from mathematical proofs of the primary findings, we demonstrate their impact through short illustrative examples and links to practical applications.

As with other sources that introduce life contingencies, we utilize spreadsheets extensively. In our teaching, we find that spreadsheets are useful for communication and dynamically visualizing results as they evolve over time. However, unlike other sources, we supplement this with approaches that emphasize programming; in this text, we use R. Programming methods such as through R (and Python, another good candidate) easily accommodate more complex situations that require more computing and, moreover, are built to graphically portray results in an attractive fashion. Analytics, the process of using data to make decisions, is enjoying tremendous attention from many industries; this is certainly true of in data-driven fields that use life contingent methods. By working with data and using programming methods such as R in the study of life contingences, users see the connections within many fields that support the actuarial science discpline. Instruction may emphasize any one of the three approaches, traditional mathematical development, spreadsheets, or a computing approach. However, this text contains all three as we believe that future generations of actuaries need to be familiar with all of these different ways to analyze, and communicate, problems that can be solved using life contingent methods.

Project Goal

The project goal is to have the actuarial community author our textbooks in a collaborative fashion. To get involved, please visit our Open Actuarial Textbooks Project Site.


We acknowledge the Society of Actuaries for permission to use problems from their examinations.

We thank Rob Hyndman, Monash University, for allowing us to use his excellent style files to produce the online version of the book.

We thank Yihui Xie and his colleagues at Rstudio for the R bookdown package that allows us to produce this book.

We also wish to acknowledge the support and sponsorship of the International Association of Black Actuaries in our joint efforts to provide actuarial educational content to all.


The project goal is to have the actuarial community author our textbooks in a collaborative fashion. The following contributors have taken a leadership role in developing Life Contingencies.

  • Vali Asimit
  • Dani Bauer
  • Adam Butt
  • Edward (Jed) Frees
  • Emiliano Valdez
  • Andrés Villegas

For our Readers

Like any book, we have a set of notations and conventions. It will probably save you time if you regularly visit our Appendix Chapter 9 to get used to ours.

Freely available, interactive textbooks represent a new venture in actuarial education and we need your input. Although a lot of effort has gone into the development, we expect hiccoughs. Please let your instructor know about opportunities for improvement, write us through our project site, or contact chapter contributors directly with suggested improvements.