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Eliminate Risk and Ensure Success in Exam SRM.


Our Study Manual for SOA Exam SRM offers personalized learning on a schedule that works for you.
The Exam SRM study manual will allow you to:
GOAL: Practice. Predict. Pass.
Reach your target GOAL Score with our proven system.
GOAL offers:


Instructional Videos
Retain more information with our helpful videos that cover the entire syllabus and further explain the most complex topics.
We've got you covered with:
Flashcards
Master key topics and formulas with our flashcards, which are rated by exam importance.


Planner
Weighted by topic importance, our Planner clearly outlines how to study for Exam SRM
Topic Search
Everything in the SOA Exam SRM study manual is fully indexed by keyword, making it easy to toggle between materials and concepts without losing your place.


Formula and Review Sheet
This at-a-glance tool helps you memorize and recall key formulas and information.
ACTEX Learning Bootcamp Sitting Information:
|
Exam SRM Sitting |
Session 1 |
Session 2 |
Session 3 |
|
May 2026 |
5/2 |
5/9 |
5/16 |
|
September 2026 |
8/8 |
8/15 |
8/22 |
Sessions will begin at 10 am ET. Sessions last two hours, with an additional 30 minutes for questions at the end.
Optimize your Study Time for Exam SRM with the ACTEX Bootcamps.
It is the perfect addition to your study schedule and will help you feel confident and ready for your exam.
Interact with the instructor and other students during this three-session online instruction course offering:
About Your Professors
Dr. Jiayue Zhang, who holds a PhD in Statistics from the University of Waterloo, focuses on assessing climate change impacts and associated risks, with applications in finance and insurance. In July 2024, she earned the Associate of the Society of Actuaries (ASA) designation. Dr. Zhang is set to begin her career as a quantitative strategist at Morgan Stanley, leveraging her expertise in statistical modeling and risk analysis to address challenges in the financial industry.
Dr. Yuanyuan Zhang holds a PhD in Actuarial Science from the University of Waterloo and is an Associate of the Society of Actuaries (ASA). A recipient of the prestigious James C. Hickman Scholarship (awarded to only six globally by the SOA), Dr. Zhang brings expertise in actuarial modeling, advanced analytics, and AI-driven solutions. Currently, he serves as a data scientist at an insurance AI consulting firm, leveraging his technical skills and deep industry knowledge to drive innovation and deliver impactful insights.
About the Authors
Runhuan Feng, PhD, FSA, CERA
Runhuan Feng is a professor and the Director of Actuarial Science Program at the University of Illinois at Urbana–Champaign. He obtained his PhD in Actuarial Science from the University of Waterloo, Canada. He is a Helen Corley Petit Professorial Scholar and the State Farm Companies Foundation Scholar in Actuarial Science. Prior to joining Illinois, he held a tenure-track position at the University of Wisconsin-Milwaukee. Runhuan has published extensively on stochastic analytics in risk theory and quantitative risk management. Over the recent years, he has dedicated himself to developing computational methods for managing market innovations in areas of investment combined insurance and retirement planning. He has authored several research monographs including An Introduction to Computational Risk Management of Equity-Linked Insurance.
Daniël Linders, PhD
Daniël Linders is an assistant professor at the University of Illinois at Urbana-Champaign. At the University of Leuven, Belgium, he obtained an M.S. degree in Mathematics, an Advanced M.S. degree in Actuarial Science and a PhD in Business Economics. Before joining the University of Illinois, he was a postdoctoral researcher at the University of Amsterdam, The Netherlands and the Technical University in Munich, Germany. He is a member of the Belgian Institute of Actuaries and has the Certificate in Quantitative Finance from the CQF Institute. Daniël Linders has wide teaching experience. He taught various courses on Predictive Analytics, Life Contingencies, Pension Financing and Risk Measurement.
Ambrose Lo, PhD, FSA, CERA
Ambrose Lo is the author of several study manuals for professional actuarial examinations and an Adjunct Associate Professor at the Department of Statistics and Actuarial Science, the University of Hong Kong (HKU). He earned his BSc in Actuarial Science (first class honors) and PhD in Actuarial Science from HKU in 2010 and 2014, respectively, and attained his Fellowship of the Society of Actuaries (FSA) in 2013. He joined the Department of Statistics and Actuarial Science, the University of Iowa (UI) as Assistant Professor of Actuarial Science in August 2014, and was promoted to Associate Professor with tenure in July 2019. His research interests lie in dependence structures, quantitative risk management as well as optimal (re)insurance. His research papers have been published in top-tier actuarial journals, such as ASTIN Bulletin: The Journal of the International Actuarial Association, Insurance: Mathematics and Economics, and Scandinavian Actuarial Journal. He left the UI and returned to Hong Kong in July 2023. Besides dedicating himself to actuarial research, Ambrose attaches equal (if not more!) importance to teaching and education, through which he nurtures the next generation of actuaries and serves the actuarial profession. He has taught courses on a wide range of actuarial science topics, such as financial derivatives, mathematics of finance, life contingencies, and statistics for risk modeling.
He is also the (co)author of the ACTEX Study Manuals for Exams ATPA, MAS-I, MAS-II, PA, and SRM, a Study Manual for Exam FAM, and the textbook Derivative Pricing: A Problem-Based Primer (2018) published by Chapman & Hall/CRC Press. Although helping students pass actuarial exams is an important goal of his teaching, inculcating students with a thorough understanding of the subject and logical reasoning is always his top priority. In recognition of his outstanding teaching, Ambrose has received a number of awards and honors ever since he was a graduate student, including the 2012 Excellent Teaching Assistant Award from the Faculty of Science, HKU, public recognition in the Daily Iowan as a faculty member “making a positive difference in students’ lives during their time at UI” for nine years in a row (2016 to 2024), and the 2019-2020 Collegiate Teaching Award from the UI College of Liberal Arts and Sciences.