RIMS-HDR Certificate Program in Quantitative Enterprise Risk Management

Course Info

Measure What Actually Matters in Enterprise Risk Management

The RIMS-HDR Certificate Program in Quantitative ERM is a three-week, interactive professional development experience delivered in partnership with Hubbard Decision Research (HDR). Most ERM programs run on heat maps, ordinal rating scales, and weighted scoring indices. They feel precise—but decades of research show they often add noise rather than insight, and can lead organizations to worse decisions than simpler methods would.

This program teaches the alternative. Across three live sessions, guided self-study, and group discussion, participants learn to build calibrated, data-informed risk models; apply Bayesian and statistical methods to real risk scenarios; and communicate quantitative results to leadership in terms that drive action. Participants will gain hands-on knowledge directly from Doug Hubbard—creator of Applied Information Economics and author of How to Measure Anything and The Failure of Risk Management—and the HDR faculty team.

The program is designed for risk professionals at every level, including experienced practitioners who are ready to move their ERM program beyond scoring rubrics. It is also a strong complement for RIMS-CRMP holders looking to add quantitative depth to their existing risk management practice.

Program Highlights:

Duration: 3-week program
Interactive Learning: Participate in live virtual sessions with the HDR faculty, group discussion, and structured self-study.
Expert Instruction: Learn directly from Doug Hubbard and the HDR team during three 4-hour virtual sessions, totaling 12 hours of live instruction.
Core Curriculum: Based on The Failure of Risk Management: Why It's Broken and How to Fix It, 2nd Edition, by Doug Hubbard (Wiley, 2020), purchased separately.
Asynchronous Calibration Training: Self-paced Calibrated Probability Assessment training, completed alongside Module 1.

October 8–22, 2026

10:00 AM – 12:00 PM EDT

MEMBER$2,250

NON-MEMBER$2,500

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Session Dates:

Thursday, October 8
Thursday, October 15
Thursday, October 22

Sessions will be recorded and shared for those who are unable to attend.

Modules

Module 1: How to Measure Anything in Risk Management, Quantitative Methods, and Calibration

Module 2: Defining Risks and Incorporating Them into the Risk Model

Module 3: Improving the Initial Risk Model and Communicating Results

Who Should Attend?

This program has been developed for risk professionals at all levels—including ERM practitioners, risk analysts, risk managers, and senior risk leaders—who want to move their risk assessment practice from subjective scoring to quantitative measurement. RIMS-CRMP holders looking to add quantitative depth to their credential will find this program highly complementary. No advanced statistics background is required.

RIMS education courses are designed primarily for risk and insurance professionals, but anyone within an organization who wants to learn more about a specific topic of interest is encouraged to attend.

Your Instructors

Douglas (Doug) Hubbard is the founder of Hubbard Decision Research (HDR) and creator of Applied Information Economics (AIE), a methodology for measuring intangibles and quantifying uncertainty in complex business decisions. He is the bestselling author of How to Measure Anything and The Failure of Risk Management, the core text for this program, along with several other influential books on risk, measurement, and decision analysis.

For more than 30 years, Hubbard has helped organizations across financial services, cybersecurity, healthcare, government, insurance, and technology improve decision-making through quantitative risk analysis. His books have sold more than 190,000 copies in eight languages, and his work has been recognized by leading research firms including Gartner and Forrester. He is widely regarded as a leading authority on measurement, risk, and evidence-based decision-making.

Andrew Adams is Chief Executive Officer of Hubbard Decision Research (HDR) and an experienced data scientist specializing in statistics, quantitative decision analysis, and Applied Information Economics (AIE). He has worked with organizations across insurance, healthcare, pharmaceuticals, cybersecurity, and consulting services to improve decision-making under uncertainty.

Andrew has developed dozens of customized Monte Carlo simulation models that combine organizational data, industry research, calibrated estimates, and Bayesian methods to support complex business decisions. Prior to HDR, he worked with IBM and the BC Centre for Excellence in HIV/AIDS, applying machine learning and predictive modeling to healthcare challenges. He holds a Bachelor of Commerce from McGill University and a Master of Science in Applied Mathematics from Simon Fraser University.

Peter Mallik is Chief Operating Officer (COO) and Director of Cognitive Research at Hubbard Decision Research (HDR), where he applies cognitive science, quantitative analysis, and decision research to help organizations improve risk assessment and decision-making. Prior to his current role, he served as a Senior Quantitative Analyst at HDR, advising clients on complex valuation and measurement challenges.

Peter earned his Ph.D. in Psychology from The University of Akron, specializing in adult development, aging, and cognitive science. His research focused on understanding the sources of noise and bias that influence human judgment and decision-making. He is an active member of several professional organizations and has published research in leading journals, including Nature Human Behaviour, Experimental Aging Research, The Journal of Cognitive Psychology, and The Journal of Cognitive Enhancement.