What are ASTIN Masterclasses?

ASTIN Masterclasses is a series of online masterclasses on a wide range of non-life insurance topics taught by the greatest minds of the actuarial profession and renowned authorities on risk and insurance. They are fully interactive covering topics from such key areas of interest as financial stability and enterprise risk management, regulatory changes, data science and artificial intelligence in insurance, climate change and catastrophe risk, cyber risk, and InsurTech and disruptive technologies.

The Art and Science of Actuarial Loss Reserving — From Then to Now by Greg Taylor

One of the largest items on an insurance company’s balance sheet, often the largest, is the loss reserve, the liability for future claim costs for which the company is already obligated. It isn’t possible to operate a risk business without a thorough understanding of its liabilities. Modern insurance businesses rely on reserve models to:

  • establish bottom-line profit for each accounting period;
  • price new business effectively;
  • report to relevant statutory authorities;
  • understand the risk associated with the estimates of liability; and 
  • manage the capital commitment to the business of its owners.

Loss reserving methodology has evolved over 50 years or so, from models of a strictly heuristic nature in the early years to properly formulated stochastic models more recently, and has evolved further in the very recent past into machine learning models. Loss reserving is often viewed as a necessary evil, divorced from the excitement of the marketplace, and dull in nature. Greg Taylor shows you that the statistical processes underlying it, and the associated modelling challenges, can lead you down stimulating by-ways.

His court-room experience, and other experience involving contesting parties, has taught him a wariness of heuristic methods. Rigorous statistical models, linked as far as possible to real-world processes, provide greater reliability. An overly simple loss reserving model might be perfectly respectable under some circumstances, but fail miserably under others, for example:

  • changing rate of claim pay-out;
  • change in Governing legislation; and/or 
  • varying inflation of claim costs.

In this masterclass, Greg traces the history of actuarial loss reserving and reserve risk management from its crude beginnings to the much more sophisticated present, looking at methodological developments and the reasons for them.  If you wish to understand these developments, and learn of models that address complex reserving situations, then you need to watch this masterclass. Greg offers solid theoretical background, relevant case studies and practical tips for anybody grappling with ways to support reliable analysis of claim data.


  1. Insurance technical reserves: what and why?   (14:21)
  2. Actuarial beginnings   (19:58)
  3. Putting stock in stochastic   (17:33)
  4. But aren’t all forecasts wrong?   (10:51)
  5. Why do your estimates use only half the available data?   (11:17)
  6. So, you've made a whole bunch of forecasts. Now what?   (8:45)
  7. Down and dirty with individual claims   (10:22)
  8. Rise of the machines   (16:42)

About the Lecturer 
Greg Taylor is an Adjunct Professor in the School of Risk and Actuarial Studies at University of New South Wales (Sydney, Australia).  Greg Taylor was a founding director of Taylor Fry Consulting Actuaries, where he acted as a consultant for 15 years. Prior to the foundation of that company in 1999, he worked as an actuary in the finance and insurance industry for 30 years, and a further 8 years as an academic. He is an Officer of the Order of Australia, and recipient of one of the only two Gold Medals ever awarded by the Actuaries Institute of Australia. He also holds the Finlaison Medal (Silver Medal) of the UK Institute and Faculty of Actuaries. He specialises in the theory of Insurance Loss Reserving, and has authored two books, and co-authored a third, on the subject. One has been translated into Japanese. He has lectured and held research positions in many academic and industry institutions in Europe and the North America.

The Insurance-Risk Landscape: An Eclectic Survey by Michael Powers

“The Insurance-Risk Landscape: An Eclectic Survey” is a Masterclass video series written and narrated by Professor Michael R. Powers of Tsinghua University. Through a collection of ten engaging episodes, Professor Powers navigates the metaphorical landscape formed by the many manifestations of insurance risk — from natural and human-made perils to insurance company insolvency. Along the way, he stops to explore some of the most intriguing twists and turns in the landscape, with an ability to make the complex simple, and the simple profound. The eclectic choice of topics includes:

  • the origins of insurance, with relevant insights for today’s markets;
  • the roles of randomness, complexity, and uncertainty in generating losses;
  • rationales for the most commonly used frequency and severity distributions;
  • the interplay between hedging and diversification in risk finance;
  • explanations (and common misconceptions) of insurability and underwriting criteria;
  • the meaning and implications of heavy-tailed losses;
  • the nature of the property-liability underwriting “cycle”;
  • the opposing effects of advancing technologies on insurance markets
  1. The Many Meanings of Risk  (10:31)
  2. Insurance and Human Society (15:04)
  3. The Nature and Origin of Insurance Losses  (23:17)
  4. Bayesian Methods in Insurance  (16:16)
  5. Modelling Insurance Losses – Distributions and Parameters  (19:27)
  6. Modelling Insurance Losses – Distributions Versatility  (19:04)
  7. Financing Insurance Losses  (15:14)
  8. Heavy Tails – Underwriting and Solvency  (16:35)
  9. Heavy Tails – Expected Utility and Risk Measures  (24:12)
  10. Winds and Waves of the Future  (18:07)

About the Lecturer:

Michael R. Powers is Professor of Finance at Tsinghua University’s School of Economics and Management. He also holds a joint appointment as Professor of Economics and Business at Tsinghua’s Schwarzman College. From 2012 to 2015, he served as chair of Tsinghua’s finance department — a unique assignment for a foreign academic in China.

Model Risk Management – The Quest for a Unifying Approach by Andrew Smith

Modern financial businesses rely on thousands of models to support decision-making from pricing and reserving through risk and capital to management bonuses and shareholder decisions. These models sometimes fail. Forecasts prove to be inaccurate, or decisions supported by models may turn out to be unwise.

What can we do about this? We cannot eliminate the possibility that the future turns out differently to a model prediction. However, we can ensure that assurance we give on models is both truthful and statistically meaningful. We can reverse stress-test models by feeding them awkward simulated data until they break down. We can choose between harsh validation tests that reveal model weaknesses, or we can apply powerless validation methods where a green light is a foregone conclusion. We can foster a culture where people who become aware of model shortcomings are heard rather than silenced.

This 8-part ASTIN Masterclass uses a series of examples to highlight quantitative approaches to model risk management, using examples related to underwriting risk, stochastic reserving and the modelling of asset price changes. Andrew offers tips for actuaries pressured into expressing undeserved confidence in risky models, together with tips better to support decision making in the context of uncertainty.

ASTIN Members can access each episode by clicking the links below. Please login to your website account. 

The first two videos are accessible to all. If you are not an ASTIN Member, please consider joining to gain access to this and future Masterclasses!



About the Lecturer:

Andrew Smith is an assistant professor in the School of Mathematics and Statistics at University College Dublin and an Honorary Fellow of the Institute of Actuaries. Before he moved to Ireland in 2017, he gained 30 years of insurance experience, specialising in stochastic modelling, including fifteen years as a partner in a major consulting firm.