Bias, guess and expert judgement in actuarial work. 18 January 2016
Sessional research meeting, 18 January 2016. Paper by the Getting Better Judgement Working Party.
Download the paper: https://www.actuaries.org.uk/documents/bias-guess-and-expert-judgement-actuarial-work
Abstract:
Expert judgement is frequently used within general insurance. It tends to be a method of last resort and used where data is sparse, non-existent or non-applicable to the problem under consideration. Whilst such judgements can significantly influence the end results, their quality is highly variable. The use of the term 'expert judgement' itself can lend a generous impression of credibility to what may be a little more than a guess. Despite the increased emphasis placed on the importance of robust expert judgements in regulation, actuarial research to date has focused on the more technical or data driven methods, with less emphasis on how to use and incorporate softer information or how best to elicit judgements from others in a way that reduces cognitive biases.
This paper highlights the research that the Getting Better Judgement Working Party has conducted into this area. Specifically it covers the variable quality of expert judgement, both within and outside the regulatory context, and presents methods that may be applied to improve its formation. The aim of this paper is to arm the insurance practitioner with tools to distinguish between low quality and high quality judgements and improve the robustness of judgements accordingly, particularly for highly material circumstances.
Keywords:
Expert judgement; Elicitation; Cognitive biases; Heuristics; Bayesian statistics
Видео Bias, guess and expert judgement in actuarial work. 18 January 2016 канала Institute and Faculty of Actuaries
Download the paper: https://www.actuaries.org.uk/documents/bias-guess-and-expert-judgement-actuarial-work
Abstract:
Expert judgement is frequently used within general insurance. It tends to be a method of last resort and used where data is sparse, non-existent or non-applicable to the problem under consideration. Whilst such judgements can significantly influence the end results, their quality is highly variable. The use of the term 'expert judgement' itself can lend a generous impression of credibility to what may be a little more than a guess. Despite the increased emphasis placed on the importance of robust expert judgements in regulation, actuarial research to date has focused on the more technical or data driven methods, with less emphasis on how to use and incorporate softer information or how best to elicit judgements from others in a way that reduces cognitive biases.
This paper highlights the research that the Getting Better Judgement Working Party has conducted into this area. Specifically it covers the variable quality of expert judgement, both within and outside the regulatory context, and presents methods that may be applied to improve its formation. The aim of this paper is to arm the insurance practitioner with tools to distinguish between low quality and high quality judgements and improve the robustness of judgements accordingly, particularly for highly material circumstances.
Keywords:
Expert judgement; Elicitation; Cognitive biases; Heuristics; Bayesian statistics
Видео Bias, guess and expert judgement in actuarial work. 18 January 2016 канала Institute and Faculty of Actuaries
Показать
Комментарии отсутствуют
Информация о видео
6 июля 2016 г. 20:33:49
01:28:59
Другие видео канала
![Quality Assurance Scheme: How (and why) to apply for the IFoA Quality Assurance Scheme](https://i.ytimg.com/vi/6NcCO5pN8cU/default.jpg)
![CERA - Chartered Enterprise Risk Actuary qualification, May 2011](https://i.ytimg.com/vi/AHXKGxl4v7g/default.jpg)
![Philip Scott introduces the proposed new membership category of Certified Actuarial Analyst](https://i.ytimg.com/vi/c7r-tlaVXc8/default.jpg)
![IFoA Alternative Economic Thinking Series - The invisible infrastructure of climate change](https://i.ytimg.com/vi/hMPogEBAxx8/default.jpg)
![ARC 2018 Webinar Series 17th Sept AM webinar](https://i.ytimg.com/vi/Gq6w8Zkdp1Q/default.jpg)
![Careers insight: Meet IFoA Fellow Matt Saker](https://i.ytimg.com/vi/73nqJ09HJiM/default.jpg)
![Actuaries Code Consultation Meeting](https://i.ytimg.com/vi/xocayrNOjkI/default.jpg)
![IFoA Sustainability Series: Climate Justice and Future Generations](https://i.ytimg.com/vi/OstEE-ODRu0/default.jpg)
![Nico Aspinall](https://i.ytimg.com/vi/y5pb3MDKbMs/default.jpg)
![Multi-population stochastic mortality models - Torsten Kleinow](https://i.ytimg.com/vi/87uiyVeSUs8/default.jpg)
![Faith Ward](https://i.ytimg.com/vi/rG9GtFLHtDw/default.jpg)
![ARC Technical Workshop October 2019 - Beyond Proportional Hazards: Plenary 5](https://i.ytimg.com/vi/X0uGa8yoP7k/default.jpg)
![Spring Lecture 2013. A view from the kennel. Robert Chote, Chairman, OBR1](https://i.ytimg.com/vi/e8qkMEwKOOA/default.jpg)
![Qualification framework member consultation: the proposal](https://i.ytimg.com/vi/0NUIbwVOIgc/default.jpg)
![Minimising Longevity and Investment Risk while Optimising Future Pension Plans - Jens Perch Nielsen](https://i.ytimg.com/vi/BwoFfkH1aTs/default.jpg)
![ARC Webinar Series 2021 - Use of Primary Health Care Records Data in Actuarial Research](https://i.ytimg.com/vi/YHTLMI8uyGA/default.jpg)
![Presence will bring you trust! Alan Donegan speaking at the 2012 Life Conference](https://i.ytimg.com/vi/YxLtUuKUQxs/default.jpg)
![Extreme events working party. Difficult risks and capital models](https://i.ytimg.com/vi/FISUNfWx7qY/default.jpg)
![How do you become an actuary?](https://i.ytimg.com/vi/1wCRkM4Pcv8/default.jpg)
![Possible unintended consequences of Basel III and Solvency II. 25 March 2013](https://i.ytimg.com/vi/Kvc7ffeCrnc/default.jpg)