My Expertise
Ethical Insurance Pricing, Insurance Data Science
Keywords
Fields of Research (FoR)
Insurance studies, Investment and risk management, Statistical data science, Marketing Management (incl. Strategy and Customer Relations), Business EthicsSEO tags
Biography
Fei is an Associate Professor in the School of Risk and Actuaries Studies and Lead - Data and AI Tech at UNSW Business AI Lab. She received her BSc. in Mathematics from Xiamen University, MPhil in Actuarial Science from the University of Hong Kong, and PhD in Actuarial Studies from the Australian National University. Before joining UNSW in 2020, she was a senior lecturer at the Australian National University. Fei is a columnist writing...view more
Fei is an Associate Professor in the School of Risk and Actuaries Studies and Lead - Data and AI Tech at UNSW Business AI Lab. She received her BSc. in Mathematics from Xiamen University, MPhil in Actuarial Science from the University of Hong Kong, and PhD in Actuarial Studies from the Australian National University. Before joining UNSW in 2020, she was a senior lecturer at the Australian National University. Fei is a columnist writing Responsible Data Science series for Actuaries Digital - Actuaries Institute Magazine.
In her research, Fei focuses on responsible AI and data-driven decision-making, especially for the insurance industry, utilizing tools from statistics, machine learning, economics, and marketing. Her research interests include fair and non-discriminatory insurance pricing, algorithmic bias, interpretable machine learning, mortality modelling, and customer relationship management. She particularly explores ways to make insurance equitable, affordable, and sustainable in the contexts of AI and climate change. Her work has been published in leading actuarial journals and received many prestigious research awards, including the National Industry PhD Program Award, ABDC Innovation and Excellence Award for Research (Emerging Applied Category), Carol Dolan Actuaries Summit Prize, the ASTIN Colloquium Best Paper Award, the Actuaries Institute's Volunteer of the Year Award in the Spirit of Volunteering category, and the UNSW Business School SDG Research Impact Award. Her research has been funded by multiple international and domestic institutions, including the Australian Research Council (Discovery Project: Dealing with Climate Disasters), Society of Actuaries, Milliman, and Casualty Actuarial Society.
Fei teaches actuarial data science and statistical machine learning at UNSW. By collaborating with industry partners, she incorporates contemporary industry challenges into the course syllabus to offer a unique industry-engaging experience for students via Sandbox Projects. Her educational excellence has been recognized by winning the UNSW John Prescott Award for Outstanding Teaching Innovation (2022), the ANU Vice Chancellor’s Award for Teaching Excellence in the Early Career Category (2018) and the ANU College of Business and Economics Award for Teaching Excellence in the Early Career Category (2017). Fei is a Senior Fellow of Advance HE (SFHEA).
Fei works with insurers, consulting firms, and government agencies for transformative research and education projects, covering a wide range of topics. Examples of such collaborations include mortality modelling, fairness metrics for life insurance, Interpretable and fair insurance pricing using causal models, personalised customer management, bushfire risk modelling, multi-coverage bundled insurance pricing, claims inflation forecasting, and property insurance pricing with high-cardinality features.
My Grants
- Dealing with Climate Disasters (with Jeremy Moss), )Australian Research Council (ARC) Discovery Project, 2025-2027, $439,488
- National Industry PhD Program Award, 2024
- Interpretable and Fair Insurance Risk Pricing using Causal Models (with Joshua Loftus (LSE)), SOA CKER and CAS Individual Grant Competition, 2024
- Fairness Metrics for Life Insurance (with Milliman), SOA Research Grant, 2023
My Qualifications
- Senior Fellow of Advance HE (SFHEA)
- PhD, Australian National University
- MPhil, University of Hong Kong
- BSc, Xiamen University
My Awards
- Australian Business Deans Council (ABDC) Award for Innovation and Excellence in Research (Emerging and Applied), with PhD student Xi Xin as a team member, 2024
- National Industry PhD Program Award, with Zurich Cover-More, Industry PhD candidate Laura Zhao, 2024
- UNSW Business School SDG Research Impact Award, 2023
- Bloomberg Education Excellence Award - Best Innovative Teaching Practice (with Kevin Liu, Xiao Xu, Jonathan Ziveyi, and Sherry Zhang), 2023
- Actuaries Institute's Volunteer of the Year Award - Spirit of Volunteering, 2023
- ASTIN Colloquium Best Paper Award, 2022
- Carol Dolan Actuaries Summit Prize, 2022
- UNSW John Prescott Award for Outstanding Teaching Innovation, 2022
- ANU Vice Chancellor’s Award for Teaching Excellence in the Early Career Category, 2018
- ANU College of Business and Economics Award for Teaching Excellence in the Early Career Category, 2017
My Research Activities
- Dealing with Climate Disasters (funded by ARC Discovery Project 25)
- Fairness and Discrimination: Insurance Discrimination and Pricing Fairness in the Context of AI (and non-AI)
(1) The Discriminating (Pricing) Actuary (with Edward (Jed) Frees), NAAJ, 2023
(2) Anti-discrimination Insurance Pricing: Regulations, Fairness Criteria, and Models (with Xi Xin), NAAJ, 2024 (This paper won the inaugural Carol Dolan Actuaries Summit Prize and ASTIN Colloquium Best Paper Award)
(3) Welfare Implications of Fair and Accountable Insurance Pricing (with Hajime Shimao), 2024 (SSRN version)
(4) Welfare Implications of Fairness Regulations in Insurance Cost Modeling: A Multi-Method Study (with Hajime Shimao and Warut Khern-am-nuai), 2025 (SSRN version)
(5) Learning Fair Decisions with Factor Models: Applications to Annuity Pricing (with Junhao Shen, Yanrong Yang, and Ran Zhao), 2025 (arXiv version)
(6) Marginal Fairness: Fair Decision-Making under Risk Measures (with Silvana M. Pesenti), 2025 (SSRN version / arXiv version) - Transparency and Interpretabilities of AI/Machine Learning
(1) Why You Should Not Trust Interpretations in Machine Learning. (with Xi Xin and Giles Hooker) (arXiv version) - Australian Socio-economic Mortality and Retirement Policy
(1) Towards Fairer Retirement Outcomes: Socio-economic Mortality Differentials in Australia (with Francis Hui and Andres Villegas) (SSRN version / Australian Socio-Economic Mortality Dataverse /Australian Longevity Explorer ) - Advanced-age mortality modelling
(1) Modelling life tables with advanced ages: An extreme value theory approach (with Ross Maller and Ning Xu), Insurance: Mathematics and Economics, 2020 - Customer Churn Analysis and Customer Management
(1) Multi-State Modelling of Customer Churn (with Yumo Dong, Edward (Jed) Frees, Francis Hui), ASTIN Bulletin, 2022 (SSRN version)
(2) A Joint Model of Cost and Churn for Stochastic Cost Industries (with Yumo Dong, Edward (Jed) Frees, Francis Hui, and Harald Van Heerde) (SSRN version)
Software Packages
STLT: STLT fits the Smooth Threshold Life Table (STLT) and Dynamic Smooth Threshold Life Table (DSTLT) as outlined in Modelling life tables with advanced ages: An extreme value theory approach. It also provides S3 methods for predicting using fitted STLT and DSTLT models, as well as plotting the fitted lines.
Open Dataset
Australian Socio-Economic Mortality Dataverse
Online Interative App
My Research Supervision
Supervision keywords
Areas of supervision
- Responsible Data-driven Decision Making
* Insurance discrimination and pricing fairness
* Algorithmic bias mitigation
* Interpretable machine learning
* Mortality modelling - Customer Relationship Management
* Pricing
* Customer Retention
* Customer Lifetime Value
Currently supervising
- Laura Zhao (primary supervisor), part-time PhD student at UNSW Sydney, National Industry PhD Program
- Xi Xin (primary supervisor), PhD student at UNSW Sydney
- Yumo Dong (primary supervisor), PhD student at the Australian National University, graduated.
My Engagement
Media Coverage:
- Actuaries Digital, Responsible Data Science Column, 2025, Achieving Fairness in Data-driven Decision Making
- Featured in a special print magazine edition of BusinessThink to celebrate UNSW Sydney’s 75th anniversary, 2024
- Forbes Advisor, 2024, How Much Is Home And Contents Insurance In Australia?
- Business Think. 2024, Beyond black box AI: Pitfalls in machine learning interpretability.
- Info360, 2024, This is why your insurance premiums keep going up. (republished by 75 news medias, and ‘audience reach’ of about 500,624. )
- RESOLVE, December 2023, AI discrimination potential explored, by Resolve Editor Kate Tilley, Australian Insurance Law Association (AILA)
- Business Think, 2023. If you get a genetic test, could a life insurance firm use it against you?
- Business Think, 2023. Home insurance is on the rise. Is there an affordable solution?
- ANZIIF article 2023: How to manage bias in insurance data and algorithms.
- Actuaries Digital 2023: The 2023 Volunteer of the Year Winners Announced!
- Business Think and UNSW Newsroom , 2022, Pricing fairness: tackling big data and COVID-19 insurance discrimination.
- IMD and Business Think, 2022. How insurers can mitigate the discrimination risks posed by AI.
- Actuaries Digital 2022, How confident are you that your insurance pricing or underwriting models are not discriminatory?
- Huang, F., Liu, K. and Yu, J., 2022. UNSW data analytics Sandbox empowers young actuaries to help solve industry problems, Actuaries Digital
- Value Driven Data Science Podcast 2022, Episode 3: Fairness and Anti-Discrimination in Machine Learning
- SBS Radio Interview (in Chinese) 2021 on Insurance Discrimination, Link
My Teaching
- ACTL4305/5305 Actuarial Data Science Applications (2020 - now)
Sandbox project (2021): Develop Pricing Models for SME Building Insurnace with Features Having High Cardinality. Industry Partner: Suncorp. Media Coverage
Sandbox project (2022): Multi-coverage Claim Modelling for Insurance Packaged Products. Industry Partner: IAG. Event Video
Sandbox project (2023): Understanding Bushfire Event Risk Across Australia. Industry Partner: Suncorp. Event Video
Datathon project (2024): Competing for Pet Insurance Customers: A Pricing Competition. Event video - ACTL3142/5110 Statistical Machine Learning for Risk and Insurance Applications (2021-2022)
Sandbox project (2022): Predicting Claims Inflation for Commercial Auto Insurance Pricing. Industry Partner: IAG. Event Video
Publications
ORCID as entered in ROS
