Associate Professor Fei Huang

Associate Professor Fei Huang

Associate Professor
  • Senior Fellow of Advance HE (SFHEA)
  • PhD, Australian National University
  • MPhil, University of Hong Kong
  • BSc, Xiamen University
Business School
School of Risk and Actuarial Studies

Fei Huang is an Associate Professor in the School of Risk and Actuarial Studies, UNSW Business School. 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 July 2020, she was a senior lecturer at the Australian National University. Fei is a columnist writing the Responsible Data Science series for Actuaries Digital - Actuaries Institute Magazine. She has received numerous awards for research and educational excellence, recognising her contributions to actuarial science, data science, and responsible AI.

Fei’s research focuses on responsible AI and data-driven decision-making, with particular emphasis on insurance, risk management, and actuarial applications. She draws on tools from statistics, machine learning, economics, and marketing to design solutions that are not only accurate and interpretable, but also fair, stable, and privacy-preserving. A central aim of her work is to ensure that insurance and superannuation (retirement income products) remain equitable, affordable, and sustainable in the face of advancing AI and a changing climate. Her recent research spans three key areas:

  • Responsible AI and Fair Insurance Pricing: advancing understanding and quantitative adoption of key responsible AI principles, especially in the insurance and superannuation industries, including accuracy, fairness, interpretability, uncertainty quantification, privacy, and stability, to ensure trustworthy and ethical data-driven decision making. This research is funded by an ARC Discovery Project "Responsible Statistical Learning: Uncertainty, Fairness and Transparency". Her research on antidiscrimination insurance pricing has received several prestigious awards from both academia and professional bodies, including the Australian Business Deans Council (ABDC) Award for Innovation and Excellence in Research (Emerging and Applied) and the North American Actuarial Journal Best Paper Award
  • Climate disaster insurance: tackling challenges related to affordability, sustainability, and fairness in climate disaster insurance policy and design. This research is funded by an ARC Discovery Project "Dealing with Climate disasters" (2025-2028).
  • Mortality and retirement income: examining socio-economic mortality differentials and their implications for retirement income and annuity systems. She led the development of the interactive dashboard, Australian Longevity Explorer and open-access Australian Socio-Economic Longevity Dataverse to help Australians, industry, and government better understand longevity patterns, using linked individual-level national datasets.

Her work has been published in leading actuarial journals and received several prestigious research awards, including the North American Actuarial Journal Best Paper Award, National Industry PhD Program Award, ABDC Innovation and Excellence Award for Research (Emerging Applied Category), Carol Dolan Actuaries Summit Prize, Amecian Academy of Actuaries' Award for Research, 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), the Society of Actuaries, and Milliman.

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. Her educational excellence has been recognised 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 collaborates with insurers, consulting firms, and government agencies on transformative research and education projects, encompassing a diverse 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.

  • Journal articles | 2025
    Xin X; Hooker G; Huang F, 2025, 'Pitfalls in machine learning interpretability: Manipulating partial dependence plots to hide discrimination', Insurance Mathematics and Economics, 125, pp. 103135 - 103135, http://dx.doi.org/10.1016/j.insmatheco.2025.103135
    Journal articles | 2025
    Zhu F; Dong Y; Huang F, 2025, 'Data-rich Economic Forecasting for Actuarial Applications', Insurance, Mathematics & Economics, 124, http://dx.doi.org/10.1016/j.insmatheco.2025.103126
    Journal articles | 2024
    Aas K; Charpentier A; Huang F; Richman R, 2024, 'Insurance analytics: Prediction, explainability, and fairness', Annals of Actuarial Science, 18, pp. 535 - 539, http://dx.doi.org/10.1017/S1748499524000289
    Journal articles | 2024
    Fahrenwaldt M; Furrer C; Hiabu ME; Huang F; Jørgensen FH; Lindholm M; Loftus J; Steffensen M; Tsanakas A, 2024, 'Fairness: plurality, causality, and insurability', European Actuarial Journal, 14, pp. 317 - 328, http://dx.doi.org/10.1007/s13385-024-00387-3
    Journal articles | 2024
    Xin X; Huang F, 2024, 'Anti-discrimination Insurance Pricing: Regulations, Fairness Criteria, and Models', North American Actuarial Journal, 28, pp. 285 - 319, http://dx.doi.org/10.1080/10920277.2023.2190528
    Journal articles | 2023
    Zhang X; Huang F; Hui FKC; Haberman S, 2023, 'Cause-of-death mortality forecasting using adaptive penalized tensor decompositions', Insurance Mathematics and Economics, 111, pp. 193 - 213, http://dx.doi.org/10.1016/j.insmatheco.2023.05.003
    Journal articles | 2022
    Dong Y; Frees EW; Huang F; Hui FKC, 2022, 'Multi-state modelling of customer churn', ASTIN Bulletin, 52, pp. 735 - 764, http://dx.doi.org/10.1017/asb.2022.18
    Journal articles | 2021
    Dolman C; Frees E; Huang F, 2021, 'Multidisciplinary collaboration on discrimination - Not just Nice to Have', Annals of Actuarial Science, 15, pp. 485 - 487, http://dx.doi.org/10.1017/S174849952100021X
    Journal articles | 2021
    Frees EWJ; Huang F, 2021, 'The Discriminating (Pricing) Actuary', North American Actuarial Journal, http://dx.doi.org/10.1080/10920277.2021.1951296
    Journal articles | 2021
    He L; Huang F; Shi J; Yang Y, 2021, 'Mortality forecasting using factor models: Time-varying or time-invariant factor loadings?', Insurance Mathematics and Economics, 98, pp. 14 - 34, http://dx.doi.org/10.1016/j.insmatheco.2021.01.006
    Journal articles | 2020
    Dong Y; Huang F; Yu H; Haberman S, 2020, 'Multi-population mortality forecasting using tensor decomposition', Scandinavian Actuarial Journal, 2020, pp. 754 - 775, http://dx.doi.org/10.1080/03461238.2020.1740314
    Journal articles | 2020
    Huang F; Maller R; Ning X, 2020, 'Modelling life tables with advanced ages: An extreme value theory approach', Insurance Mathematics and Economics, 93, pp. 95 - 115, http://dx.doi.org/10.1016/j.insmatheco.2020.04.004
    Journal articles | 2020
    Ma J; Huang F; Bruhn A, 2020, 'Estimating China’s Future Life Insurance Market', Asia-Pacific Journal of Risk and Insurance, 15, http://dx.doi.org/10.1515/apjri-2019-0027
    Journal articles | 2018
    Ferreira A; Huang F, 2018, 'Is human life limited or unlimited? (A discussion of the paper by Holger Rootzén and Dmitrii Zholud)', Extremes, 21, pp. 373 - 382, http://dx.doi.org/10.1007/s10687-018-0318-8
    Journal articles | 2018
    Huang F; Yu H, 2018, 'Optimal reinsurance: A reinsurer's perspective', Annals of Actuarial Science, 12, pp. 147 - 184, http://dx.doi.org/10.1017/S1748499517000161
    Journal articles | 2016
    Huang F; Browne B, 2016, 'Mortality forecasting using a modified Continuous Mortality Investigation Mortality Projections Model for China I: Methodology and country-level results', Annals of Actuarial Science, 11, pp. 20 - 45, http://dx.doi.org/10.1017/S1748499516000142
    Journal articles | 2016
    Huang F, 2016, 'Mortality forecasting using a modified CMI Mortality Projections Model for China II: Cities, towns and counties', Annals of Actuarial Science, 11, pp. 46 - 66, http://dx.doi.org/10.1017/S174849951600018X
    Journal articles | 2014
    Huang F; Butt A; Ho KY, 2014, 'Stochastic economic models for actuarial use: An example from China', Annals of Actuarial Science, 8, pp. 374 - 403, http://dx.doi.org/10.1017/S1748499514000104
  • Working Papers | 2025
    Dong Y; Frees EJ; Huang F; Hui F; Van Heerde H, 2025, A Joint Model of Cost and Churn for Stochastic Cost Industries, SSRN, http://dx.doi.org, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5259489
    Working Papers | 2025
    Huang F; Hui F; Villegas Ramirez A, 2025, Towards Fairer Retirement Outcomes: Socio-Economic Mortality Differentials in Australia, http://dx.doi.org10.2139/ssrn.5253598, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5253598
    Working Papers | 2025
    Huang F; Pesenti SM, 2025, Marginal Fairness: Fair Decision-Making under Risk Measures, SSRN, http://dx.doi.org, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5266857
    Working Papers | 2025
    Huang F; Shen J; Yang Y; Zhao R, 2025, Learning Fair Decisions with Factor Models: Applications to Annuity Pricing, http://dx.doi.org, https://arxiv.org/abs/2412.04663
    Working Papers | 2025
    Park C; Williams M-A; Zhan S; Laub P; Huang F, 2025, ClassChat: Can AI help us collaborate and discuss better?, http://dx.doi.org
    Working Papers | 2025
    Shimao H; Huang F; Warut Khern-am-nuai W, 2025, Welfare Implications of Fairness Regulations in Insurance Cost Modeling: A Multi-Method Study, SSRN, http://dx.doi.org, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5112616
    Working Papers | 2025
    Zhu F; Dong Y; Huang F, 2025, Data-Rich Economic Forecasting for Actuarial Applications, http://dx.doi.org, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4756743
    Working Papers | 2024
    Xin X; Hooker G; Huang F, 2024, Why You Should Not Trust Interpretations in Machine Learning: Adversarial Attacks on Partial Dependence Plots, http://dx.doi.org, https://arxiv.org/abs/2404.18702
    Working Papers | 2022
    Huang F; Maller R; Milholland B; Ning X, 2022, A Proposal for Finite But Unbounded Human Lifetimes, http://dx.doi.org10.1101/2022.01.07.474862
    Working Papers | 2021
    He L; Huang F; Yang Y, 2021, Data-adaptive Dimension Reduction for US Mortality Forecasting, http://dx.doi.org, https://arxiv.org/abs/2102.04123
    Working Papers | 2021
    Huang F; Maller R; Miholland B; Ning X, 2021, A Mixture Model Incorporating Individual Heterogeneity in Human Lifetimes, http://dx.doi.org10.1101/2021.01.29.428902, https://www.biorxiv.org/content/10.1101/2021.01.29.428902v1
    Working Papers |
    Dong Y; Frees EJW; Huang F, Deductible Costs for Bundled Insurance Contracts, Elsevier BV, http://dx.doi.org10.2139/ssrn.4020299, https://doi.org/10.2139/ssrn.4020299
    Working Papers |
    Frees EJW; Huang F, Online Supplement to: The Discriminating (Pricing) Actuary, Elsevier BV, http://dx.doi.org10.2139/ssrn.3892473, https://doi.org/10.2139/ssrn.3892473
    Working Papers |
    Shimao H; Huang F, Welfare Implications of Fairness and Accountability for Insurance Pricing, Elsevier BV, http://dx.doi.org10.2139/ssrn.4225159, https://doi.org/10.2139/ssrn.4225159
    Working Papers |
    Xin X; Huang F, Anti-Discrimination Insurance Pricing: Regulations, Fairness Criteria, and Models, Elsevier BV, http://dx.doi.org10.2139/ssrn.3850420, https://doi.org/10.2139/ssrn.3850420
  • Conference Presentations | 2022
    Huang F, 2022, 'Anti-Discrimination Insurance Pricing: Regulations, Fairness Criteria, and Models', presented at ASTIN Colloquium, 22 June 2022
    Conference Presentations | 2022
    Huang F, 2022, 'Anti-discrimination Insurance Pricing: Regulations, Fairness Criteria, and Models', presented at All-Actuaries Summit, 03 May 2022
    Conference Presentations | 2022
    Huang F, 2022, 'Cause-of-death Mortality Modelling using Penalized Tensor Decomposition', presented at 24th International Congress on Insurance: Mathematics and Economics, 04 July 2022
    Conference Presentations | 2021
    Huang F, 2021, 'The Discriminating (Pricing) Actuary', presented at 11th China International Conference on Insurance and Risk Management, 11 July 2021
    Preprints | 2020
    Frees E; Huang F, 2020, The Discriminating (Pricing) Actuary, http://dx.doi.org/10.2139/ssrn.3592475
    Conference Presentations | 2020
    Huang F, 2020, 'Modelling Life Tables with Advanced Ages: an Extreme Value Theory Approach', presented at 28th Colloquium on Pensions and Retirement Research, 29 November 2020
    Conference Presentations | 2020
    Huang F, 2020, 'Modelling Life Tables with Advanced Ages: an Extreme Value Theory Approach', presented at Actuarial Research Conference, 29 July 2020
    Conference Presentations | 2020
    Huang F, 2020, 'The Discriminating (Pricing) Actuary', presented at CLMR Research Symposium 2020, 20 November 2020
    Conference Presentations | 2019
    Huang F, 2019, 'Modelling Life Tables with Advanced Ages: an Extreme Value Theory Approach', presented at International Workshop on Subnational Life Tables, 20 November 2019
    Conference Presentations | 2019
    Huang F, 2019, 'Multi-population Mortality Forecasting using Tensor Decomposition', presented at China International Conference on Insurance and Risk Management (CCIRM), 30 July 2019
    Conference Presentations | 2018
    Huang F; Ferreria A, 2018, 'Is there a limit to Human Life or Not?', presented at Actuarial Risk Modelling and Extreme Values (ARMEV) Workshop, 18 September 2018
    Conference Presentations | 2018
    Huang F, 2018, 'The Younger-Older Dichotomy of Mortality Patterns: Observations and Applications', presented at 22th International Congress on Insurance: Mathematics and Economics, 09 July 2018
    Preprints |
    Fu B; Huang F; Maller R, Modelling Australian Life Tables with Advanced Ages -- A Report Prepared for the Australian Government Actuary, http://dx.doi.org/10.2139/ssrn.4020309
    Preprints |
    Zhang X; Huang F; Hui F; Haberman S, Cause-of-Death Mortality Forecasting Using Adaptive Penalized Tensor Decompositions, http://dx.doi.org/10.2139/ssrn.3943888

  1. Australian Research Council (ARC) Discovery Project, (with Yanrong Yang, Samuel Muller), 2026-2028, $636,574, "Responsible Statistical Learning: Uncertainty, Fairness and Transparency".
  2. Australian Research Council (ARC) Discovery Project,  (with Jeremy Moss), 2025-2027, $439,488, "Dealing with Climate Disasters"
  3. National Industry PhD Program Award, Industry Researcher PhD category (for Laura Zhao), 2024-2032, $232,000 (max from government to support the project). "Personalised Risk Management for Australian Travellers utilizing Causal and Generative AI Model".
  4. Fairness Metrics for Life Insurance (with Milliman), SOA Research Grant, 2023, US$30,000, "Fairness Metrics for Life Insurance" 
  5. CAS Individual Grant Competition, collaborated with Joshua Loftus (LSE), US$17,554, "Interpretable and Fair Insurance Risk Pricing using Causal Models".

  1. Climate Disaster Insurance - ARC Discovery Project (2025-2028) Dealing with Climate Disasters with Jeremy Moss
  2. Responsible AI -- Fairness and Discrimination in insurance pricing
    (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, ASTIN Colloquium Best Paper Award, American Academy of Actuaries' Academy Award for Research, and North American Actuarial Journal 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 versionarXiv version)
  3. Responsible AI -- Transparency and Interpretability
    (1) Pitfalls in machine learning interpretability: Manipulating partial dependence plots to hide discrimination. (with Xi Xin and Giles Hooker) (arXiv version)
  4. Mortality and Retirement Income -- Socio-economic Longevity Differentials
    (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 )
  5. Mortality and Retirement Income -- 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
  6. 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 Interactive App 

Australian Longevity Explorer: Understanding Australian Socio-Economic Longevity and its Retirement Income Implications

Recent Invited Industry Talks:

  1. Young Actuaries Conference, Actuaries Institute, 2025
  2. Navigating The Future: Understanding AI Risk & Opportunities From An Actuarial Perspective, Institute and Faculty of Actuaries (IFoA), 2025
  3. Understanding Bias in Actuarial Data-driven Decision Making, Society of Actuaries, 2025 (close to 700 attendees)
  4. Model Risk Management and Ethical AI Adoption, International Actuarial Association, 2025

 

Media Coverage:

  1. Actuaries Digital, 2025, When Students Become Startups
  2. Business Think, 2025, How socio-economic factors drive significant life expectancy gaps
  3. The Actuary Magazine (IFoA), 2025, Check your AI: a framework for its use in actuarial practice
  4. Actuaries Digital, Responsible Data Science column, 2025, The Price of Loyalty: Rethinking Optimisation in Insurance Pricing
  5. Actuaries Digital, Responsible Data Science column, 2025, Achieving Fairness in Data-driven Decision Making
  6. Featured in a special print magazine edition of BusinessThink to celebrate UNSW Sydney’s 75th anniversary, 2024
  7. Forbes Advisor, 2024, How Much Is Home And Contents Insurance In Australia?
  8. Business Think. 2024, Beyond black box AI: Pitfalls in machine learning interpretability.
  9. Info360, 2024, This is why your insurance premiums keep going up. (republished by 75 news medias, and ‘audience reach’ of about 500,624. )
  10. RESOLVE, December 2023, AI discrimination potential explored, by  Resolve Editor Kate Tilley, Australian Insurance Law Association (AILA)
  11. Business Think, 2023. If you get a genetic test, could a life insurance firm use it against you?  
  12. Business Think, 2023. Home insurance is on the rise. Is there an affordable solution? 
  13. ANZIIF article 2023: How to manage bias in insurance data and algorithms.  
  14. Actuaries Digital 2023: The 2023 Volunteer of the Year Winners Announced!
  15. Business Think and UNSW Newsroom , 2022, Pricing fairness: tackling big data and COVID-19 insurance discrimination.
  16.  IMD and Business Think, 2022. How insurers can mitigate the discrimination risks posed by AI.
  17. Actuaries Digital 2022, How confident are you that your insurance pricing or underwriting models are not discriminatory? 
  18. Huang, F., Liu, K. and Yu, J., 2022. UNSW data analytics Sandbox empowers young actuaries to help solve industry problems, Actuaries Digital
  19. Value Driven Data Science Podcast 2022, Episode 3: Fairness and Anti-Discrimination in Machine Learning
  20. SBS Radio Interview (in Chinese) 2021 on Insurance Discrimination, Link

 

 

My Research Supervision

  • Yuan Zhuang (primary supervisor), PhD student at UNSW Sydney
  • 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 Teaching

  1. ACTL4305/5305 Actuarial Data Science Applications (2020 - now)
    Datathon project (2024): Competing for Pet Insurance Customers: A Pricing Competition. Industry Partners: Fetch, Airtree, Finity. Event video; Media Coverage (When Students Becomes Starts, Actuaries Digital)
    Sandbox project (2023): Understanding Bushfire Event Risk Across Australia. Industry Partner: Suncorp. Event Video
    Sandbox project (2022): Multi-coverage Claim Modelling for Insurance Packaged Products. Industry Partner: IAG. Event Video
    Sandbox project (2021): Develop Pricing Models for SME Building Insurnace with Features Having High Cardinality. Industry Partner: Suncorp. Media Coverage
  2. 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