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20212026
most citedRobust estimation and model diagnostic of insurance loss data: a weighted likelihood approach

1 citations · 2 across the 8 of their papers we have counts for

collaborators

9 papers

econ.GN2026

Quantifying Social Inflation in Liability Insurance with Advanced Statistical Methods

Tsz Chai Fung, Lie Ma, Liang Peng +1

Social inflation, which is the rise in liability claim costs beyond general economic inflation, has become a major concern for insurers and reinsurers, yet it is difficult to quant…

stat.AP2025

Statistical Learning of Trade Credit Insurance Network Data with Applications to Ratemaking and Reserving

Woongchae Yoo, Spark C. Tseung, Tsz Chai Fung

Trade credit insurance (TCI) is a specialized line of property and casualty insurance, protecting businesses against financial losses due to buyer's insolvency. Predictive modeling…

stat.AP2024★ 1 cited

A Revisit of the Optimal Excess-of-Loss Contract

Ernest Aboagye, Vali Asimit, Tsz Chai Fung +2

It is well-known that Excess-of-Loss reinsurance has more marketability than Stop-Loss reinsurance, though Stop-Loss reinsurance is the most prominent setting discussed in the opti…

stat.ME2023

Diagnostic Tests Before Modeling Longitudinal Actuarial Data

Yinhuan Li, Tsz Chai Fung, Liang Peng +1

In non-life insurance, it is essential to understand the serial dynamics and dependence structure of the longitudinal insurance data before using them. Existing actuarial literatur…

stat.AP2022

A Posteriori Risk Classification and Ratemaking with Random Effects in the Mixture-of-Experts Model

Spark C. Tseung, Ian Weng Chan, Tsz Chai Fung +2

A well-designed framework for risk classification and ratemaking in automobile insurance is key to insurers' profitability and risk management, while also ensuring that policyholde…

math.ST2022

Mixture of experts models for multilevel data: modelling framework and approximation theory

Tsz Chai Fung, Spark C. Tseung

Multilevel data are prevalent in many real-world applications. However, it remains an open research problem to identify and justify a class of models that flexibly capture a wide r…