AS Lab

• Development of Insurance Pricing Models:
  • Building pricing models for life, non-life, and health insurance.
  • Applying Machine Learning (ML) and AI to enhance insurance pricing.
  • Analyzing economic factors affecting premium rates.
  • Statistics methods for Frequency-Severity model.
• Risk Management and Insurance Finance:
  • Developing loss modeling using Extreme Value Theory (EVT).
  • Applying Value at Risk (VaR) and Conditional Value at Risk (CVaR) in risk control.
  • Evaluating the impact of climate change on catastrophe insurance.
• Big Data and AI Applications in Insurance:
  • Deep fraud detection systems.
  • Developing and evaluating deep learning frameworks for enhanced claim loss prediction
• Pricing Financial Derivatives and Insurance Investments:
  • Developing option pricing models for unit-linked insurance products.
  • Applying Black-Scholes and Monte Carlo simulations in investment portfolio management.
  • Analyzing the effects of financial market volatility on insurance firms.
  • Term Structure Model
• Mathematical, Statistical, and Computational Methods in Insurance:
  • Using Markov models and time series analysis for insurance trend forecasting.
  • Applying Bayesian Statistics in insurance data analysis.
  • Developing optimization algorithms for insurance risk portfolios.
  • Copula and related topics
  • Generative modeling for insurance.
  • Computational methods in probability and statistics

Here, we share a list of leading journals/conferences in the field in which our Lab operates and which are the targets of the Lab's research products. The list is divided into three levels: Tier 1 (the highest level), Tier 2, and Tier 3, based on our assessment of the quality of the journals.

• Scientific research