Skewed link regression models for imbalanced binary response with applications to life insurance

Understand

For a portfolio of life insurance policies observed for a stated period of time, e.g., one year, mortality is typically a rare event.

• When we examine the outcome of dying or not from such portfolios, we have an imbalanced binary response.
• The popular logistic and probit regression models can be inappropriate for imbalanced binary response as model estimates may be biased, and if not addressed properly, it can lead to serious adverse predictions.
• In this paper, we propose the use of skewed link regression models (Generalized Extreme Value, Weibull, and Fre\`chet link models) as more superior models to handle imbalanced binary response.