Yanxin Liu
University of Nebraska
Room: M3 3127
Identifying Long-term Mortality Improvement Rates: A LiDAR Approach
Two-dimensional mortality improvement scales are promulgated by actuarial professional organizations across the world. In such scales, mortality improvements rates are assumed to converge gradually from higher values to lower ultimate values. The success of the two-dimensional projection approach therefore depends crucially on a correct identification of the long-term mortality improvement rates. In this paper, we attempt to identify long-term mortality improvement rates using Light Detection and Ranging (LiDAR), an artificial intelligence technology that has been applied to such areas as autonomous driving for remote sensing purposes. Using canopy height models in LiDAR, we successfully locate “tree tops” in historical mortality improvements, from which we can further extract waves of short-term improvements and deteriorations in the past. After such an extraction, the long-term mortality improvements are systematically identified.