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This paper presents an Insurance Reserve Intelligence Platform using Physics-Informed and Knowledge-Informed Neural Networks for accurate and efficient term-life insurance reserve prediction, achieving high accuracy and 119.53 times faster inference than classical solvers.
This paper investigates scaling laws in actuarial ratemaking models using tabular data, finding that TabM exhibits stronger data scaling than standard Transformer and MLP architectures without additional inductive biases.