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LSTM-Based Detection of Structural Breaks in Property Insurance Loss Reserving: A Climate-Informed Approach

arXiv cs.LG · 2026-06-11 Cached

This white paper proposes using LSTM neural networks to detect structural breaks in property insurance loss reserving caused by climate-driven catastrophes, aiming to improve accuracy by 15–20% over traditional methods like Chain Ladder.

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