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Scaling Laws, Tabular Data and Actuarial Ratemaking Models

This story is from 2026-09-04. It is preserved in the archive; the latest stories are on the live feed.

arXiv:2609.03106v1 Announce Type: new Abstract: Scaling laws in modern deep learning describe how held-out loss improves as model capacity, training data, and compute increase, often following power-law trends. We investigate whether analogous scaling regularities arise in actuarial ratemaking, whe…

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  1. 2026-09-04 04:00 · arXiv cs.LG
    Scaling Laws, Tabular Data and Actuarial Ratemaking Models

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