Modelling dynamic lapse with survival analysis and machine learning in CPI

DOI10.1007/S10203-020-00285-9zbMath1470.91219OpenAlexW3026280043MaRDI QIDQ2044802

Marco Aleandri, Alessia Eletti

Publication date: 10 August 2021

Published in: Decisions in Economics and Finance (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10203-020-00285-9

zbMATH Keywords

defaultsurvival analysismachine learningaccelerated failure time modelprepaymentlapserandom survival forestcredit protection insuranceTVOG

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Credit risk (91G40) Actuarial mathematics (91G05)

Related Items (1)

Identifying the determinants of lapse rates in life insurance: an automated Lasso approach

Cites Work

• Not if but when will borrowers default
• An equilibrium characterization of the term structure

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