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PreprintCC BY 4.0arXiv

Text Data Analysis and Classification Methods - Insights from Customer Letters in Life Insurance

  • Andreas Groll
  • Marie Punsmann
  • Leonid Zeldin
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Abstract

The business of life insurance companies is characterized by long-term contracts. For this reason, data describing customers is of immense value. A portion of the data provided to the customer is rarely or not at all analyzed. This includes customer letters of any kind. This work focuses on classifying customer letters as cancellations and identifying the respective reason, if available. The outlined approach can also be applied to other business transactions and reasons. We discuss data acquisition and preparation, present alternatives, and explain the reasons for the chosen approach. A successful implementation of such a tool can lead to a better understanding of customer cancellation behavior by the insurer, enabling more targeted actions in certain situations.

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Cite

BibTeXRIS
BibTeX
@misc{groll2026text,
  title = {{Text Data Analysis and Classification Methods - Insights from Customer Letters in Life Insurance}},
  author = {Andreas Groll and Marie Punsmann and Leonid Zeldin},
  howpublished = {arXiv},
  year = {2026},
  month = aug,
  doi = {10.48550/arxiv.2608.29699},
  eprint = {2608.29699},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2608.29699},
  note = {CC BY 4.0},
}
RIS
TY  - UNPB
TI  - Text Data Analysis and Classification Methods - Insights from Customer Letters in Life Insurance
AU  - Andreas Groll
AU  - Marie Punsmann
AU  - Leonid Zeldin
PY  - 2026
DA  - 2026/08/30
PB  - arXiv
DO  - 10.48550/arxiv.2608.29699
UR  - https://arxiv.org/abs/2608.29699
AB  - The business of life insurance companies is characterized by long-term contracts. For this reason, data describing customers is of immense value. A portion of the data provided to the customer is rarely or not at all analyzed. This includes customer letters of any kind. This work focuses on classifying customer letters as cancellations and identifying the respective reason, if available. The outlined approach can also be applied to other business transactions and reasons. We discuss data acquisition and preparation, present alternatives, and explain the reasons for the chosen approach. A successful implementation of such a tool can lead to a better understanding of customer cancellation behavior by the insurer, enabling more targeted actions in certain situations.
ER  -