An integrated method based on hesitant fuzzy theory and RFM model to insurance customers’ segmentation and lifetime value determination

Abstract

The analysis of lifetime value of property insurance company customers can not only help the company to allocate customer relationship management resources reasonably, save the management cost, but also help the company to identify risk timely and effectively, so that the risk control and management can be implemented. In this paper, based on RFM model, adding claim index of evaluating clients’ risk is to evaluate the lifetime value of property insurance customers quantitatively. At the same time, in view of massive uncertainties in practical decision-making, with hesitant fuzzy theory, the attributes will be weighted by hesitant fuzzy entropy. Secondly, the similarity measure theory based on hesitant fuzzy set is used to do cluster analysis and four customer homogeneous groups are obtained. Finally, calculate the lifetime value score of these four groups based on a quantitative method and analyze their characteristics from the quantitative perspective.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 13 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.