Fraud is a significant issue for insurance companies, generating much interest in machine
learning solutions. Although supervised learning for insurance fraud detection has long …

Over the last decade, digitisation and individualisation have fostered the development of on-
demand services in many industries. In the insurance sector, technological progress brings …

Identifying insurance fraud is a difficult task due to the complex nature of the fraud itself, the
diversity of techniques employed, the rarity of fraud cases observed in data sets, and the …

Fraud is a social phenomenon, and fraudsters often collaborate with other fraudsters, taking
on different roles. The challenge for insurance companies is to implement claim assessment …

Life assurance companies typically possess a wealth of data covering multiple systems and
databases. These data are often used for analyzing the past and for describing the present …

This chapter delves into the digital transformation in the insurance industry, beginning with
the challenges and rewards it presents. It then examines the transformation of the insurance …

In this paper, we examine the role of usage‐based auto insurance on customers' decisions
to change their insurance coverage at the renewal. Using a sample of 135,540 customers …

The ecological governance system has made significant progress in information technology
construction, and digitization has become an important driving force in the construction of …

Using data on 76 Chinese insurance companies from 2011 to 2020, this study investigates
the impact of digital transformation (DT) on total factor productivity (TFP). We use the latent …

Selection markets create a multitasking environment where intermediary agents often need
to increase consumer take-up as well as resolve information asymmetries about consumer …