Using artificial intelligence to create value in insurance

Abstract

Purpose

Recent technological and digital developments have opened new avenues for customer data utilization in insurance services. One form of this data transformation is automated chatbots that provide convenient access to data leveraged through a discussion-like interface. The purpose of this paper is to uncover how insurance chatbots support customers’ value creation.

Design/methodology/approach

Three complementary theoretical perspectives – artificial intelligence, service logic, and reverse use of customer data – are briefly discussed and integrated into a conceptual framework. The suggested framework is further shown through illustrative case examples that characterize different ways of supporting customers’ value creation.

Findings

Chatbots represent a new type of interaction through which companies can influence customers’ value creation by providing them with additional resources. Based on the proposed conceptual framework and the illustrative case examples, four metaphors are identified that characterize how insurance chatbots can support customers’ value creation.

Research limitations/implications

The study is conceptual in nature, and the case examples are used for illustrative purposes. No representative data from those users who will eventually determine whether chatbots are of value was used.

Practical implications

Using the suggested framework, which is aligned with provider service logic, insurance companies can consider what kind of a role they wish to play in customers’ value-creating processes.

Originality/value

Automated chatbots provide convenient access to data leveraged through a discussion-like interface. This study is among the earliest to address their value-creating potential in insurance.

Citation

Riikkinen, M., Saarijärvi, H., Sarlin, P. and Lähteenmäki, I. (2018), "Using artificial intelligence to create value in insurance", International Journal of Bank Marketing, Vol. 36 No. 6, pp. 1145-1168. https://doi.org/10.1108/IJBM-01-2017-0015