A framework for the evaluation of InsurTech

• DOI: http://doi.org/10.1111/rmir.12161
• Date: 01 December 2020
• Published date: 01 December 2020
• Author: Peter Zweifel,Xian Xu

Risk Manag Insur Rev. 2020;23:305–329. wileyonlinelibrary.com/journal/rmir

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305

Received: 5 June 2019

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Revised: 22 November 2020

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Accepted: 1 December 2020

DOI: 10.1111/rmir.12161

FEATURE ARTICLE

A framework for the evaluation of InsurTech

Xian Xu

1

|Peter Zweifel

2

1

Department of Insurance and Risk

Management, Fudan University, Shanghai,

China

2

Department of Economics, University of

Zurich, Zurich, Switzerland

Correspondence

Xian Xu, Department of Insurance and Risk

Management, Fudan University, 600

Guoquan Road, 200433 Shanghai, China.

Email: xianxu@fudan.edu.cn

Funding information

British Academy, Grant/Award Number:

NAFR2180130; British Academy Newton

Advanced Fellowship

Abstract

In recent years, the insurance industry has known

rapid development and application of new technolo-

gies, leading to the emergence of a large number of

innovative products. This constitutes a challenge for

stakeholders ranging from consumers, management,

investors, and on to regulators, who need to evaluate

these so‐called InsurTech innovations. This study

applies a modified Delphi method in combination

with the Analytical Hierarchy Process of Saaty to first

provide the weightings of 42 individual indicators for

aggregation to 9 subdimensions, among which degree

of innovation, size of potential user base, and delivery

of services turn out to be the most important. These

subdimensions are in turn aggregated into three main

dimensions, (i) management and operations, (ii) level

of technology, and (iii) user experience, which are

found to have equal weight. In conclusion, this paper

proposes a transparent way of evaluating InsurTech

innovations that also may provide guidance for their

future development.

JEL CLASSIFICATION

G22; O32; O33; G10

1|INTRODUCTION

With the rapid development of technologies such as artificial intelligence, cloud computing, and

big data in recent years, the financial industry has been challenged to adopt so‐called Fintech

innovation. Fintech includes mobile payments, loans and financing, wealth management, retail

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© 2020 The American Risk and Insurance Association

banking, and transaction settlement. In the insurance industry, InsurTech started with fast and

convenient price comparison platforms but has spread to other areas, such as insurance

marketing and underwriting, health management, and fast claims settlement. While the

development of science and technology has been a shock to the financial industry in general,

its long‐run impact will likely be most strongly felt in the insurance industry as InsurTech

(World Economic Forum, 2015).

Indeed, InsurTech has affected the entire value chain of insurance, from product design,

underwriting, actuarial activities, claims assessment and settlement, asset management, and on

to capital investment. Types of innovation include peer‐to‐peer insurance selling, usage‐based

insurance where pricing reflects mileage and driving behavior with the support of the Internet

of vehicles, automated customer service often combined with artificial intelligence, cloud‐based

customer policy management, and automated loss adjustment using image‐recognition tech-

nology. Thus, InsurTech can take on the form of new insurance products (e.g., usage‐based

insurance), new tools to provide services (e.g., robo‐advisors), management instruments (IBM

Watson, Ant Claims Adjuster), and even a complete business model. While InsurTech is

designed to improve the efficiency of the industry, its rapid development has also given rise to

several issues. First, its quality varies greatly between insurance companies, reflecting ample or

insufficient investment in innovation, respectively. Second, a number of InsurTech products are

largely identical. For example, the robo‐advisors launched all put almost exclusive emphasis on

risks to be covered and premium calculation. Thus, the degree of innovativeness and differ-

entiation of products could be improved. Third, there are many free riders acting under the

banner of InsurTech who are not innovating at all. Many of the business models that self‐

advertise as InsurTech are limited to Internet insurance sales or platforms for offering mutual

aid in the event of loss. Finally, some of them merely amount to the application of standard

existing technologies, without the potential for future development. For example, the use of

artificial intelligence is often limited to simple knowledge mapping rather than applications

of neural networks and deep learning. These weaknesses of InsurTech make it difficult for

relevant stakeholders such as consumers, insurance managers, investors, and regulators to

evaluate the overall strength of InsurTech innovation, resulting in an impediment to its future

development. For instance, regulators designing a supportive policy to impel the development

of InsurTech usually need an evaluation framework to identify competitive InsurTech start‐ups.

So do the investor, who have interest in seeking out promising InsurTech start‐ups and

the consumers who prefer a powerful provider for high‐quality InsurTech service such as

customizing insurance products. Overall, effective evaluation of insurance technology compa-

nies will ultimately help accelerate the survival of the fittest and promote the development of

the InsurTech industry. However, there does not seem to exist research offering a general

quantified framework for this evaluation.

Against this backdrop, this study seeks to develop a comprehensive, transparent, and

consistent framework for evaluating InsurTech innovation by identifying and weighting its

principal dimensions. In a first round, an open‐ended questionnaire of the modified Delphi

method is used to identify 42 relevant indicators covering the three main dimensions of

InsurTech products, viz. (i) management and operations, (ii) level of technology, and (iii) user

experience. In a second round, participating experts are asked to rate these indicators in

terms of their importance. These ratings provide the input to the analytic hierarchy process

(Saaty, 1986), which yields weights that permit to aggregate the indicators to nine subdimen-

sions and from there, to the three main dimensions distinguished above reflecting both the

current status and the direction of future development of global InsurTech innovation.

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