A Conceptual Model for Pricing Health and Life Insurance Using Wearable Technology

• Date: 01 December 2018
• DOI: http://doi.org/10.1111/rmir.12112
• Author: Mark Farrell,Michael McCrea
• Published date: 01 December 2018

Risk Management and Insurance Review

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Risk Management and Insurance Review, 2018, Vol.21, No. 3, 389-411

DOI: 10.1111/rmir.12112

FEATURE ARTICLE

ACONCEPTUAL MODEL FOR PRICING HEALTH AND LIFE

INSURANCE USING WEARABLE TECHNOLOGY

Michael McCrea

Mark Farrell

ABSTRACT

A health risk score was created to investigate the possibility of using data

provided by wearable technology to help predict overall health and mortality,

with the ultimate goal of using this score to enhance the pricing of health

or life insurance. Subjects were categorized into low-, increased-, and high-

risk groups, and after results were adjusted for age and sex, Cox proportional

hazards analysis revealed a high level of significance when predictingmortality.

High-risk subjects were shown to have a hazard ratio of 2.1 relative to those

in the low-risk group, which can be interpreted as an equivalent increase in

age of 7.8 years. Our findings help to demonstrate the predictive capabilities

of potential new rating factors, measured via wearables, that could feasibly be

incorporated into actuarial insurance pricing models. The model also provides

an initial step for insurers to begin to consider the incorporation of continuous

wearable data into current risk models. With this in mind, an emphasis is

placed on the limitations of the study in order to highlight the areas that must

be addressed before incorporating aspects of this model within current pricing

models.

INTRODUCTION

Much like the disruptions seen in the banking industry over the past decade, emerging

technologies are revolutionizing the insurance industry. Traditional insurers are under

pressure to innovate existing business models to retain a competitive edge (Hilton,

2017). Data from CB Insights showed funding to start-ups in the newly coined InsurTech

industry has risen from $140 million in 2011 to $2.7 billion in 2016, and investment in

the sector is expected to continue to grow as new technologies arise (Catlin et al., 2017;

Jubraj et al., 2017).

The primary driver of this change has been the increasingly larger amounts of personal

data available to insurers, which offers the opportunity to predict the risk for each

Michael McCrea and Mark Farrell are in Queen’s Management School, Queens’ University

Belfast, Riddel Hall, 185 Stranmillis Rd, Belfast BT9 5EE, UK; e-mail: mmccrea11@qub.ac.uk,

mark.farrell@qub.ac.uk. The authors would like to thank Anthony Horn, whose invaluable

suggestions contributed significantly to the planning of this research.

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390 RISK MANAGEMENT AND INSURANCE REVIEW

customer and charge them accordingly. Traditionally,in life insurance, underwriting data

come from a questionnaire and a medical examination performed by a registered nurse

or licensed physician, depending on the coverage amount and the age of the customer.

A new potential source of this information is the Internet of Things (IoT), composed of

the network of physical objects that can connect to the Internet and communicate with

one another. Examples of these include mobile phones, pacemakers, onboardcomputers

in cars, and of most interest to this study, wearable technology. This term, often shortened

to just wearables, describes all technology that is worn comfortably on the body or

combined with clothing (Tehraniand Michael, 2014). Common wearables include Fitbit,

Garmin fitness bands, and the Oura ring. By use of the IoT, insurers have the potential

to access huge amounts of real-time data, allowing them to build far more accurate risk

profiles concerning the people they insure. Not only can this allow a more personal and

fairer method of pricing, but through improved engagement with the customer risks

can be both managed and reduced.

The overall research aim of this article is to demonstrate the potential that data derived

from wearable devices may provide to insurance companies in terms of new rating

factors for their pricing models. As such, we develop a conceptual risk model that utilizes

data measurable by wearables, and can classify a policyholders’ relative risk to the rest of

the population. This risk model serves to highlight the potential for insurance companies

to incorporate wearable device data in their own health- and life-insurance-related

pricing models. As this is to be a preliminary model demonstrating potential and acting

as a proof of concept, simplicity will be key in order to retainthe model’s generalizability.

This is the first study that attempts to create a health risk score comprising solely data

that can be collected in a continuous manner by wearable technology.

The rest of the article is outlined as follows. The “Literature Review” section investigates

the current state of the insurance industry with respect to the use of wearable technology,

and then provides a review of medical literature used in the formation of health risk

scores. The “Methodology” section describes the methods used to analyze the data.

The “Statistical Analysis—Results” section comprises the results of the analyses and

the diagnostic tests performed to confirm the validity of the findings. The “Discussion”

section discusses the possible implications of the findings, and follows with an in-depth

investigation into the limitations of the analyses performed. The article is concluded

with suggestions for possible extensions of the study.

LITERATURE REVIEW

Current State of the Insurance Industry

The insurance industry is well aware of the challenges it is likely to face over the coming

years, and so is investing heavily in research and data in order to evolve (Sultan, 2015).

Over 63 percent of insurers expect wearables to effect the industry significantly in the

next 2 years (Schwartz and Hamilton, 2015). A huge advantage of these pieces of tech-

nology is the ability to record and analyze data continuously with minimal interaction.

Already, a number of insurers have begun to incorporate wearables into their products,

trialing new innovative programs in an attempt to get ahead of their competitors and

break into markets of potential customers previously considered uninsurable. A main

area of concern for insurers is the willingness to participate in these kinds of programs.

Opt-in rates can be as low as 5 percent; however, PwC found that if the wearable was