Digital revolution has been slow to take off in insurance
by Milka Kirova
Ms. Kirova is a Vice President and Senior Economist with Swiss Re’s Economic Research and Consulting unit in North America. In this function, she is responsible for life re/insurance market research and provides regular analysis of macroeconomic and life industry developments and outlook. Visit www.swissre.com.Digitalization and the spread of the internet and mobile technology have impacted a number of industries in recent years, transforming them beyond recognition.
In insurance, there has been gradual acceptance of certain aspects such as digital distribution over the past decade but change, especially in the life sector, has been at the margins only. Customer-centricity is not yet the norm in life insurance: a “one-size-fits-all” approach and a focus on agents rather than consumers is still widespread, limiting consumer choice and product customization.
Moreover, a lengthy and convoluted buying process often leaves consumers confused and lacking trust in insurance providers. Yet consumer preferences and buying behaviors are changing rapidly, not least because many industries have already adopted more customer-centric and technology-inspired business models. Not surprisingly, consumer surveys show insurance lagging behind most other industries when it comes to customer satisfaction from online experiences.
Technological advances have the potential to radically change the way life insurers interact with consumers and also help them better assess and price risks. The rapid spread of internet-enabled wearable devices and ubiquitous connectivity are enabling new ways of communication and information sharing. The amount of digital data generated automatically, inexpensively and non-intrusively is growing exponentially.
So too are new tools to analyze the data and extract useful insights on consumers. Developments in artificial intelligence and cognitive systems also create opportunities for innovation. And advances in medical technology have the potential to improve health outcomes and extend lives, thus changing risk pools.
New technology and data capabilities will make underwriting more efficient
Advances in technology have the potential to radically transform underwriting in life insurance. Lengthy, complex and invasive underwriting processes have long been viewed as an impediment to reaching and engaging with more of the un- and underinsured.
Traditional underwriting techniques to differentiate and select risks are effective, but the process is time consuming and involves high costs. New data sources, platforms to store and analyze data, and fast, innovative technologies to mine the data or simply automate existing processes have the potential to reduce the length and invasiveness of risk assessment, improve risk selection and refine policy pricing.
Cognitive computing will push automated underwriting to new frontiers
Automated underwriting has been a growing trend in life insurance. Developments in cognitive computing – the simulation of human thought processes in a computer model – will advance automated solutions by bringing more consistency to underwriting decisions and by making the process faster and more cost-effective. Integration of the learning capabilities of cognitive systems, and also their voice recognition and text reading algorithms, will make it possible to extract meaningful information from all sources of data, including unstructured medical reports.
Cognitive systems can be developed to read an applicant’s information, put it in context, extract all relevant facts, compare with the rules and guidelines in underwriting manuals, make a decision on the application, and set a premium for cover if the application is accepted. Digitalization in healthcare and wide availability of Electronic Health Records (EHR) will make the use of cognitive systems more effective to this end.
New alternative data sources can be used to assess risk
The rapidly expanding universe of data in digital form – from EHR, connected devices, social media and other sources – provide alternative data sources which insurers could use to better assess and price risk, and in different ways. Use of non-traditional data will likely become more prevalent and may even eliminate the need for medical exams for many customers.
EHR contain various types of data including lifestyle characteristics, medical history, family history, clinical biomedical indicators and prospective medical treatments.
Getting the medical records of an applicant to underwrite a policy is currently a cumbersome and time-consuming process, with most of the information provided in print format. Ability to instantaneously access medical history with the individual’s consent in digital form eliminates the need for underwriters to search and wait for critical information, greatly streamlining and speeding up the underwriting process, and significantly reducing costs.
Data from health monitoring devices such as Apple’s HealthKit and Jawbone’s UP on physical activity levels, diet, sleep patterns and heart rate etc may also become useful. It is currently challenging to interpret these data for underwriting purposes because there is not enough research and experience to link the indicators to health outcomes with a comfortable degree of confidence. Companies are launching products that make use of these data though at the moment they have a low level of credibility on the underwriting side and are more of a customer engagement and retention tool. But in time this should improve.
Growing ability to measure and monitor risks on an ongoing basis could also open opportunities for life insurers to personalize pricing in real time, adapt products over time, and expand insurability or augment pricing for conditions where life and health risks can be mitigated by healthier lifestyles and behaviors. For example, a healthy diet and increased levels of exercise are known to improve outcomes for people suffering from chronic conditions such as high blood pressure and diabetes. People who alter their behaviors in a positive way may qualify for lower premiums rates.
Predictive analytics can streamline and cut the costs of underwriting
Predictive modelling – the use of advanced statistical techniques and data analysis to make inferences or identify meaningful relationships in order to predict future outcomes – can be an alternative means to differentiate and select risks.
The life industry has been slow to implement advanced data mining and predictive analytics techniques, but this will likely change. In the future, easier access to data in digital form and from non-traditional sources will enable a more widespread use of predictive analytics in underwriting. Ability to retrieve medical records instantaneously will accelerate the process and lead to better underwriting decisions, because EHR can easily go through predictive algorithms to produce more consistent results than human deliberation.
New tools for data analysis will also help. The premise is that there are correlations between lifestyle factors and mortality, and that more data and new data mining techniques will unearth these. Some early experiments have shown this to be the case. Life insurers currently do not make widespread use of third-party data on consumers beyond the types used traditionally (eg, from MIB Group, motor vehicle reports and prescription records in the US) due to concerns about regulatory and reputational risks, but the acceptance of using such data should improve over time.
Life insurers can use technology to broaden their reach and improve consumer engagement
The importance of new distribution channels such as the internet, smartphones and social media in life insurance is increasing. But effective distribution is not about focusing on one channel; rather, strategy should be geared towards reaching potential customers in a timely fashion with relevant content through preferred consumer channels. New technologies and increased data availability can help insurers tailor a multi-channel delivery approach to optimal effect.
One way to extend the reach of life insurance is to make the buying process easier, and here technology can help. A technique increasingly used by life insurers to engage customers is “gamification”. This is the use of game thinking and mechanics in a non-game environment to increase customer engagement and stimulate desired behavior through challenges, incentives and rewards. There is significant potential interest, particularly among younger people, in games and apps that can help them better understand their risks and insurance needs.
Moreover, technology can help life insurers to have a more interactive relationship with their customers. Currently, the completion of a policy sale often marks the end of customer interaction, with the remaining touch points focused on billing and claims handling.
However, this kind of relationship misses opportunities to address the full range of customer needs over their lifetime. Some life insurers have started to engage customers through programs that reward them for healthy lifestyle activities and choices, such as exercising, regular check-ups and giving up smoking. The Vitality program, developed by South African insurer Discovery, has been a leading example of how to retain customers by keeping them engaged.
New technologies also bring challenges
Amidst the vast range of opportunities, new technologies also bring challenges. In monetizing the potential of digital technology, life insurers could have problems from data protection and privacy, cyber security, fraud, records retention and authentication.
Companies will need to implement new risk management procedures, importantly around consumer data protection, and monitor regulatory concerns around digital distribution. Also, life insurers will not want to alienate consumers through their use of technology and data analytics and need to be cognizant of the fact that unsolicited, personalized offers of insurance are not always welcome. This seems to be more the case in developed countries than in the emerging markets.
On the flipside, life insurers are susceptible to rising risks of anti-selection (or adverse selection) as consumers build more understanding of their own health status with the different healthy-living apps and health testing devices available on the market.
The rise of non-traditional players is another development life insurers need to respond to. The new entrants present opportunities for mutually beneficial partnerships as some have access to huge amounts of data about individuals gathered from consumer use of smartphones, search engines and social media. However, non-traditional players have the potential to disrupt established industry practices and could eventually compete with traditional insurers. ◊
Endnote
1. See sigma 6/2016: Life insurance in the digital age: fundamental transformation ahead, Swiss Re
