New technologies like AI are already part of our daily lives and are changing our lives in a big way. The insurance industry will not be spared in a revolution where their customers, for instance, are using wearables that can transmit real-time health data. We are also experiencing more uses of blockchain to enforce strong data security and consistency. To survive the changes, insurers need to embrace the technologies, adapt their products to fit the new realities.
Insurance technology trends will increase competition with new entrants joining the market as existing players grapple with the hostile environment. McKinsey & Company agrees with these sentiments, affirming that technology will alter the structure of many organizations (1) in the coming decade. Future leaders in the industry will be organizations that integrate these technologies into their core processes and adopt an innovative mindset in light of the new realities.
Our assessment of the life and health domain has proven how new technologies are gaining momentum.
Technology adoption in actuarial practice has far progressed beyond using digital communication devices. Already, insurers have to balance the influence tech giants and regulators place on their business. Rewriting business models is one way of adapting to these changes. But the more sophisticated approach leading to improved speed of delivery and better cost ratios should see insurers exploiting the following five technologies:
Artificial intelligence has the potential to rewrite many processes in insurance practice. AI is already being used in fraud detection, risk calculation, and virtual customer support. According to the FBI, insurance fraud causes over $80 billion in damage to the industry (2). The bleak statistics translate to massive losses for insurers and increased premiums for consumers, and AI has proven effective in prevention.
The predictive nature of underwriting services informs the shift to predictive analytics. For instance, life underwriters can use machine learning models to predict future risks for customers, work with them on preventive measures, and help to bring down claims.
The accuracy in AI is much higher than in human-in-the-loop systems.
Data has many roles in actuarial practice. For example, life insurance providers can make better policy decisions using consumer health and lifestyle data. Big data is vast, complex, structured, or unstructured information that businesses rely on to make decisions. The data possesses three key characteristics (3) that make it hard to process using conventional methods:
The value of big data lies with the insurer’s ability to process the data and drive revenue growth, improve operational efficiency, and innovate new products.
Blockchain is gaining traction across all industries. Although much of the hype around the technology is built on cryptocurrencies, the idea of smart contracts and distributed ledgers have a massive disruptive potential for the industry. Blockchain technology allows us to transfer digital assets and documents securely.
One of the groundbreaking ideas already being implemented includes sharing data on the blockchain to curb insurance fraud. By consolidating claims data across all industry players, insurers will be able to detect suspicious patterns along the channels (4). Of course, it will need immense collaboration and commitment, but it will prove beneficial in the long run.
The internet of things (IoT) is led by the development of programmable devices and sensors with internet connectivity. These devices collect user data or information about the environment and relay it to other connected gadgets. IoT provides an immense opportunity for insurers to develop new business ideas. McKinsey estimates that by 2025, people will own more than 50 billion networked devices(5).
Life insurance, for instance, can capitalize on the use of smart sensors and wearable health devices to remove group bias and match customer lifestyles with policies.
The interconnectivity of devices poses a vital security risk, and insurers must enforce strict access control and secure the communication channels.
Automation depends on some of the technologies we’ve mentioned before, but it remains a unique concept because of its transformative power in the flow of work. Indeed, Deloitte affirms that up to 22.7 million jobs in the US will have been automated by 2020 (6). The key triggers for this shift in the insurance industry are high claims ratios, volatile interest rates, and rapid deregulation.
Insurance practice relies on speed to deliver services: faster claims settlement, rapid onboarding systems, and fast time to market for new products.
Predictive analytics is a model used by insurers to identify behavior patterns and determine their likelihood in the future. In life insurance, it helps underwriters to ascertain the risks associated with unhealthy lifestyles. Such information affects the pricing of the premiums. It also reduces genetic bias, as it is easy to separate it from other factors more accurately.
Predictive analytics insurance can be applied in different areas. Rate-setting and premium prices, for instance, will be based on individual risk rather than group factors. Such a move will see an uptake in life product consumption. Claims management will also be improved, with faster processing and better fraud detection becoming the norm.
Pilotbird’s lifestyle risk scoring engine is a good use-case example. Analyzing over $400M+ worth of group life insurance products while modeling the underwriting process, the software improves accuracy by up to 3 times.
The Willis Towers and Watson survey of 2020 already affirms the potential benefits of predictive analytics to life insurers. Over 80% of their respondents agreed that using predictive analytics had brought positive results to their business (7). Their study allocates its usage to 70% for large carriers, 50% for mid-sized, and 54% for smaller underwriters.
Navigating the landscape for the modern insurance executive means that they have to be proactive in spotting technological shifts and rapidly adapting to insurance technology trends. They should stop treading underwriting as something they review periodically and focus on technology-enabled data processing and sharing at massive scales. New and better insurance products will continue to emerge as more insurers embrace the technologies.
1). “How top tech trends will transform insurance – McKinsey.” 30 Sep. 2021, https://www.mckinsey.com/industries/financial-services/our-insights/how-top-tech-trends-will-transform-insurance.
2). “Insurance Fraud – FBI.” https://www.fbi.gov/stats-services/publications/insurance-fraud.
3). “What is Big Data and Why is it Important? – SearchDataManagement.” https://searchdatamanagement.techtarget.com/definition/big-data.
4). “Insurance Disruption Using Blockchain Tech l CB Insights.” 2 Aug. 2021, https://www.cbinsights.com/research/blockchain-insurance-disruption/.
5). “Digital ecosystems for insurers: Opportunities through the Internet of ….” 4 Feb. 2019, https://www.mckinsey.com/industries/financial-services/our-insights/digital-ecosystems-for-insurers-opportunities-through-the-internet-of-things.
6). “How robotics and cognitive automation will transform insurance ….” https://www2.deloitte.com/content/dam/Deloitte/mt/Documents/rpa/mt-cons-how-robotics-and-cognitive-automation-will-transform-the-insurance-industry.pdf
7). “Improved performance and customer centricity drive momentum in ….” 25 Nov. 2020, https://www.willistowerswatson.com/en-GB/News/2020/11/improved-performance-and-customer-centricity-drive-momentum-in-use-of-predictive-analytics-by-life.
Mani Kaur is an industry thought leader in the insurance industry with numerous articles on technology, innovation, and financial services.
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