Choon Yan previously led the PayPal Startup Relation team in APAC and is a mentor in various Asian accelerators. Insurance policies can be complex, and some policyholders may not understand all the fees and coverages included in a policy. Indeed, people typically buy policies on unfavorable terms. In 2014, two major insurers, Blue Shield and Cigna of California, were sued for misrepresentation of the coverage network, which caused delays for their consumers in accessing needed health care. Yet, insurance should help societies and individuals mitigate catastrophes' impact through the way it changes who bears the cost of losses.
Before assessing the potential impact Artificial Intelligence can have in the health insurance industry, it's important to understand what the term "AI" really means. In general, AI refers to a series of algorithms that can collect, process and analyze data on their own, without being explicitly programmed, to make predictions and insights far beyond the capabilities of manual processing. Originally conceived back in the 1950's companies have been attempting to design and improve machine learning models for decades only to have seen little commercial success. But thanks to hardware advances and the emergence of big data analytics, companies are recognizing and taking advantage of the true power of AI. In the health insurance space, there are many opportunities where AI and analytics can be applied to increase organizational productivity and drive new competitive advantages in today's fast-paced and complex business environment.
Since the insurance industry is founded on estimating future events and measuring the risk/value of these events; volume, velocity, veracity and variety of massive datasets has become an essential tool for insurers. With new data sources such as telematics, sensors, government, customer interactions and social media, the opportunity to utilize big data is more appealing across new areas of this industry nowadays. Big Data technologies are used comprehensively to determine risk, claims and enhance customer experience, allowing insurance companies to achieve higher predictive accuracy. Let's take a look at the major uses of big data and its technologies in the insurance industry; One of the most important uses for insurers is determining policy premiums. Used mostly by automobile, home and health insurance companies, many insurers benefit from telematics (in-vehicle telecommunication devices) IoT devices and wearables (Fitbit, Apple Watch etc.) to track their customers in order to predict and calculate risks.
The global insurance industry will grow more strongly than the global economy in 2018 and 2019, Munich Re predicts in its latest outlook. "This year and next, we expect global premium to grow by more than €460 billion in all. This is equivalent to average annual premium growth of 5.3% (in real terms, i.e., adjusted for inflation: 3.7%), whereas global GDP is expected to grow by only 4.9% (3.3% in real terms). Life insurance, in particular, looks set to return to strong annual premium growth of 5.6% (3.9% in real terms) after a weak 2017. Property-casualty insurance is benefiting from the currently favorable economic environment.
The complexity of change occurring within the Life & Health insurance value chain is much greater than in other insurance subsectors and the potential positive impact on the quality of life for the consumer is much more profound. As we are seeing a growing overlap between Life & Health insurance, we combined these two markets into the theme for this quarter. InsurTech has the potential to bring them even closer. In our Q2 2018 Industry Theme, we focus on three key areas of Life & Health disruption: data, customer and product. Incumbent Life insurers sell a combination of protection (injury or death benefits) and accumulation (future income) products.