Insurtech is the latest buzzword making the rounds within the chief experience officer (CXO) quarters of the insurance industry.
Unlike banking, insurance has never been known for its romantic pursuit of technology. But never has technology created so much buzz in the insurance industry as it has with this latest term.
Insurtech, a moniker adapted from its more famous cousin “fintech,” is not merely a combination of the words insurance and technology. Rather, it aptly symbolizes the disruption that technology is creating in the insurance business.
While fintech is disrupting banking industry processes by enabling newer ways of doing business, insurtech goes one step further in the insurance industry by disrupting its very business model and products.
Let's examine the “famous five” disruptive technologies of insurtech.
5 Artificial Intelligence
AI-driven cognitive robotic automation has tremendous potential to elevate the traditional, intricately-human, process-dependent insurance industry. Be it quote (and illustration), know your customer (KYC), or claims processing, insurance processes have traditionally been tardy, complicated, and documentation-heavy.
To add to these woes, human errors make the processes inefficient and expensive, leading to money leakage.
AI can take process automation to the next level, thereby reducing operating costs. Another area where AI is going to make a significant impact is service and engagement through on-demand robo-advisors or chatbots.
With payment of premiums and claims being the most likely and infrequent customer touch points, insurance has much to do in terms of customer engagement.
AI can help tremendously in these areas.
4 API and microservices
This is another area of technology that can help insurers up their game.
Core platforms and technology ecosystems are still heavily leaning towards older or legacy technology, and associated sunk costs. Insurers should aggressively use APIs (roughly, a set of clearly defined methods of communication between various software components) and microservices to decouple modular processes—that is, help modules interact with other modules simply, without their being dependent on each other—and expose them, such as providing the user with an interface to access them, so customers, agents and other partners use only the required services as and when they need them.
Exposing processes such as financial need analysis or changing of premium payment frequency can only help sell more and service better by putting power in the hands of customers.
Distributed databases are the new kid on the block. After creating waves in banking and financial services, the blockchain system holds significant promise for the insurance industry.
Blockchain features include immutability, or the idea of making data that's entered unchangeable, disintermediation, or the ability to omit a middleman, and smart contracts. These ideas relate so much to insurance and its needs that it's only a matter of innovative thinking and time before blockchain finds usage and major adoption in the insurance industry.
Since insurance is essentially a contract, there is significant opportunity to adopt blockchain reincarnating into smart contracts. Placement, negotiation and binding of risk in a commercial insurance broker market place, automating claims settlement for simple claims, or sharing customer KYC data on blockchain, and managing reinsurance treaties are just some of the possible use cases.
2 The Internet of Things (IoT)
This technology has perhaps the biggest potential to impact the insurance industry. An increasing number of devices, used in various quarters of human lives, are getting connected to the internet and the data collected from inbuilt sensors are becoming available for consumption.
While being “in touch” with our devices is a new way of life, it has its own ramifications for business, particularly insurance.
IoT is impacting the very core of the insurance business, which is risk assessment and product. Be it a connected car or the Fitbit band worn by an employee, products are telling a story which helps insurers better understand risk, allowing for increased granularity in pricing and embodying a paradigm shift from risk classification to risk personalization.
The sensor data may also be analyzed to expose failure symptoms, thereby bringing the ability to preempt claims and reduce loss costs.
1 Data and analyticals
Data-driven insights (also known as actuarial science) have long been a cornerstone of insurance. Hence, underlying the above technologies, big data and machine learning are the keys to unlocking the full potential of insurance in the current century, be it sensor data from IoT, or the process data or customer interaction data generated from cognitive automation.
We live in an age when we are continually generating data, in both structured and unstructured fashions, across business, devices (IoT), or customer interactions (contact center, social media, chatbots). The insurance industry is constantly being exposed to a variety of potentially useful data.
Soon, big data will no longer be a choice, but a key component of business operations. Machine learning is a willing partner to bring automation in the use of such a volcanic eruption of data.
Insurtech gives the industry an unprecedented opportunity to explore new dimensions of the business and morph itself from the age-old traditional set of processes and products to something befitting of this age. This should make for exciting times ahead.