A featured contribution from Leadership Perspectives: a curated forum reserved for leaders nominated by our subscribers and vetted by the Construction Tech Review Advisory Board.
Indonesia
Artificial Intelligence, Machine Learning and Insurtech
Gilbert Naibaho
As one of financial industry, insurance is among highly regulated industries and bound to regulatory that is different between countries. However, we don’t see this becoming a reason for the industry to be free from global competition. The exponential growth of internet usage in this generation contribute to rapid change of the insurance market. The explosion of internet users is creating a new level of demand in insurance.
Insurtech is introduced to overcome this situation. Insurtech is the combination of insurance and technology which means the emergence of technology that transforms insurance industry. The question is, does insurtech really exist in the market nowadays?
Some people will say yes because we can see insurance online platforms available in the market. Customers now can buy insurance products online. Some even provide claim service through their online platform.
The question again—Is it true that insurtech has been really in place? Is it true that insurtech is associated with online platform only?
Unfortunately, this is not the case. From my point of view, current insurance industry is still far from Insuretech implementation. Insurtech is not about delivering products to customers through online platform (e-commerce). It is far beyond that. Insurtech is when technology is implemented into insurance operation which includes product development, policy servicing, claims, customer services, underwriting, and marketing.
I would agree with Accenture (in their article, 2018) when saying that Artificial Intelligence (AI)
and advanced Machine Learning (ML) are among the top 10 strategic technology trends that leading organisations are currently using to reinvent their business for a digital age. In the case of insurance, I would define insurtech as the implementation of AI and ML in insurance operation to improve the quality and quantity of the business at the same time.
Why do I say this? Because Insurance is now facing two transitions at the same time:
1. Transition on demand. In P&C side, insurance facing different business model of industries and manufacturers with different level of risk and different approach in risk management. At the same time in life and accident side, the change in business model is also introducing new behavior of the generation with different risk perception. The changing is on progress so that insurance should be able to serve two business models which are the old one and the new one.
2. Transition on demography. The insurance industry now is still serving most of the gen X while the gen Y (millennials) is on the way to take its role. Insurance that is used to have a traditional and conventional procedure that fit to gen X no longer fit to the millennial way which tends to see the outcomes instantly (now). Again those two generations are now there to be served.
Considering those two facts, insurers will need to allocate more resources to serve two different generations at the same time if they stay with their “traditional’’ way. In contrary, AI and ML will play more efficient roles to connect the two generations into one platform since AI and ML have the capability to personalize service and fasten the process at the same time. Finally I would say insurtech (with AI and ML) is not an option, it is a must for the future insurance survival. To survive is to do digital transformation toward insurtech.
Unfortunately, this is not the case. From my point of view, current insurance industry is still far from Insuretech implementation. Insurtech is not about delivering products to customers through online platform (e-commerce). It is far beyond that. Insurtech is when technology is implemented into insurance operation which includes product development, policy servicing, claims, customer services, underwriting, and marketing.
I would agree with Accenture (in their article, 2018) when saying that Artificial Intelligence (AI)
and advanced Machine Learning (ML) are among the top 10 strategic technology trends that leading organisations are currently using to reinvent their business for a digital age. In the case of insurance, I would define insurtech as the implementation of AI and ML in insurance operation to improve the quality and quantity of the business at the same time.
Why do I say this? Because Insurance is now facing two transitions at the same time:
1. Transition on demand. In P&C side, insurance facing different business model of industries and manufacturers with different level of risk and different approach in risk management. At the same time in life and accident side, the change in business model is also introducing new behavior of the generation with different risk perception. The changing is on progress so that insurance should be able to serve two business models which are the old one and the new one.
2. Transition on demography. The insurance industry now is still serving most of the gen X while the gen Y (millennials) is on the way to take its role. Insurance that is used to have a traditional and conventional procedure that fit to gen X no longer fit to the millennial way which tends to see the outcomes instantly (now). Again those two generations are now there to be served.
Considering those two facts, insurers will need to allocate more resources to serve two different generations at the same time if they stay with their “traditional’’ way. In contrary, AI and ML will play more efficient roles to connect the two generations into one platform since AI and ML have the capability to personalize service and fasten the process at the same time. Finally I would say insurtech (with AI and ML) is not an option, it is a must for the future insurance survival. To survive is to do digital transformation toward insurtech.
The articles from these contributors are based on their personal expertise and viewpoints, and do not necessarily reflect the opinions of their employers or affiliated organizations.
