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The new reality of AI in insurance

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AI has vast potential to transform the industry from ‘detect and repair’ to ‘predict and prevent’

Industries from around the world are facing disruption as a result of using artificial intelligence (AI) in key operations. But the insurance industry, in particular, is slowly capitalising on this technology leading to the evolution of insurtechs.

So the big question is—what is the reason for AI and insurance to go hand in hand? In the past, carriers have been conservative in technology adoption compared to those in the banking industry—creating an obvious gap between technology adoption and transformation in the industry until recently.

Now insurers are individually and collectively seeking to innovate their operations, products and solutions to strengthen the global insurance market at large. For example, disruptors are entering the current market scene and changing the standard model of micro insurance.

Imagine, how will it play out if Google or Amazon forayed into the insurance industry? The existing insurance companies would not be able to sustain a massive transformation overnight, especially with a limited use of technology. For that reason, it is essential for insurance companies globally to adopt and use AI to cope with industry setbacks and unprecedented changes in the future.

AI is a game-changer for insurers
In fairness, insurance companies globally have realised the potential of AI to synchronise the insurance ecosystem and streamline processes. This in turn will help them to work on the existing layers of complexities to develop a sustainable customer-centric approach in the long-term.

Traditionally, an insured customer will have two main points of contacts with the insurer. First is the policy submission followed by claim notification. These are core processes which give carriers a unique advantage to understand customer requirements first hand. It is worth noting that outsourcing the claim process is not very savvy.

AI has now become a game-changer for the industry. AI-enabled chatbots are being implemented to simplify the claim process run by insurers. In translation, this touchless insurance claim process eliminates excess human intervention and can seamlessly report the claim, capture damage, update the system and communicate with the customers without any supervision.
For insurers, the customer-centric approach is no longer an option. So it is disappointing to think that there are insurance companies that still remain short-sighted in their approach while trends across customer demographics are rapidly changing.

New model is on the rise
How can technology concretely help insurers in practice? In this context, AI can help monitor and predict risks by giving customers indications on how to reduce risk. For example, having healthy behavior can prevent health problems, and in turn, reduce the premium rate. The final purpose is to reduce the frequency and severity of losses over time.

Because insurance is a highly regulated industry, carriers have been slow in adopting this technology compared to other industries. That said, they are now rethinking their customer engagement and in this evolution, insurance is ideally shifting from its current and traditional state of ‘detect and repair’ to future ‘predict and prevent’, transforming every aspect of the industry during this process. In another example, road accidents can be reduced as a result of using autonomous vehicles—and health damages can be lowered owing to healthy behaviours. Also, home and property damages can be prevented through the adoption of IoT devices.

Developing an ecosystem approach
In recent years, technology products, even the most advanced and AI-driven ones, have important limited value when used alone—but can substantially increase in value when used with complementary applications. This is known as an ecosystem approach. In a nutshell, there is no one-size-fits-all technology or AI software which can solve all the problems on-the-go. Multiple technologies and technological methodologies, if combined together, can provide tangible benefits thanks to complementarity.

Skepticism slows AI adoption
It is worth noting factors that slow down insurers in AI adoption and where does their resistance to change come from?
Skepticism is definitely a relevant variable and is the typical resistance to change. Disruption can easily polarise reactions and behaviours: convinced promoters and supporters vs. strong and inflexible detractors.

However, one of the most deep-rooted causes to resist change in the insurance industry is culture. To innovate, insurers have to experiment, pilot and redesign their processes and offerings. Insurers have always focused on avoiding failure. However, evaluating the risks in detail which can be a time-consuming but worthwhile activity will make a difference and increase the pace of change.

All these factors should be part of every insurer’s coherent analytics and technology strategy that addresses all aspects of the business, with a particular attention on both value creation and differentiation.

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