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Insurtech: Expectation Vs Reality

The idea behind the implementation of technology in the Insurance sector is to make the Insurance processes much more efficient, comfortable and provide the customers with a simplified interface. In recent years when talks about Insurtech was ripe then it was all about blockchain, IoT, wearables, innovations labs and AI. But, as the things started to roll out, it doesn’t seem to be an easy road with expected results will not be visible anytime soon. The digitalization of the Insurance industry has begun with a boom but the challenges surrounding this whole new era are unlimited, and Insurers need to strike a balance between expectation and the practicalities.

The challenges of the Insurtech industry and Insurance as a service:

1. Data and more data

It is a matter of the fact that the available data for the insurers is unlimited which help them to underwrite policies, detect fraud, price the products that were otherwise not possible traditionally. Insurers are constantly gathering, incorporating data received from automobile sensors, home sensors, Amazon web services, social media channels into their business models. It is a great way to be efficient enough and provide relevant content to the insurants.

Reality: There is a widening gap between the available data and the ability of the insurers to process this data contextually and derive insights into it. The data is something that keeps changing continuously, and it needs to be processed and used quickly for the expected results. But, the truth is that insurers do not have any actionable information around this data as they lack the proper infrastructure for fast processing the datasets.

2. Automated customer service and the chatbots

The impact of AI and machine learning on InsurTech is profound, and it is most visible in the customer service department. The automated chatbots are programmed to provide an instant solution to customer queries without any delays.

Reality: Even though chatbots are being adopted by big insurance companies, but accuracy is still an issue. The more complex the chatbot is, the more problematic it becomes.  No matter how intelligent a chatbot is, it can never replace a human.  Insurers need to ensure that their bots offer a high level of data protection and are compliant with regulatory measures.   There are still customers who want to talk to the customer representative, not an automated agent. So, chatbot can never replace the human representatives it can just be another option of communication.

3. AI and cognitive automation

Data analytics and AI are a boon for the insurance industry. The power of AI backed systems help insurers to accurately price risk, manage claims value and do a lot more than only providing insurance. For example, in health insurance, the insurance product is more like a health assistant and for auto insurance using car sensors for usage-based policies. All this sounds like an insurance-perfect technology which is ready to revolutionize the insurance industry.

Reality: The technical hurdles sprout at every stage of AI implementation. AI helps insurers, but it may prohibit them to consider some factors or introduce some new precise elements. The immense intrusion of AI into the systems poses a roadblock that is the more sophisticated and accurate AI becomes the capability of humans to interpret and understand it keeps growing bleak.  It is a challenge for the state actuaries and the rate reviewers who are responsible for evaluating the vast number of risk-classifications and seeing how it influences other in the process. Rate determination for tomorrow requires a perfect balance between the insurers and the AI-driven risk pricing tools.

From the above, it can be concluded that the insurance industry is rapidly evolving introducing a new wave of innovation. But, the challenges are still persistent and to be successful insurance companies need to employ quality people with competent management and supporting technical infrastructure.


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