Tue. May 21st, 2024
Ovik Mkrtchyan

Ovik Mkrtchyan, corporate consultant of the Gor Investment Limited group of companies, shares his expert opinion on the trends in the implementation of Big Data, IoT and Machine Learning in the insurance industry.

Reducing and diversifying risks, providing reliable protection against financial losses – these tasks have been key approaches for enterprises in many fields for decades. However, achieving these is of particular importance for insurance companies, which is why they constantly modify business processes and introduce new technologies. Increasing public awareness of the services of insurers has seen them using various forms of unstructured data, machine learning algorithms, and artificial intelligence. The insurance industry paid special attention to these technologies of course during the pandemic which itself prompted universal digitalisation.

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Increasing customer loyalty and retention

In the future, according to Ovik Mkrtchyan, the successful companies in the insurance sector will be those that can quickly and more accurately adapt to changing conditions. This will only be possible in the case of those with a built-in analytics system, competency in data work and the correct interpretation of that data. The result will be optimised business processes, increased customer loyalty and, importantly, a reduction in costs.

“I believe that over time insurance can become a ‘pioneer’ in terms of innovation in the use of Big Data opportunities. This is due to the general trend now going on towards the digitalisation of business, changes in technology, and the fact that zoomers, including entrepreneurs, are starting to contact insurers. The younger generation of course is accustomed to all-inclusive digitalisation through activities like car-sharing and smart devices, they understand that technology can make life so much easier. Creating a positive customer experience is one of the challenges for insurers. Technological changes can be seen even now of course. Could we have imagined even a short while ago that we would be able to use the online insurance regulation service through a mobile app?” Ovik Mkrtchyan enthuses.

An ‘intelligent’ and flexible approach to customer service is gaining momentum, as is the technology race of insurance companies. But how are Big Data and customer loyalty connected? The fact is that algorithms, based on user behaviour and pulse survey data, are able to determine when a client was dissatisfied with the quality of a particular service. This allows timely action to be taken to correct the situation. Such mechanisms contribute to customer retention.

The boom of unstructured data

Insurance companies have always worked with structured data. Back in 1762 James Dodson, British mathematician, actuary and innovator in the insurance industry, identified a number of mathematical patterns and introduced an initiative to establish the amount of insurance premiums in accordance with the age of clients. Today, insurers continue to use structured data including, for example, information about the name, place of residence, age, of a potential client which is entered into standard tables and systems. It is easy to work with such data, but they do not give a complete picture. More accurate analytics requires unstructured data. Their correct use and interpretation is therefore an important milestone for insurance companies.

Unstructured data may include, for example, information about the user obtained from his social media accounts, habits and lifestyle features. Such data is more difficult to collect, store, process and use. However, with IoT (the Internet of Things) tools come to the rescue, contributing to the formation of a methodology for working with information and creating more accurate client profiles. Big Data allows the capture of more data and generates more accurate analytical and predictive reports, as well as making forecasts and assigning customers to different risk groups. Put simply, the whole process can be compared to assembling a puzzle.

“A good example of this is life insurance. You can personalise the terms of the contract – make it more client-centric if you add information about the client’s health status, his habits, and general activity to the usual structured data. This will help diversify risks and create a more flexible pricing system as regards premiums. We see similar cases in foreign practice with Insurtech companies and startups,” says Ovik Mkrtchyan.

“Another similar example from the car insurance sector is telematics – that is, a system for collecting information in real-time using sensor technologies. This is an innovation in the field of data collection proposed by insurers. People like telematics policies and that’s because careful driving keeps insurance premiums down. For companies, it simplifies the process of considering possible claims,” adds Ovik Mkrtchyan.

Big Data and the future of insurance

Innovations in technology include a number of nuances that can complicate the work of insurance companies. First of all, we are talking about compliance with the GDPR – correct work with data – ensuring transparency in the collection and secure storage of information.

Another aspect is the problem of staff shortage. To work with Big Data, IoT and ML, qualified specialists are needed and the situation is complicated by the fact that in today’s highly-competitive market, such talented people receive a lot of job offers – all of this coupled with the growing demands of customers to ensure high-quality services.

“Despite some barriers faced by insurance companies during the introduction of new technologies, forecasts for the development of the industry are optimistic. Digitalisation remains a driver for the development of the insurance industry,” Ovik Mkrtchyan concludes.

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