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Big Data

Contributory Data Can Result in Greater Returns and Increase Customer's Trust in Insurers

In India, data analytics is a phenomenon that insurance companies are just starting to adopt, some of the basic advantages of data analytics include faster and better decision making to gain a competitive advantage with unique insights from proprietary data
Contributory Data Can Result in Greater Returns and Increase Customer's Trust in Insurers
Image credit: graphicstock
MD – India, LexisNexis Risk Solutions
4 min read
Opinions expressed by Entrepreneur contributors are their own.

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Technology is the beacon of paradigm shifts across all walks of life, be it in businesses, economies or people’s day-to-day lives. Most industries are rapidly adapting technological processes to save costs and time and increase productivity, efficiency and ultimately profitability. 

The primary goal of all the stakeholders currently – insurers, the regulatory authority, the government and consumers – is to raise the penetration of life, health and motor insurance to enable policyholders to protect themselves from unforeseen circumstances. While the insurance regulatory authority has been at the forefront of creating a favourable environment for both insurance companies and consumers, there is much more that could be done.

Data Reveals

A recent report reveals that insurance penetration in India has moved from 3.3 per cent in 2014 to 3.44 per cent in 2015, attributable to the various insurance schemes that the government launched. India’s insurance penetration as a whole in 2015 was 3.4per cent, against the world average of 6.2per cent.  

While adaptation to new technology has enabled the rapid growth of markets for a large number of industries, a key player in the Indian economy - the burgeoning insurance industry - is yet to fully leverage the varied uses of technology to effect faster growth.

After Privatisation of the Insurance Sector

Although the insurance sector was privatised a few decades ago, insurance companies continue to hold bleeding portfolios, largely due to poor loss ratios, underwriting losses and claims frauds.

Given the long history of insurance companies in the country, it is evident that they hold reams of data which, if digitized and analyzed appropriately, could help yield significant insights for effective premium pricing, underwriting of risk, curbing fraudulent claims, and ensuring the more personalized customer experience. A big way to stem these losses is through the adoption of advanced data analytics solutions.

Policy

While the policymakers are in the process of creating a balance between privacy and the need to allow data to be used for legitimate and beneficial purposes, India has witnessed the first step towards a Data Privacy regime. By defining individuals as data principals and processors as data fiduciaries, it has enabled the committee to enhance the autonomy of the individual and places a great degree of responsibility on the processor to maintain trust.

In India, data analytics is a phenomenon that insurance companies are just starting to adopt.  Some of the basic

advantages of data analytics include faster and better decision making to gain a competitive advantage with unique insights from proprietary data.  An example of these insights is a closer understanding of an individual customer’s lifestyle, from health factors to what kind of vehicle they drive, which can be highly predictive of insurance risk.

Boosting these insights would be an intelligence exchange platform which enables industry data to be shared amongst insurers (large and small), with data being pooled from all segments of the total population. While an insurance company gains basic insights from its own data, there are exponentially more benefits that can be derived through data sharing, if handled securely by a trusted third party.  

A comprehensive database would provide deeper and more accurate insights into the lifecycle of the population set Data analytics applied to larger pools of data would also help insurance companies better understand their current and potential consumers, price premiums more accurately, and reduce the incidence of frauds.

Examples

An example of a smart data intelligence exchange would be one that holds multiple consumer data points – including their current and past policies, health declarations, claims history, agent network, habits and preferences, all of which aid in making better underwriting decisions at the time of policy issuance, claims payouts and policy renewals.

It is time that the Indian insurance companies consider data sharing and analytics as an easy way to leapfrog into the information age. Contributory databases are commonplace in more mature insurance sectors such as in the United States.

The creation and usage of a contributory database call for open and transparent sharing amongst all the players in the marketplace, supported by a trusted provider of data, analytics and customer insights. Insurers of all sizes benefit from having access to more information than if they are operating in isolation.

With this backdrop, the Indian insurance segment must work towards creating a synergistic decision to pool in their data into such contributory databases.

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