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Big Community was privileged to talk to Arun Sundar Chief Strategy Officer at TrustSphere. This was ahead of the 2nd Asia Conference on Big Data and Analytics for Insurance held in Singapore at which Arun was scheduled to speak at, but due to unforeseen travel circumstances, had to be replaced by his colleague.

Nevertheless, Arun was gracious enough to be interviewed on his thoughts around how the insurance arena is being affected by Big Data Analytics and what is the future he foresees.

Arun Sundar is one of the eminent thinkers in the emerging technologies space in Asia Pacific. He has built, led and advised emerging technology businesses across the globe and was one of the key management team members who established the category of ‘Relationship Analytics’ globally as part of the current venture TrustSphere where he is their Chief Strategy Officer. He is also the Chairman of Asia Analytics Alliance, a special interest group of Asia Cloud Computing Association where he lead the oft-referred and first of its kind study in APAC on the supply and demand gap for big data analytics in Asia Pacific. One of his interest and passion is in understanding the disruptive technology eco-systems across the world and cross pollinate learning b/e East and West. Arun is a regular speaker, writer and opinion leader in the IT market place in APAC, US and Middle East.

“The truth is for any new technology to be adopted in an established industry, it will either be to increase the revenue or to reduce the risk”, said Arun. “In the risk aspect, analytics has proven to be able to reduce risk but it isn’t 100% full proof, which is why analytics is predominantly used for revenue enhancements”, he added.

This being especially true since analytics are already being used to increase market penetration. But how will this work in favour of the insurance industry per se? Arun believes the trends will enhance in to two separate directions with the first being increasing revenue.

He attributes this to how consumer data in increasing by the day with new data sources and new technologies too that are able to curate and make sense of the data. This will in many ways accelerate the growth of the industry.

“So now that this has proved the value of analytics in the industry, they will start looking at other avenues of leveraging analytics. Whether it is for employee satisfaction, improving business operations and improving ROI or any number of marketing strategies”, he said saying this will be the second trend he sees.

That being said, some areas of the industry will grow into using analytics faster than others such as with property and casualty insurance, where we tend to see a high demand for advanced data analytics as compared to other products in the industry.

“The availability of data sources, to make sense of the data and leverage value for these segments is exceptionally high. For instance if we want to look at how the property market will behave, there is a lot of both, historical and real time data that is available. When you have a lot of data available, you will tend to utilise those to get better insights and improve innovations”.

With the onset of the growing data sets available, the tendency to use emotions to make decisions on the value of property in this instance, will now become governed by data thus eradicating the possibility of the ‘hunch’ on certain value or predicament.

“Insurance has traditionally been an emotional decision on both ends. Eventually it will become more of an analytics game, leaving little to chance and that has already taken place in the space of property and casualty insurance”.

With other segments of the industry, first there has to be value gleaned from the technology, before it can be considered as a tool that has value.

“For analytics to enter into other segments of the industry there will need to be data sets and data models to provide insights. I foresee that to happen in time but not for the next 5 to 10 years”.

An important aspect of moving the industry to the next level in using analytics, is through collecting more data. When there is more data, then patterns can be formed so that the analytics which is all about understanding the patterns in data, can produce the insights necessary.

“I don’t believe we will ever reach a point where the data will be adequate and we understand every pattern. The reason being none of the patterns will sustain for long since patterns are known to change. So when patterns change, we assume that if we had more data, we could predict the change in pattern. However, we will never have adequate data to understand all the patterns”, he hypothesized. “Adequate is a state you will never reach in analytics”.

At the same time, collecting data indiscriminately might have an effect on the consumer as well and be against fundamentals of the consumer vendor relationship.

“Policies can be made very personalised with analytics through using different types of analyses such as behavioural and emotional analytics and therefore catering to the clients’ needs as they require them. However once an organisation starts knowing more than what the individual wants them to know, then they would be abusing that power entrusted to them if they acted on it. There have been numerous cases of this and proper mitigation steps need to be put in place to ensure the rights of the consumer isn’t abused”.

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