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Predictive analytics are likely to be used more widely across pricing, underwriting, claims and mortality risk as insurers increasingly look to boost customer relations.

Both terms are used interchangeably, with business intelligence being the generalized term that encompasses analytics, but there are distinctions. The major difference between business intelligence and data analytics is that analytics is geared more toward future predictions and trends, while BI helps people make decisions based on past data.

Brands can make their marketing dollars go further by finding new opportunities within their existing customer base. Research has shown that attracting new customers can cost five times more than retaining existing ones, and an increase in Customer Retention of only 5 percent can increase profits by 25 to 95 percent.

Along with that, the earlier in the data pipeline that you can clean the data, that you can fix errors in the data, that you can validate the data, the easier and cheaper it's going to be for you to use that data later on.

By applying predictive analytics to customer data, retailers can harness their user habits and customer preferences to tailor their offerings to providing a personalized experience that can promote customer retention.

Though data is the centre of your business, it should never control it instead, your business should keep control of your data.

Even if everyone is data literate, many organizations need to consider if they have the data management piece aligned.

Digital transformation is here to stay, and it is dramatically changing the way we work.

In weighing up the potential impact of AI and data analytics on their businesses, executives should focus on enabling better decision-making.

Bratt said insurers who are seeking margin optimization and automation above all else will not survive in the long-run only those who perfectly balance the human touch and the use of smart technology will. In the future, he believes big data will just be called data. Major carriers will start using data to fuel machine learning and artificial intelligence on their rating engines.

We live in an era where data is not only getting more valuable by the minute, but also each minute more data is being produced than the one before.

According to Harvard Business Review, 99% of businesses surveyed reported that they intend to implement big data analytics and AI in the near future. On the flipside, only around 30% have actually succeeded in doing that.