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Data still the biggest obstacle in insurance

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Insurers have many bespoke solutions to meet the diverse requirements of their customer base. To develop these, they utilise systems such as enterprise resource planning and broker and claims management to pull data together from many disparate sources. But herein lies the challenge as these systems do not integrate effectively with one another thereby reducing the effectiveness of the data.

By Tony Bell, director of sales at Decision Inc.

In fact, the biggest problem for insurers is managing the data-rich environment between their internal systems. Tools that perform data blending and ETL (extraction, transformation, and loading) can help in this regard by linking data from various sources. Unfortunately, many decision-makers are ignoring the problem or not addressing it as quickly as they should.

With the rise of Chief Data Officers and Chief Analytic Officers, there is an increased awareness around the importance of this integration and the need to find more innovative ways of extracting value out of the available data.

 

Exponential growth

With the sheer volume of data growing exponentially, it has become a business imperative to integrate the company’s own data with that of the industry and pull strategic insights from there. Complicating matters is the reliance on insight generation tools that, while successful in the past, are not fit for the more modern digital business environment.

To address this, insurers need to find ways of managing their data in smaller chunks. So, even though they might have different systems of gathering data, the tools they use to blend it do not become focused on just one aspect of the information. Executives also need to accept that more innovative tools are released faster than before and can blend data more cost-effectively.

 

Planning ahead

When it comes to solution development, insurers have a solid roadmap strategy in place. However, the availability of resources and high costs might not always make it practical. Adding to this pressure is the comfort level that exists with current vendors and an unwillingness to try something new.

Innovative data analysis solutions are more readily available. These solutions provide the insight required to dynamically change product strategy to be more reflective of current customer requirements. This trend has led insurers to recognise the importance of trying new vendors (and tools) to meet real-time business demands.

Digital transformation has become an essential driver in the insurance environment. Consumers are already getting close to the claims process thanks to the likes of mobile apps that enable them to take photographs of accident damage and submit it for automatic processing.

 

Changing the traditional

Even the field of fraud analytics has the potential to be positively impacted by this change in approach. Using better analytical solutions, insurers will be able to investigate fraud more effectively and manage the various thresholds they have in place. With fraud impacting everything from insurance cost to making certain products unviable, this provides the insurer with much-needed opportunity to expand the business.

The broker versus direct model is another challenge that more intuitive solutions can help address. Brokers used to be the ones selling policies but that is now being bypassed with customers going direct. Brokers now need to provide a more personal approach to set themselves apart from insurers.

Currently, many insurers are going into the direct business for mainstream solutions but are remaining loyal to their brokers when it comes to more niche offerings. This is only possible thanks to the more advanced data analytical tools available providing the necessary insight to do so.

Digital transformation is not going to go away. Insurers must learn to embrace change and be willing to examine how new data analytical techniques can assist them to bring more customised and innovative solutions to market. Fortunately, it has started to happen with many seeing the value in this evolution.