Data velocity and variety, key challenges for insurance firms
The insurance industry is poised to capitalize on the growing potential of big data and analytics solutions. However, many insurance companies are facing challenges with big data, particularly when it comes to dealing with the tremendous data velocity and variety, more than the volume of data. This is unlike several other industries where enterprises see huge volume of data as the key impediment in big data deployment.
Handling data velocity and variety
According to a recent report by research firm Celent, almost 80 per cent of respondents experience difficulty in collecting and analyzing data promptly, and over 70 per cent have problems in dealing with unstructured or semi-structured data. The report states that when data lacks structure, analytics tools tend to be inconsistent in delivering reliable results.
“Many insurers are not able to perform data analysis quickly because they do not have the necessary computation resources to run algorithms on a large volume of data,” says Nicolas Michellod, Senior Analyst at Celent and co-author of the report. “Sources of data insurers need to leverage to perform certain types of analysis are growing rapidly. In this context, we think insurance companies will have to address the volume challenge with new investments in technologies, thereby improving the performance of their analytic tools,” he says. For example, a commercial fleet insurer may use actual data derived from telematic devices implanted in vehicles to underwrite a policy and set rates.
Celent report also notes that although very few insurers at present are using external data, they have begun to understand there is potential value in leveraging external data sources – such as the ones available on websites, social networks and other media. “One of the major problems, though, is finding an efficient approach to include these data sources in their daily analysis,” says Craig Beattie, senior analyst and co-author of the report, adding that insurers have not really captured the importance of mixing data from different sources to the benefit of their activities.
Leveraging big data strategically
Deapite several challenges, insurance companies are realizing that big data can improve their overall performance by facilitating greater pricing accuracy, deeper relationships with customers, and more effective and efficient loss prevention if used strategically. A recent PwC report notes that insurers that are able to leverage big data and analytic technologies to make sense of the growing amount of internal and market data available ultimately will gain competitive advantage.
The propensity of an insurer to deploy advanced analytics and big data will likely depend on how strategically the company is able to leverage on the capabilities. Analysts note that as the insurance industry is highly customer centric, insurers should build teams with strong data analysis capability and appoint specific people to identify and modify certain data before jumping to the big data bandwagon. As the study also indicates that although insurers are taking a somewhat pragmatic approach to data with newer technologies, significant gaps exist in their perception of both their competitors and their customers.
In this context, Amarnath Ananthanarayanan, MD & CEO, Bharti AXA General Insurance explains that CIOs in insurance firms can leverage data analysis technologies to improve their business basics with growing interest in cloud-based analytics, but big data-related technologies are still not popular to many insurers. Insurers are still struggling to find value in big data. Moreover, pricing optimization, customer segmentation, underwriting and fraud detection are the areas insurance CIOs should focus on when leveraging big data infrastructure.
“Insurance companies must treat data as a critical raw material,” believes Beattie. “In many mature insurance markets, loss ratios deteriorated as fraud became more organized and structured,” says he, stating that fraud mitigation tools can offer strong value to insurers when they are coupled with big data infrastructure with a number of out-of-the-box solutions already implemented on big data techniques and technology.
Beattie also adds that an insurer not investing in big data technologies is behind the competition already. Those that are cautiously investing in these types of technologies since the last one or two years are likely to have a competitive edge in the coming days.
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