“Big Data” is disrupting all industries. It can even be used to change the way we play sports, shop, and live, and its potential to transform a range of professions, from insurance to healthcare, is increasingly apparent. Let’s think about Big Data as a way to collect both your moments and engagement with every “thing” around us and also the communication of “things” (i.e. machines) among each other. Then, these traces will be collected to associate and predict patterns in almost any industry.
2015 has been deemed the year of technology driven transformation in the insurance sector. The speed of change in an industry that has long been characterised as a slow adopter of technology is gathering pace and we look at four big ways big data and analytics are paving the way to these changes.
It is important for banks and insurance companies to seek for ways that reduce the number of potential losses as well as costs from claims processing and collection recovery situations. Mainly, this is done by attempting to gain insight into customer interactions and behaviors across different channels. One possible way is using graph analytics which are among the most promising big data applications scientists are working with today. These new types of analytics can be used to fight whiplash for cash scams. In graph analysis, insurance companies can perform analysis on huge amounts of data in much better performance and less time compared to traditional techniques in order to find suspicious behaviors. Thus, they can follow the whole fraud trail of all people and cars involved to detect whether they are involved in other accidents along with different degree of connection among them.
Big Data will enable insurance companies to gain a better understanding of their customers’ health over the life of a policy. With the rapid growth of the wearable technology market, insurance companies can build up loyalty programs using apps that turn fitness achievements into loyalty points. Nonetheless, these apps can track the behavior of customers while encouraging them to improve their lifestyle. Insurers can make use of these data points to reduce risks and enhance loyalty and retention. On the other hand, customers who improve their health habits can access different coupons and discounts in their shopping and leisure activities and also get better prices on insurance company’s products.
Social media is also a potentially large and profitable channel for insurance companies to use for competitive advantage. It can be potentially used to acquire a significant number of new clients, through social media analytics capabilities. It offers a unique cross-selling opportunity through linking social activity and profiles and insurance services consumption of the existing customers. It can be made use for assessing the quality of service, through early identification of customer dissatisfaction through customer service, brand sentiments and initiating marketing campaigns in response to trending or popular events.
In summary, social media offers an optimal solution and platform where intraday operational activity of potential and current customers on the internet can be monitored. Selling opportunities can be identified and demands and sentiments identified and analyzed in real-time.
Insurance companies rely on growing their number of customers by adapting insurance policies for each individual customer through fine-grained analytics. In telematics insurance, predictive analytics can help insurers get more accurate evidence-based insights about breaking speed limit and unsafe driving. In this case, these customers might lose points or get higher fees. Thus, Predictive models might then be used to analyze such risks or to give a personalized service to customers. Besides, Big Data analytics applications can be used to automatically assign the right claim adjuster to the right claim which will in terms result in improving claim duration and improve customer experience.
Big Data will enable resilient processes within the insurance companies especially when natural disasters occur where insurers want to settle claims in a short matter. Big Data can help by analyzing claims data in a quicker manner to assign the right claim adjusters and also setting the right limits for claim payouts.
What do you think about the future of Big Data in insurance? Feel free to share your comments and thoughts below.
This article originally appeared at FinTechUK.
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