The interest of insurance sector for analytics and big data started in the automotive insurance market, which plays a big role in US property and casualty business (P/C). Instead of price policies based on variables like age of the driver, zip code, gender, etc. companies started to use analytics to target their potential clients more effectively, better select data and better select risk.
Now big data analysis is spreading through other insurances lines like commercial and home insurance sector with the possibility of changing the whole business model.
What is Big Data?
According to Big Data expert and Forbes contributor, Bernard Marr, Big Data refers to “ The ever increasing amount of digital information being generated and stored, and the advanced analytics procedures which are being developed to help make sense of this data”.
Marr explains that examining data collected from the past is helping to build models to show what could happened in the future. In an industry based on predicting risks, this possibility is key to offer a better service to potential customers.
That´s exactly what Capgemini’s Seth Rachlin (with 25 years of experience in the insurance market) tell us about what we can expect in the future of insurance business. He says that, to stay competitive, insurers need to keep investing on improving their technology and capabilities.
He also assure there will be a high level of customization: “People will be able to buy the insurance they want and need, priced and tailored to what they’re actually doing. It’s going to come to resemble far more what it does now a more traditional retail-oriented industry business.”
In conclusion, there are multiple benefits of using Big Data and Predictive Analysis. Here a few:
Advantages of using Big Data for insurance:
- Identify new customers.
- Predict fraud.
- Streamline costs.
- Target possible customers.
- Identify possible expensive claims.
Sources:
www.datanami.com/2016/01/05/how-big-data-analytics-is-shaking-up-the-insurance-business/
http://www.ft.com/cms/s/2/3273a7d4-00d2-11e6-99cb-83242733f755.html?siteedition=uk#axzz49CfpfiUP
