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How Big Data Contributes to the Insurance Industry


Insurance is of significant importance for every individual as it deals with shielding our lives and assets. Big Data analytics is a prime part of the innovations happening in the Insurance Industry. It provides an aid to the Insurance Industry by helping them take the right decision with intuitive insights. It epitomizes what an Industry can do if offered with the accurate insights.As the Insurance Industry is data dependent, Big Data helps by providing abundance information collected from various sources such as call centre data, customer e-mails, social media, user forums and user behavior while logged into the insurers’ sites. 

The Big Data can help in risk assessment through the predictive modeling. This methodology can help insurers identify whether the drivers are likely to be involved in an accident or have their car stolen by combining the behavioral data with the road conditions. In addition, when a customer intends to buycar insurance, the insurer can acquire information from which they can calculate the safety levels for driving in the buyer’s proximity and can also know his prior driving records.

Big Data has also proven itself as a helping hand to the Insurance Industry in cracking down on fraud. Through Data Management and Predictive modeling, it is now possible to improve fraud detection and criminal activity. Here, the variables in every claim are matched against the profiles of past claims which were fraudulent. If such a match is found, the claim is pinned for further investigation.

Another important usage of Big Data is that it plays an important role in automating simple processes such as compliance check, data entry or repetitive tasks. With an increase in the usage of big data technologies, these simple tasks even opened ways to more complicated skills such as loan underwriting, reconciliation, assessment of property, verification of the claim, receiving customer insights and fraud detection. With a move towards more intelligent automation, insurers can now save both time and money with the help of machine learning which trains data to improve algorithms and predictive analysis.

Big Data helps in acquiring an absolute understanding of customer behaviors, habits and requirements from various sources for insurers to help them predict future behaviors, to offer suitable products and to identify the correct segmentation. After a complete insight into the customer behavior, insurers became more efficient in offering targeted products and services thus indirectly helping in marketing. Through this collected data one can offer personalized services and products such as lower-priced premiums, contacting the customer for special offers when they are likely to leave or even offering a family package.

Gaining customer insight with big data analytics provides predictions about when a customer is likely to leave or helps in shaping a customer’s policy. Moreover, it helps develop trusted relationships and engaged customers with the correct information. Also, it can help the organizations answer frequent questions asked by the customer to the organization. As a result of this strategic learning, insurers are able to achieve positive outcomes such as solving customer problems in real-time with the right approach and also help them in focusing on improving customer experience.

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