Can Big Data Benefit the Insurance Sector?

By CIOReview | Tuesday, June 11, 2019

FREMONT, CA: The insurance sector has always been quite conventional; nonetheless, the embracing of new technologies is not just a contemporary trend but a requirement to continue the competitive pace. In the present digital era, Big Data technologies assist in processing large amounts of information, increase in workflow efficiency, assessments of risks, and reduction of operational costs.

Modern civilization is constantly producing striking amounts of real-time data. Processed by Artificial Intelligence, it becomes a valuable source of information critical for most industry models, including insurance. The insurance industry has always been based on data analysis―accident figures, policyholder’s private data, as well as third-party resources. The data received from these multiple sources help to categorize citizens into different risk categories, based on losses and expenses. The swift progression towards the digital society unlocks new resources of information that can be utilized to generate an intricate behavioral pattern for each customer and precisely conclude his or her risk situation.

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Role of Big Data in the Insurance Industry:

•  New distribution models: virtual assistants and Chatbots that augment customer interactions and formulate marketing more targeted.

•  Process automation: it substitutes physical labor and improves the competence of the in-house workflow.

•  New propositions: it facilitates the creation of alternative business forms such as peer-to-peer notions or digital insurers.

Several Big Data Solutions for Insurance:

Customer Acquisition:

Every customer generates massive amounts of data via emails, social media platforms, and feedback, which produces precise information about their choices than any survey or questionnaire. By analyzing such amorphous data, insurance firms can augment their efficiency.

Customer Retention:

Based on consumer activity, algorithms can recognize early signs of customers’ dissatisfaction. By using these assembled insights, insurers can concentrate on solving the client’s issues by changing the pricing model.

Risk Assessment:

Insurers were always concentrated on the authentication of customer information while assessing the risk. Big Data can boost the effectiveness of this process by deploying predictive modeling to foretell possible issues based on the client’s data.

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Cost Reductions:

Big Data can computerize many labor-intensive processes, making them more competent. In a competitive setting, the reduction of the costs on handling claims and governance will result in lower premiums and help in attracting new clients. For instance, life insurance based on Big Data can be applied for shaping pricing models that will both fit consumers’ budgets and guarantee profit for companies.