The ever-changing challenges that the insurance industry faces, has made it imperative for insurers to leverage the powers of data and analytics. The valuable insights derived from analyzing data propel insurance companies to find a solution to business problems. Analyzing structured data related to policyholders, and unstructured data from different sources, including social media, aid insurers to analyze the risks involved in insuring an individual who has opted for an insurance policy. This is also necessary for deciding the premium to be charged.
In addition, Big Data and analytics have also profoundly affected customer insights, claims management, and risk management. Here are five ways Big Data has transformed the insurance industry:
1. Standing out in the crowd – The competition prevalent in the insurance industry makes it important for every insurance company to define and prove its efficiency over its competitors. This can be ensured offering their products at a lesser price, without compromising on impeccable customer-service. Big Data and analytics help insurers to simplify the business processes, and meet changing regulatory requirements.
2. Streamlining business processes – Big Data helps the insurers offer policy recommendations that not only suit the interest of customers, but also serve the best interests of the company. This is possible only through data analysis.
3. Get valuable insights on customers – As customer needs and preferences frequently change, it poses a constant challenge for insurance companies to keep a track of it constantly. Big Data aids insurers in understanding and predicting customer behavior, effective in customer acquisition and retention. This makes it possible for insurance companies to develop products to suit the ever-changing tastes of their customers and ensure smart insurance distribution.
4. Managing claims to identify fraud – The insurance industry often incurs heavy losses due to fraudulent practises, with almost $80 billion being the estimated figure for fraudulent claims. Predictive analytics helps insurance companies address the rise in such claims, analyze data from internal sources, and identify applicants with a greater propensity to resort to fraudulent practises. They can also use data mining to keep a tab on digital channels through social listening to detect fraudulent behavior.
5. Managing risk – Big Data and analytics help insurers in formulating policies, especially policies for natural catastrophes, keeping in mind policy conditions, historical data, and such other technical data. The process of insurance distribution becomes comparatively streamlined when insurance companies are able to decide on a catastrophe policy on the basis of accurate Big Data like the residential address, and other important factors, rather than merely the city or state. Big Data solutions can automatically update their pricing models for efficient insurance distribution.