The Insurance industry is the least bothersome industry where customers stay with the product for a fixed amount of time ranging from maximum 3-10 years. There are still millions of uninsured people which leave the insurers baffled. Analytics comes to the rescue of insurers because there is a goldmine of information that is generated by an individual who is insured via a term plan. That particular individual goes through multiple changes in his life like employment positions, personal milestones like marriage and kids affecting the health and the income parameters. This data can come in handy for the insurance companies.
Loss of Data
Insurance giants are turning to predictive analytics because, via the traditional method of processing data which is dependent on underwriters, a lot of data is lost in the databases. The underwriters evaluate the risk by actuarial data, claims data and use other techniques to evaluate the cost factor. Later, the underwriters evaluate risk, cost, gross and the net premium and the first premium is issued to the customer. There is a humongous amount of data that is not accessible to underwriters because of lack of communication with agents and brokers. The data collected by agents and brokers is restricted from being shared to the third party. Thus, a lot of data is lost.
Rebuilding the Insurance Industry
1) Building Customer Loyalty
Customers nowadays believe in trusted consultants and industries understand the importance of customer centricity. Data analytics and intelligent management platforms powered with smart dashboards allow agents to get a 360-degree overview of each customer's portfolio and provide actionable insights based on previous insured customer data, building customer loyalty.
2) Prevention of Fraud
Insurance data provides actionable intelligence to predict and prevent potential fraud before it happens. Smart Social Media Analytics can scan the social media profiles of a policyholder who reports an accident and seeks a claim but is enjoying a vacation and posting pictures on social media.
3) Premium Pricing
To make predictions for an insurance product, companies have relied on "The Law of Large Numbers”. Through this principle, an experienced driver gets the same amount of premium as a learning license holder. To fix policy prices, insurance companies have taken the route of predictive analytics with actionable insights from the data. Insurers maximize their revenue by analyzing the profitability of policies offered, customizing product offerings, fixing premium policy pricing and improving employee productivity.
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