Tuesday, 21 November 2017

Importance Of Analytics In Decision Making In Insurance Industry

Insurance industry over the past few decades has faced a lot of challenges due to the worsening economic conditions which have affected their growth as well as insurance revenue. Along with this external factor, there are many intrinsic problems like lousy pricing, inability to check and control frauds, etc. due to which insurance companies are under tremendous pressure reports www.forbes.com. In all this gloom comes analytics as a potent tool to ease decision making.
In any industry decision making is based on data, when you have a large set of data you can make a decision which is researched and well informed. Thus, you can make better decisions in processes like pricing, marketing, customer relation, etc. With a significant amount of data at your disposal, insurers with the help of analysts can take better decisions, below are the ways analytics helps:

Cost: A major influential factor in deciding on the costs of operation is the actuarial and underwriting expenses. Traditionally the price risk involved in the underwiring involved analysis based on historical data which was not foolproof. However, with the advent of analytics, the actuaries can utilize multi variants to analyze and come up with estimates keeping a futuristic approach.

Fraud Analytics: The most significant expenditure for an insurer is claims. A substantial portion of the money earned on premium is spent on payouts to claims. The technique used to detect fraud was manual, and there were a lot of disadvantages like inaccuracy as well as being time grabbing. But with the advent of digital technology, fraud analysis has also evolved, and sophisticated solutions for analyzing fraud has come up. Some of the solutions make use of analytics in geospatial, social media, loss-padding, etc. The advantages of using fraud analytics are:
Detection of claims which are fraudulent.
False positives can be reduced.
Subrogation recovery can be increased

User analytics: Insurance models used for analyzing customer data was not very personalized, it was a one fit solution for all. That meant that irrespective of the need for the customer products were pushed to users and hence very few buyers for those products. But with the help of analytics, insurance companies can serve customers better by providing customized products and thereby more likelihood of a customer buying it.
Another advantage of analytics is the prediction. By historical analysis of data, you can predict the customer behavior and hence make acquisitions by looking into the prospect of converting each lead to a prospective customer along with considering the potential for future sales. 
Retention of existing customer is quite a challenge for insurers as more companies are coming into the market with better offers. Customer analytics can be utilized to retain customers when their policy is about to lapse. The data provided in this model can also calculate clients who add value and thus increase profits. Targeting such customers will improve your profitability than pursuing customers who do not add value. Companies can achieve earnings by using this retention model to convert lapsed policy to an active one.

Many insurers are of the opinion that using analytics can be a massive investment regarding infrastructure and software, but many open source tools can be used based on your business needs.

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