Data Science Use Cases in Insurance

Data Science teams are now an integral part of insurance organizations as a huge number of insurers have embarked on the journey of digital transformation in recent years. InsurTech's are taking advantage of data science to learn the ways in which they can use this data to improve the business.

Apparently, data science can make enormous contributions to the insurance industry, may it be in acquiring new customers, developing personalized products, calculating the risks and many more.

Here is a short infographic on the major Data science use-cases in the insurance industry.

Fraud Detection:
Where data science can compare the behavior patterns of customers to those that pre-configured patterns that indicate fraudulent activities.

Price Optimization:
Insurers can now quote the premiums dynamically after understanding the customer's price sensitivity from the policy documents.

Customer Segmentation:
For engaging with customers on a personal level, insurers can now segment their customers based on a wide range of parameters.

Personalized product development
With the help of data scientists, we are now able to identify the needs and lifestyle of customers and offer them more personalized policies that will suit their lifestyle and needs. This type of policy can be easily sold and contributes to the overall revenue of insurance organizations.

Policy Recommendation Engines.
Instantly recommend products and services to customers after studying their behavior patterns.

Risk Assessment
Analyze the risk of loss in claims payout for each type of policy and adjust the pricing accordingly for a more profitable business. If insurance companies keep selling high-risk policies for low premium amounts then it will ultimately result in losses.

Claim Segmentation and Triage Analysis:
This process deals with analyzing the complexity of each claim and assigning a suitable adjuster to handle each claim. Less complex claims will be processed in fast track and high complex claims are assigned to experienced adjusters.