Home > Insurance Analytics


Insurance is a contract entered between two parties, i.e. the company assuring in the contract of insurance to compensate is known as insurer / assurer. While the person to whom such assurance is given is known as insured / assured. In this contract, the insurer is liable to compensate for the specific loss to the insured who has paid regular consideration, i.e. an insurance premium.

Insurance, being a data rich industry and a high customer life time value business, can gain immensely from real-time analytics. With much better access to third-party data from a wide variety of sources, insurers can pose new questions and better understand many different types of risks. Analytics in Insurance is tricky because of the huge volume of data that is generated in real time that directly impacts the business.

Insurance companies can use Analytics for

  • Making performance improvements in existing data warehouse environments
  • Detecting fraud
  • Combining customer channels
  • Optimizing call center workload
  • Using telematics data to derive prescriptive and predictive value
  • Leveraging cross-sell and up-sell potential
  • Improving sentiment analysis to improve customer service
  • Utilizing social media to introduce new products and services
  • Closing the loop between pricing risk and claims
  • Leveraging external data for more accurate pricing
  • Enhancing intranet search capabilities
  • Creating comprehensive customer satisfaction surveys