Driving Insurance Agent Productivity with Mobile and Big Data...
Consumer Insight, Experimentation and Other Winning Strategies for...
Innovation challenges and the Insurance Broker
How IT Transformation is Enabling Nationwide's Digitization
Redefining the Future of IT in Insurance
Murali Natarajan, SVP & CIO, West Bend Mutual Insurance
Mary Kotch, Executive Vice President & CIO, Validus Reinsurance
A Practical Approach to Innovation
Mark L. Berthiaume, EVP, Chief Information Officer & Chief Technology Innovation Officer, The Hanover Insurance Group
Building Towards Tomorrow: Driving Change in Insurance
Mary Kotch, EVP & Global CIO, Validus Reinsurance
Thank you for Subscribing to CIO Applications Weekly Brief
How Insurers can Leverage Data Analytics to Reap Benefits
An insurance company that can correctly predict the needs of prospective customers by analyzing data trends has a much better chance of making a sale than an insurance company that only uses traditional selling methods
Fremont, CA: Insurance companies that have implemented data analytics solutions have seen significant improvements in decision-making, business intelligence, customer conversion, and other areas. The following are the primary advantages of data analytics:
More Leads Generating
In this day and age, every insurer is finding it difficult to compete with the internet. In this scenario, the web's unstructured data serves as an unrestricted source of lead generation. The insurance data analytics of such unstructured data provides one with a deep dive into customer behavior and market opportunities for up-sell and cross-sell.
Customer Satisfaction Improvement
An insurance company that can correctly predict the needs of prospective customers by analyzing data trends has a much better chance of making a sale than an insurance company that only uses traditional selling methods. Existing customer data analysis can also provide prescriptive insights into improving customer satisfaction.
Predicting Accurate Risk for Underwriting
Underwriting is a difficult task for insurers, but it can be made easier with insurance underwriting analytics. For instance, a customer whose data trend predicts a lower risk profile would pay a higher premium than a customer whose data trend predicts a higher risk profile.
Allowing for Business Growth
One of the most important aspects of the insurance domain is quantifying risk levels, which is best accomplished through the acquisition and analysis of user data. As a result of its ability in predictive analysis of big data, Insurance data analytics serves as a growth engine for insurance companies.