Common Use Cases
As new innovation and applications for using advanced analytics emerges in all types of product lines and business functions, it is important to develop, test, and adopt the proper validated predictive and optimization models. As data sources and technologies become mature, the competitive advantage will go to insurance firms that incorporate consistent and predictable data science life-cycles in their approach.
By leveraging big data technologies, such as Hadoop, ingesting real-time data, external data, and usage-based information, insurers can pose new questions and better understand many different types of risk, customer behaviors, and serve key clients more effectively.
We can help create lasting improvements in analytics modeling that will also enable firms to underwrite many other emerging risks that are underinsured, including those related to cybersecurity, health, regional, and industry-wide business interruption stemming from climate and natural disasters.