The availability of large data volumes is fueling the importance of quality analysis and insight in in the insurance business. As computing power grows, advanced analytics and machine learning methods are accelerating this trend and enabling stakeholders across the business to make better, data-driven business decisions.
The EY Data Science in Insurance Survey explores the current state of analytics strategy implementation in insurance companies and examines trends in data science and advanced analytics in the industry. The survey covered all types of insurance companies (life insurance, non-life insurance, health insurance and reinsurance) and was structured along four dimensions:
- General perception of data science in the insurance industry
- Data science functions
- Use cases in data science
- Objectives and challenges of advanced analytics
For the purposes of the survey, advanced analytics is broadly defined as the use of machine learning methods along the insurance value chain.