The Digital Underwriting Survey reveals the important and rapid evolution that is proceeding within underwriting.
Digital underwriting is not defined solely by the latest technology, the greatest degree of automation or the largest data volumes – though those components are vitally important. A more promising vision involves greater value creation for the business based on expanding roles, new capabilities and a powerful human-machine combination at the heart of a new kind of underwriting organization. In this sense, “digital” is as much about shifting the mindset or culture as it is about adopting a set of software tools. Results from EY’s Digital Underwriting Survey demonstrate how insurers are moving forward in pursuit of such a vision.
The Digital Underwriting Survey looked at 12 different technologies and revealed that many insurers remain in the early stages of their transformation journeys. While great strides have been made with mature technologies, most solutions involving emerging technologies are in the pilot or proof-of-concept phase.
- Predictive analytics
- Big data capabilities
- Underwriting trading platforms
- Automated portfolio management
- Artificial intelligence (AI)
- Machine learning
- Semantic web
- Image and video analysis
Key themes emerging from the survey
- Predictive analytics, big data, underwriting trading platforms and geographic information systems (GIS) are the most mature technologies currently being adopted.
- Blockchain, robotic process automation (RPA) and sensor-based technologies are all high priorities for the future, with organizations planning to commit significant resources.
- There is a strong need for longer and closer monitoring time of early stage investments and the potential need for more rigor in business case development.
- Insurers and brokers agree that underwriting and pricing capabilities are the most important and potentially valuable in terms of future technology investments.
- Actuarial has benefited the most from predictive analytics and machine learning, while policy processing has been the focus of RPA initiatives.