Becoming an Insight-driven Insurer
A new approach to data analytics
"Becoming an Insight-Driven Insurer", an inspiring short video, is an introduction to insight-driven insurer (IDI). It looks into how an insurer transform into an IDI and the five building blocks of an IDI. Big data and analytics enable the insurer to improve basic capabilities such as actuarial, underwriting, claims, and customer services. Leveraging data analytics and transforming into an IDI is the key to making an institution a market leader. In this video, several insurance industry experts from Deloitte China will give an in-depth interpretation of IDI from strategic, actuarial and technological perspectives:
- Introduction of IDI
An insight-driven insurer (IDI) embeds analysis, data, and reasoning into the decision making process, every day. Becoming an IDI means figuring out how to scale analytics projects across the organization to drive greater business impact. In our experience, an IDI requires a combination of five essential building blocks and concerted efforts within business strategy, actuarial and IT and other teams.
- Detailed insights of IDI from the five main aspects: strategy, people, process, technology and data
An IDI has five building blocks including strategy, people, process, technology and data. From strategic perspective, setting strategy requires executive sponsors and champions to carefully define their analytics objectives and align the analytics journey with the organization’s broader goals, business plans and win strategy. From actuarial perspective, in terms of people, an IDI needs to identify the champions and develop analytics talent as well as build an analytical culture. Moreover, IDIs need processes to turn data into insight and to act upon that insight. From technological perspective, the organization needs people with the requisite technical skills, a delivery model to disseminate insights across the organization and a structured approach for collaborating with your third-party technology partners to build up a well-thought-out solution architecture. With regard to data, IDIs need to optimize and visualize the current data sets and obtain new valuable data as well as ensure regulatory compliance and carefully consider the ethical implications of how they use their data.