• Overcoming one of the biggest challenges facing the industry – managing expectations. • Creating a realistic expectation of what can be achieved. • Ensuring non-data people are educated on where data efforts should focus.
• Ensuring people are able to make a decision they need to. • Allowing people to see the value that data can have in their role. • Creating data advocated in each business unit.
• Given the relative maturity of insurance, is the CDO role necessary? • Should the CDO be perform a different role in insurance to other industries? • Making the role a long term function rather than a transitional position.
• Creating a platform to show the value offered by data-driven insight. • Ensuring that all projects have clear RoI to ensure continued investment in analytics projects. • Working with business units to identify the key drivers of a project in the planning stage.
• Identifying the challenges of recruiting and retaining top talent. • Discussion on the complementary skillsets required to perform a high-performing team. • Advocating the need for investment of resources to compete with other industries for talent.
• How does a CDO or CEO interact with CEO and other C-level roles. • Interaction between CDO and CUO • Is this different in insurance due, or with organizations with different levels of maturity?
• How can Artificial Intelligence be used to improve current analytics practices? • Is your analytics team mature enough to trust AI? • Does Artificial Intelligence offer real progress for insurance?
• As insurance providers must provide a larger array of products, how can smaller markets be catered to. • Using smaller niches to offer the products that customers want. • Staying ahead of competition by offering unique and bespoke products that remain profitable..
• Advocating data-driven insight over ‘gut instinct’ and hunches. • Ensuring open communication with stakeholders to provide genuine collaboration on data projects. • Understanding the needs of the user to create genuine enthusiasm for data projects from broader organization..
• Using telematics to see how customers act in real time. • Rewarding high value customers and creating bespoke products to improve retention. • Possible challenges around fundamental change in approach bought about by new technology as a disruptive agent.
• Data-enabled startups and tech companies are moving into the space, is Big Data the answer for insurance? • Understanding the products that customers want and providing a seamless experience to improve retention. • Focusing on customer satisfaction as a key indicator of loyalty and driving product development in this way.
• CDAO’s are frequently asked to run multiple projects from multiple stakeholders, but not all can be run simultaneously. • How do you identify where to focus resources? • Understanding the need for projects with short term RoI, and those with longer value propositions
• Reinsurers in particular face challenges from a lack of uniform data, is it possible to create uniform data to make analysis quicker and more effective. • Managing the cost in time and resources of getting data in a position it can be used. • Refocusing traditional systems and processes to support more effective data… Read more.
• No project has RoI if the stakeholder doesn’t use the insight, make sure the hard work doesn’t become wasted effort. • Embedding data insight into how teams operate so projects reach their full potential. • Making that insight is communicated in an effective way for the business user..
• Discussing how new players in the industry are forcing traditional players to reconsider how they should operate. • Does tradition and legacy pose a risk to reacting quickly? • The role of actuaries in acting as data advocates and creating a culture more receptive to data-driven insight.