9:00 am Chair’s Opening Remarks
9:10 am Developing a Culture of Analytics: Building Trust, Gaining Buy-In, Changing Mindsets
Synopsis
• Building the business case for investment in new analytics capabilities
• Taking non-technical staff beyond the surface level understanding of analytics capabilities to communicate and sell its true value
• Engaging leadership and clients to build trust in new tools, models and outputs
• Overcoming cultural barriers to change across teams, functions and regional offices
• Utilizing analytics as a catalyst to refocus insurance around customer needs
Change Management & Adoption Strategy
9:50 am Panel Discussion: Benchmarking Analytics Applications: Identifying and Prioritizing Opportunities to Drive Decision-Making
Synopsis
• Identifying and reviewing the different analytics applications adding value to the
insurance industry
• Assessing business needs to prioritize opportunities
• Comparing the quick wins from the longer-term rewards
• Setting short and long-term goals while recognizing realistic time frames and
required investments
• Where next? Translating successful analytics to new applications across the
insurance value chain
10:30 am Morning Refreshments & Speed Networking
Synopsis
This Speed Networking session is the ideal opportunity to meet other industry
leaders experiencing similar challenges and day-to-day obstacles to advancing
analytics. Take this opportunity to share experience
Collaboration, Teams & Skill Development
12:00 pm Panel Discussion: Embedding Analytics into the Heart of Business: Which Organizational Structure Works Best?
Synopsis
• Who should be involved in leading the initiative of data analytics?
• Protecting and insulating analytics teams vs integrating them within business and
IT functions: which is the best approach?
• Comparing reporting lines for analysts: Data, IT, Finance, Claims, Marketing etc.
• Evaluating the necessary structural differences of analytics teams in small,
medium and large organizations
• Considering where data scientists should sit within the organizational structure
• Interconnecting national and international teams
12:40 pm Lunch
1:40 pm Fostering Collaboration to Achieve an Enterprise-Wide Approach to Analytics
Synopsis
- Establishing core principles for a successful adoption of Data Analytics solutions in an insurance company
- Using the needs and requirements of the business as the starting point for designing and implementing Data Analytics solutions
- Integrating the Data Analytics solutions into the insurance business processes and value chain
- Bridging the gap between Data Analytics expertise and business acumen
- Educate and enable the decision makers across the organization to correctly interpret results coming from Analytics solutions
Achievements and Challenges to Date
2:20 pm Creating an Artificial and Human Intelligence Center of Excellence to capture the Value of Data Science and AI
Synopsis
• Exploring how to design, build and run a Center of Excellence to create and capture value
• What technology, cost and time investment is needed for successful results?
• Embedding data science into claims, pricing and actuarial and customer engagement processes to become intrinsic to everyday business
• Discovering how Rimac Seguros has capitalized on its AI Center of Excellence to build out a new analytical suite for the insurance industry
3:00 pm Afternoon Refreshments
3:20 pm Use Case 1 – Talent Analytics for Improved Human Resources
Synopsis
• Exploring how to apply predictive and workforce analytics to your organization for improved talent management
• Harnessing the power of big data and advanced analytics to shift from reactive to proactive HR processes
• Informing talent decisions and defining business requirements and priorities through human capital analytics and workforce data insights
• Understanding where to source data and what technology requirements are necessary for successful analytics
Use Cases – Round 1
3:50 pm Use Case 2 – Leveraging Data Analytics for Advanced Budgeting, Forecasting & Pricing Models
Synopsis
• Learning how a broker have employed data analytics to enhance their pricing
• Discovering which technology, tools and software facilitated this project
• Examining the challenges faced by brokers when utilizing data to inform decision-making
• Empowering the consumer to choose their own coverage through a platform powered by analytics
• Leveraging data to deliver personalized ‘tailor-made insurance’
4:20 pm Q&A with Use Case Presentation Speakers
4:40 pm Chair’s Closing Remarks
5:00 pm End of Day One
11:20 pm Designing and Growing an Analytics Team: Training, Recruitment & Retention
Synopsis
• Reviewing the core skills and ideal mix of players required for an analytics team:
Analysts vs Modellers vs Data Scientists vs IT
• Aligning team design within wider business roles and capabilities
• Exploring when and how to scale analytics initiatives in order to remain agile as
business requirements change
• Developing recruitment and retention strategies: Sourcing data scientists in a
highly competitive market
• Comparing internal vs external skill development programs to ensure training is
time and cost effective
• Evaluating two training approaches: how can Analytics work for Business and how
can Business work for Analytics