Skip to content

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

  • Sergio Gomez Managing Director, Latin America – Analytics, Reinsurance Solutions, AON

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

  • Miguel Paredes Vice President of Artificial Intelligence and Data Analytics, Rimac Seguros y Reaseguros

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

  • Diana Parrao Deputy Director Technical Benefits, Lockton Companies

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

  • Keith Lawler Managing Director, Reinsurance Solutions, Aon Latin America

5:00 pm End of Day One

11:20 pm Designing and Growing an Analytics Team: Training, Recruitment & Retention

  • Alvaro Ortiz Director of Data and Analytics, Insurance Office of America

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