SIFT_Analytics_Data_Driven_Insurance

In a data-driven insurance model, companies leverage their data to develop innovative solutions, automate their process, and create value-added services. This session is specifically designed to address the challenges faced by insurance companies in achieving these objectives.

📊 Eliminate Manual Reports and IFRS17 Processes

  • Challenges: Reports such as compliance and IFRS 17 processes involve tedious and manual tasks performed daily.
     
  • Approach: Automate these reports and processes to ensure accurate results, eliminate human errors, and simplify variance root cause analysis and amount validations.
     
  • Impact: The automated workflow becomes a repeatable process that generates final outputs more accurately and efficiently.

💡 Insurance Sales Optimization

  • Challenges: Agents face several challenges in identifying and closing deals with potential customers, including a deep understanding of customer-specific needs based on their unique profile and stage of life, offering personalized advice, and recommending the most suitable insurance products to them.  

  • Approach: Leveraging advanced data analytics to transform the way agents operate, the focus is on three key areas: customer segmentation, predictive analytics for customer identification, and product coverage recommendations.

  • Impact: By recognizing customers as individuals rather than mere market segments, agents are empowered with data-driven decision-making, gaining actionable insights and delivering timely, relevant products. With higher precision to identify the right customer and empowered by product recommendation mechanisms, agents can focus more on servicing the 20% of high potential customers and generate 80% of the Analyze First Year Premium (AFYP).