GenAI for enhanced outcomes, while protecting the downside
VALUE TO CUSTOMERS
Parallelly, key risks need to be guarded against/ mitigated
Speed to outcome
Convenience, ease of business
Superior experience
• Faster claims
• Intuitive process • Information availability • Reduced consumer • complaints, load on customer service.
• Increased trust index • Higher Member NPS
VALUE TO ENTERPRISE
Risk Mitigation • Data privacy & security • Compliance/ legal hassles • Reputation risk
Day-to-day efficiencies
Process Redesign
Better financials • Combined ratio • Lower loss ratio (More accurate risk assessment )
• Standardization • Improved humans accuracy • Lower Attrition
• Higher productivity (# Quotes/UW,
reduction (Expense cost)
#Claims/Adjustor, etc.)
• Reduced time load
Fig 1. Value assessment framework
Setting up an operating model for scaled success A well-defined and scalable operating model is essential to successfully integrate GenAI into insurance operations. The model below (Fig. 2) outlines how the collaboration between the GenAI Center of Excellence (CoE) , GenAI core team, and GenAI governance council ensures consistency and efficiency while maintaining strong governance. This operating model focuses on three key areas, namely:
1. Foundation:
Assessing the enterprise's readiness for GenAI initiatives and establishing the necessary infrastructure.
2. Operational:
Offering oversight and strategic direction for GenAI projects, which involves using expansive language models and agreement on GenAI tools and technologies. The CoE and the core team foster collaboration among data science teams, helping to spread the technology more widely and implement solutions efficiently.
3. Functional:
Aligning GenAI efforts with organizational goals, assessing risks, and upholding responsible AI standards.
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