This is a paid press release. Direct any questions to the press release distributor.
Zinnia and Snowflake Team Up to Deliver Real-Time Insurance Analytics and AI
Zinnia announced a new integration with Snowflake's AI Data Cloud to bring real-time analytics and AI-driven decisioning to life and annuity carriers. The partnership blends Zinnia's insurance know-how with Snowflake's data and AI platform to speed up decisions while meeting enterprise security and scale needs. The goal: move from batch reports to timely, trusted insights across the policy lifecycle.
What this means for insurers
- Faster decisions: Underwriting, claims, and service teams can work from fresher data and model outputs, not next-day reports.
- Unified data: Core policy, distribution, claims, and servicing data can be brought together for a single view of customers and operations.
- Operational efficiency: Less time stitching spreadsheets, more time acting on signals that matter to loss ratio, expense ratio, and growth.
- Enterprise-grade controls: Security and scalability are built to meet large-carrier standards.
High-value use cases to target first
- Underwriting and new business: Real-time risk indicators, instant eligibility checks, and pricing support at point of sale.
- Claims: Triage and severity forecasts, fraud risk flags, subrogation likelihood, and cycle-time reduction.
- Distribution and retention: Lead scoring, producer performance insights, lapse prediction, and next-best action for service teams.
- Actuarial and finance: Near real-time experience monitoring, assumption tracking, and early variance alerts.
- Compliance and governance: Audit-ready data lineage and controls across sensitive fields.
Implementation playbook
- Pick 2-3 decisions where minutes matter (e.g., straight-through processing, first notice of loss, lapse saves). Define the KPI lift you expect.
- Map the data. List sources (core admin, CRM, claims, third-party), how often they refresh, and quality gaps. Close the highest-impact gaps first.
- Operationalize models. Set thresholds, handoffs, and feedback loops so model outputs change actual workflows-not just dashboards.
- Govern responsibly. Establish model monitoring, bias checks, and access controls before scaling use beyond pilots.
- Upskill your team. Train underwriters, claims leaders, and ops on reading signals, not just viewing charts.
Key details
Announcement date: January 20, 2026, Greenwich, Conn. Companies: Zinnia (life and annuity technology) and Snowflake (AI Data Cloud). Objective: deliver real-time analytics and AI solutions with security and scalability for insurers.
Learn more about the companies involved: Zinnia and Snowflake AI Data Cloud.
Next steps for your team
- Run a 60-day pilot on one workflow with clear KPIs (quote speed, bind rate, claim cycle time, loss ratio).
- Create a shared scorecard for business, data, and compliance so decisions move faster with the right safeguards.
- If you need structured upskilling on AI for specific roles, explore AI courses by job to level up adoption across underwriting, claims, and operations.
Disclosure: This is a paid press release. Direct any questions to the press release distributor.
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