Performance Constraints
High computational demand during peak reporting periods pushed the system to its limits.
Modernizing Convex Insurance with Scalable
AWS Cloud and Data Architecture
Client Overview
Convex is a global specialty insurer and reinsurer founded to serve the complex needs of commercial clients and brokers with innovative, dependable risk solutions. With experienced leadership from across the industry and operations spanning Bermuda, London, Europe, and the US, Convex combines deep underwriting expertise with a strong financial foundation to deliver tailored insurance and reinsurance products across a wide range of specialty markets.
Business Objective
A global insurance and actuarial organization was facing increasing pressure on its capital modeling environment. As regulatory requirements intensified and model complexity grew, the existing infrastructure struggled to keep pace with peak reporting cycles, leading to operational strain and performance limitations during critical periods. The organization needed to remove infrastructure bottlenecks that were slowing actuarial reporting, improve system stability during peak demand, reduce infrastructure costs during off-peak hours, and establish a scalable, future-ready foundation to support long-term business growth.
Industry
Insurance
Platform
AWS
Service
Cloud Infrastructure Modernization
Nick Owen
CTO
We are thrilled to share our positive experience with NeosAlpha. Initially engaging them for their...
Read More Challenges
High Fixed Costs
Significant infrastructure investment was required year-round, even when utilization was low.
Operational Risk
A centralized environment created exposure to downtime during heavy processing cycles.
Limited Agility
Scaling required manual intervention and infrastructure changes, slowing responsiveness to business needs.
Complex modeling workloads stuck on rigid infrastructure? Move to on-demand scaling and significantly reduce compute spend with our approach.
Book a Free Discovery CallSolutions
Elastic Compute Scaling
We implemented a dynamic compute framework on Amazon Web Services that automatically scales resources based on modeling demands. This ensures peak-period performance without maintaining expensive, underutilized infrastructure during quieter cycles.
High-Performance Shared Storage
To support intensive modeling workloads, we introduced a centralized, high-speed storage layer that enables consistent, reliable data access across all compute resources. This improved processing efficiency while maintaining data consistency across parallel runs.
Managed Data Services
We transitioned critical modeling and operational data into a secure, managed database environment. This strengthened data integrity, reduced administrative overhead, and enhanced overall system reliability.
Automated & Repeatable Deployment
The infrastructure was built using an automated deployment framework, allowing new modeling environments to be provisioned quickly and accurately. This provides agility for regulatory updates, testing scenarios, and business expansion initiatives.
Results
Improved Reporting Reliability
Capital modeling runs now execute without infrastructure-related interruptions, even during peak-demand periods.
~45% Reduction in Compute Costs
Intelligent scaling eliminated unnecessary infrastructure expenses during nights, weekends, and low-activity periods.
Faster Actuarial Turnaround
Parallel processing capabilities significantly reduced model execution time, accelerating regulatory and management reporting.
Enhanced Operational Resilience
The new architecture minimizes single points of failure and ensures continuity of critical modeling workflows.
Technology Stack
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