Modernizing Legacy Insurance Systems with AI and Microservices Architecture

Insurance company transforms mainframe-based core platform and prepares operation for continuous digital scale

A large insurance company faced scale and performance limitations in a legacy environment based on mainframe batch processing. The monolithic architecture hindered the evolution of digital services, increased the response time of operations and restricted the organization's ability to keep up with the pace of transformation in the insurance market.

The challenges: overcoming the limitations of a monolithic batch environment and enabling digital scale

The existing technological environment was heavily dependent on mainframe batch processing, with a large volume of critical business rules distributed in legacy COBOL code.

Among the main challenges were

• Operational scalability limitations in monolithic architecture;

• High response times for processing services;

• Dependence on batch processing to execute critical operations;

• High technical complexity associated with maintaining legacy code;

• Need for modernization without compromising sensitive insurance business rules;

• Preparation of the technological base for continuous evolution oriented towards digital services.

The organization needed to transform its technological architecture while preserving legacy knowledge and guaranteeing operational continuity.

Why Foursys?

Foursys was chosen for its ability to conduct structured projects to modernize critical legacy systems using artificial intelligence and modern microservice-oriented architectures.

Among the main differentials considered were:

• Experience in modernizing COBOL environments on a large scale;

• Strategic application of artificial intelligence in the analysis and transformation of legacy code;

• Specialization in the transition from batch architectures to distributed online environments;

• Ability to implement complete DevOps pipelines;

• Experience in orchestrating applications in Kubernetes environments.

Success factors

Project execution was based on a structured engineering approach that ensured predictability, technical quality and preservation of critical business rules during modernization.

Among the main success factors were:

• Use of artificial intelligence applied to the structural analysis and transformation of legacy code;

• Progressive strategy to replace batch processing with online microservices;

• Implementation of a DevOps treadmill with continuous integration and test automation;

• Orchestration of the solution in a Kubernetes environment to ensure scalability and resilience;

• Maintaining the integrity of business rules throughout the modernization process.

The solution: transformation of monolithic batch architecture into a modern service-oriented platform

Foursys implemented a complete technological modernization strategy focused on replacing the legacy batch model with a distributed architecture based on microservices.

The solution included

• Modernization of the legacy environment using artificial intelligence applied to the analysis and transformation of COBOL code;

• Replacing the monolithic batch system with a scalability-oriented online microservices architecture;

• Implementation of a DevOps treadmill with continuous integration to increase the quality and speed of deliveries;

• Orchestration of the Kubernetes platform to guarantee high availability and operational resilience;

• Structuring a technological base prepared for the continuous evolution of the insurer's digital services.

Results

The modernization of the core platform enabled significant gains in operational efficiency and technological evolution capacity:

• Modernization of 600,000 lines of code;

• Handling of more than 2,000 CopyBooks / DCLGENs;

• Evolution of 450 COBOL files and API methods;

• Significant gains in operational efficiency;

• Significant reduction in service response times;

• Technological base prepared for continuous evolution and expansion of digital services.