Insurance

Modern data, software, and AI solutions for regulated insurance environments.

Insurance organizations operate in environments defined by strict regulatory and compliance requirements, complex legacy core systems, high operational dependency on correct data, and increasing expectations for speed and transparency.

Acosom works with insurance providers to design, build, and operate data platforms, operational software, and AI-enabled solutions that improve insurance processes — while respecting regulatory, security, and stability constraints.

Insurance IT landscapes are shaped by long-lived systems and processes that prioritize stability and correctness.

What Insurance Organizations Gain

When evolving capabilities safely within regulatory constraints.

Usable Core Insurance Data

Legacy insurance data transformed into accessible, governed data products that support modern processes without disrupting core systems.

Modern Operational Software

Workflow-driven applications used directly by insurance clerks and operations teams, improving efficiency and partner collaboration.

Responsible AI Adoption

AI for document classification, fraud detection, and decision support — explainable, auditable, and aligned with regulatory expectations.

Enforced Data Governance

Clear data ownership, access control, policy enforcement, and auditability without blocking innovation.

Evolutionary Modernization

Incremental evolution from batch to event- and stream-based patterns without breaking stability.

Long-Term Platform Ownership

Platforms designed for internal ownership, enablement, and long-term operability — not permanent external dependencies.

Insurance Success

Real-Time Insurance Data for Healthcare Partners

A large insurance provider needed to modernize data integration and operational processes. Coverage verification relied on batch processing and manual checks, causing delays for healthcare partners. We established a platform for modern data integration enabling teams to define pipelines using declarative and programmatic approaches, extracted data from legacy relational systems, and fed downstream processes in near real time. Healthcare partners could now receive live insurance coverage updates immediately.

Result: Coverage status became available in real time, dramatically improving operational efficiency for both the insurer and healthcare partners. Teams could define and deploy new data pipelines safely. The platform evolved from batch to event-based patterns without disrupting core systems. Data platforms, integration patterns, and governance directly improved insurance operations.

Discuss Your Insurance Needs

Understanding the Reality of Insurance IT

Insurance IT landscapes are shaped by long-lived systems and processes that prioritize stability and correctness.

Common characteristics include large relational core systems, batch-oriented integration patterns, complex data models, and strict governance and audit requirements.

While these environments are reliable, they often struggle to support real-time decision-making, efficient collaboration with partners, and modern, data-driven processes.

Our work focuses on evolving these environments incrementally, without disrupting core systems.

Typical Challenges We See in Insurance

Recurring challenges that require architecture, governance, and execution — not isolated tools.

Making Core Insurance Data Usable

Legacy insurance data is trapped in complex relational models. Making it usable outside core systems without breaking stability requires careful integration patterns and governance.

Modernizing Data Integration

Evolution from batch to event- and stream-based patterns while maintaining reliability, correctness, and auditability.

Supporting Operational Teams

Insurance clerks and operations teams need better tooling, workflow-driven applications, and partner-facing integrations.

Introducing AI Responsibly

Using AI for document classification, fraud detection, and decision support without violating regulatory expectations or losing explainability.

Enforcing Data Governance

Defining data ownership, access control, policy enforcement, auditability, and controlled duplication where required by regulation.

Operating Platforms Reliably

Long-lived platforms that evolve over time, enable internal ownership, and provide self-service where it creates leverage — not chaos.

How We Support Insurance Providers

Our work with insurance organizations spans multiple, repeatable solution areas.

Enterprise Data Platforms & Integration

Integration of legacy insurance systems, evolution from batch to event- and stream-based patterns, and scalable access to insurance data for internal consumers. Making core insurance data usable outside legacy systems without breaking stability.

Operational Software for Insurance Processes

Tools used directly by insurance clerks and operations teams, workflow-driven applications, and partner-facing integrations (e.g., healthcare providers). Software that improves insurance operations while respecting existing processes.

AI for Insurance — Used Responsibly

Document classification and analysis, fraud and anomaly detection signals, AI as decision support rather than autonomous decision-making, and explainable, auditable AI usage aligned with regulatory expectations.

Data & AI Governance

Definition of data ownership and responsibilities, access control and policy enforcement, auditability and lineage, and controlled duplication where required by regulation. Governance that enables innovation rather than blocking it.

Platform Design & Operating Models

Long-lived platforms that evolve over time, internal ownership and enablement, self-service where it creates leverage, and clear operating models that support both stability and innovation.

Modernization & Evolution

Incremental evolution of legacy-heavy landscapes, migration from batch to real-time patterns, and modernization strategies that respect operational reality and regulatory constraints.

How Our Services Fit Insurance

Depending on the organization, we support insurance providers through different aspects of their technology journey.

Consulting: Platform strategy, governance models, operating concepts

Engineering: Implementation of platforms, software, and AI solutions

Managed Services: Reliable operation under defined support models

Training & Enablement: Enabling internal teams to own and evolve systems

Within insurance organizations, we often work with data and integration teams, platform and architecture groups, insurance operations and partner teams, and compliance and security functions.

Frequently Asked Questions

How do you handle insurance-specific regulatory requirements?

Regulatory compliance is built into our approach from the beginning, not added later.

Our approach:

Systems are designed with auditability and traceability from the start
Data flows are documented and explainable
Access controls and policy enforcement are built into platforms
AI outputs are reviewable and explainable
We collaborate directly with compliance and risk teams

We understand that insurance operates under strict regulatory oversight and design accordingly.

Can you integrate with our legacy core insurance systems?

Yes. We have extensive experience integrating with complex legacy insurance systems.

Our approach:

Clean integration that respects core system stability
Proper handling of complex relational models
Data lineage and traceability maintained
Safe decoupling for downstream consumers
Evolution from batch to event-based patterns where beneficial

We understand that core insurance systems are not experimental playgrounds — integrations must be reliable, correct, and maintainable.

How do you use AI in regulated insurance environments?

We use AI as decision support and assistance, not as autonomous decision-making.

Our approach:

AI is used for classification, anomaly detection, and decision support
Outputs are explainable and reviewable by humans
Final decisions remain with authorized insurance professionals
Usage aligns with regulatory expectations
Models are auditable and traceable

This enables practical AI adoption while maintaining compliance, explainability, and trust.

Do you only work with large insurance companies?

No. We work with insurance organizations of different sizes and types.

Who we work with:

Large insurance providers
Regional insurance companies
Specialized insurance organizations
Insurance operations and partner teams

The size matters less than the criticality of systems, regulatory constraints, and operational requirements.

What if our systems are mostly batch-oriented and on-premises?

That’s not a problem. Many insurance organizations operate with batch-oriented, on-premises systems.

We have extensive experience with:

Legacy relational core systems
Batch-oriented integration patterns
On-premises and hybrid architectures
Incremental evolution to event-based patterns
Respecting operational stability while modernizing

We adapt to your operational and regulatory reality, not the other way around.

Can you help us modernize without disrupting operations?

Yes. Our approach is evolutionary, not disruptive.

Our approach:

Understand existing systems and their operational criticality
Define clear modernization scope and boundaries
Evolve in controlled, incremental steps
Maintain parallel operation where necessary
Ensure auditability and rollback capability
Never compromise operational stability

In insurance, modernization must be planned, tested, and executed with full awareness of business and regulatory impact.

Ready to evolve your insurance capabilities safely and sustainably? Let’s talk about your specific challenges.

Discuss Your Insurance Needs

Insurance

What Insurance Organizations Gain

Usable Core Insurance Data

Modern Operational Software

Responsible AI Adoption

Enforced Data Governance

Evolutionary Modernization

Long-Term Platform Ownership

Real-Time Insurance Data for Healthcare Partners

Understanding the Reality of Insurance IT

Typical Challenges We See in Insurance

Making Core Insurance Data Usable

Modernizing Data Integration

Supporting Operational Teams

Introducing AI Responsibly

Enforcing Data Governance

Operating Platforms Reliably

How We Support Insurance Providers

Enterprise Data Platforms & Integration

Operational Software for Insurance Processes

AI for Insurance — Used Responsibly

Data & AI Governance

Platform Design & Operating Models

Modernization & Evolution

How Our Services Fit Insurance

Frequently Asked Questions

How do you handle insurance-specific regulatory requirements?

Can you integrate with our legacy core insurance systems?

How do you use AI in regulated insurance environments?

Do you only work with large insurance companies?

What if our systems are mostly batch-oriented and on-premises?

Can you help us modernize without disrupting operations?

Ready to evolve your insurance capabilities safely and sustainably? Let’s talk about your specific challenges.

Acosom is a Beconn partner

How to Effectively Test Flink SQL Scripts Using Unit & Intregration Test

IoT Streaming Analytics with Kafka, Flink, Druid and Superset