Insurance Legacy System Transformation: 2025 Guide

Mainframes and Common Business-Oriented Language (COBOL) apps still power core insurance systems, but they weren’t designed for real-time orchestration, intelligent workflows, or AI agents. As insurers push toward modernization, these legacy systems block not only speed but relevance itself.

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Replacing them is challenging because they're tightly integrated with numerous interconnected systems. Instead, insurers are adopting strategies like orchestrated layers and API enablement to extend and build upon their existing infrastructure.

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In this article, we’ll cover: 

• Why insurance legacy systems hold companies back
• How insurance legacy system transformation projects succeed (or fail)
• Where platforms like Superblocks unlock real ROI

Let’s start by discussing why insurance legacy systems are hard to replace.

Why are insurance legacy systems so hard to replace?

Insurance legacy systems are hard to replace because they are deeply integrated with every aspect of the business, making any change risky.

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Let’s look at the barriers these entrenched legacy systems create:

Decades of system interdependencies

Over time, insurers layered numerous interdependent processes and databases onto these systems. Replacing one piece risks breaking others. Even simple changes can trigger cascading failures throughout the organization.

Risk of data loss or compliance violations

Older mainframe applications often lack complete documentation after decades of patches and modifications. Much of the system knowledge exists only in the minds of veteran developers. A poorly planned replacement could inadvertently omit critical business logic or data. In turn, it could potentially halt business operations, frustrate regulators, or trigger costly customer issues.

Scarcity of legacy expertise

Many legacy systems were built 30+ years ago, and the engineers who built them are retiring. COBOL and RPG skills are disappearing from the talent pool, while younger developers rarely want to work with these systems, let alone rebuild them. This puts insurers in a race against time.

Heavy past investments

Insurers have poured millions into customizing their legacy processes over the years. From some leadership’s perspective, these systems do exactly what they need (albeit inefficiently). Executives often struggle to justify the cost and risk of a wholesale replacement with uncertain ROI.

The real cost of legacy: Risks and limitations

These outdated core systems create mounting operational and financial risks that compound over time.

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These risks include:

• Slow adaptation to market or regulatory changes: Even minor product changes or compliance updates can require extensive manual coding and testing on an old platform. A study by PwC found that developing and testing a new insurance product on legacy systems takes on average 6–9 months and $400K – $900K.
• Siloed systems create duplicate work and errors: Decades-old insurance IT architectures typically consist of many isolated subsystems (policy, billing, claims, etc.) that communicate poorly with each other. Teams often have to re-enter data or run batch transfers. It creates duplicate work and increases the risk of errors.
• Poor data access limits modern capabilities: Legacy systems make it hard to extract clean, structured, and complete data. This limits everything from reporting to analytics to AI. LLMs and agents can’t work with inaccessible or inconsistent data. And without APIs or event streams, real-time orchestration isn’t an option.
• Rising maintenance costs squeeze margins: Hardware support, software patches, and niche developer talent all cost more over time. These escalating costs reduce insurers' profitability while pulling funds away from customer-facing improvements.
• Poor user experience for both employees and customers:  Legacy interfaces frustrate employees who waste time navigating clunky, non-intuitive screens. Customers bear the brunt of slow, paper-driven processes and limited digital options.
• AI integration is off the table: Legacy systems can’t expose data in real time, support API-based orchestration, or integrate with AI tools without workarounds. That puts insurers at a disadvantage as competitors roll out AI-driven products, workflows, and experiences.
• Security and compliance risks: Older systems may not log or audit data access in compliance with today’s regulations. End-of-life software might not even receive security updates, effectively leaving known vulnerabilities exposed.

What does insurance legacy system transformation involve?

Insurance legacy system transformation involves rebuilding how data, processes, and applications connect across the business.

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Key components of an insurance legacy transformation include:

Data migration and normalization

Legacy systems store decades of policy, claims, and financial data, often in inconsistent formats.

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Data migration and normalization involve:

• Standardize fields and formats across business lines
• Resolve duplication, fragmentation, and orphaned records
• Structure unstructured content (like scanned forms or claim notes)

Redesigning workflows

Modernizing technology without improving processes would simply reproduce old, inefficient workflows on new tech. Transformation is a chance to rebuild those workflows around automation and intelligence.

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This might involve:

• Eliminating redundant approvals or re-keying
• Introducing real-time triggers for events like quote requests or claim updates
• Aligning new workflows with front-office UX and back-office compliance
• Adding automated decisions using AI
• Enabling customers to self-serve certain steps

Application refactoring and API enablement

In some cases, insurers choose to rewrite or modify the old code into a modern architecture (such as microservices). In others, they wrap them with APIs.

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They can:

• Break up monolithic apps into modular services
• Expose key functions (like policy lookup or payment status) via secure APIs
• Introduce orchestration layers that allow newer tools to interface with legacy back ends

This makes it possible to introduce digital channels or AI agents without waiting for a full core replacement.

Incremental modernization instead of full re-platforming

Very few insurers rip out everything at once. Most modernize in layers:

• Start with low-risk, high-impact domains (e.g., claims intake or quoting)
• Run old and new systems in parallel during transition periods
• Use middleware to sync data across systems while decoupling logic

Teams reduce operational risk and gain time to validate outcomes before expanding further through this phased model.

Rebuilding governance and security controls

Transformation requires bringing governance up to modern standards.

• Implement RBAC and SSO from the start
• Set up CI/CD pipelines and version-controlled deployment
• Enable audit trails for both system changes and user actions

Testing and validating every system change

A huge part of any legacy transformation is testing. Given the high risk of defects, a small error can cause financial miscalculations or compliance breaches. Insurers, therefore, invest heavily in test coverage at every stage. This includes:

• Replicate key business scenarios (e.g., policy rating, premium billing, claims calculations)
• Compare outputs across legacy and modern systems to validate results
• Run performance and load tests to confirm the new system can handle real-world volumes

Managing change across teams

Upgrading core systems changes how employees do their jobs and can be unsettling for long-time users of the old system. Effective transformation involves a change management program:

• Communicating changes to all stakeholders
• Providing training on the new tools
• Establish “super user” teams or a Center of Excellence to support others during and after the transition

5 Strategies: How leading insurers approach transformation

Insurers know legacy transformation carries risk. The ones who succeed build momentum with practical, low-risk moves that compound over time.

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Here’s how leading teams approach it:

1. Map system dependencies early

Insurers begin transformations with an exhaustive discovery phase to map all the interdependencies and spaghetti connections in their current architecture. This ensures that when one piece is moved, everything that relies on it is addressed.

2. Start with low-risk, high-impact workflows

They might target a peripheral but impactful process as a pilot. A process that, if improved, would benefit the business, but if it glitches, it won’t stop daily operations. A successful pilot is how modernization efforts earn trust and budget for larger phases.

3. Use middleware to gradually decouple systems

Leading teams insert middleware or API layers between legacy systems and new applications. The goal is to:

• Orchestrate workflows across both environments

• Allow new apps to ship while legacy logic stays in place
• Make future cutovers less painful

This strangler fig approach lets teams modernize one service or domain at a time.

4. Blend agile and waterfall for smoother change management

Some firms combine the strengths of Agile (flexibility, iterative delivery) with the rigor of Waterfall (detailed planning, stage gates) where appropriate.

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For example, the development of new front-end applications or microservices might use Agile sprints to deliver functionality continuously. But the overall program, with fixed regulatory deadlines, data conversion, and integration testing, might have Waterfall elements and hard milestones.

5. Align IT and business goals upfront

Insurers make sure to tie every technical decision to a business objective. To accomplish this, they break the traditional silo where IT owns systems and the business owns outcomes. Business and IT leadership work as one team with shared KPIs.

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This structure avoids the trap of building technically sound systems that don’t actually solve user pain points.

Superblocks as the bridge to insurance modernization

For teams modernizing in phases or wrapping legacy with APIs, Superblocks is designed to do exactly that.

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This AI-native enterprise application platform enables teams to build internal tools, orchestrations, and automations directly on top of legacy infrastructure. With full-code flexibility/extensibility, built-in governance, and hybrid deployment options, it bridges the gap between existing systems and modern requirements.

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Let’s break down how it speeds up insurance modernization:

UI modernization

Insurers use Superblocks to modernize legacy systems by building web-based UIs that sit on top of their existing logic.

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At the center of this is Clark, the AI agent by Superblocks. Clark builds full-stack, context-aware React interfaces that align with your design system, permissioning rules, and data access boundaries. You can go from prompt to working UI/app in seconds, then refine it visually or in raw code (in your IDE) as needed.

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The back-end systems stay untouched, while the front end communicates with them through secure APIs. For example, an insurer could build a modern policy inquiry dashboard with rich graphs and web forms that, behind the scenes, fetches data from the mainframe policy system.

Orchestration layer

Superblocks acts as a control layer that connects siloed systems through APIs or direct DB access.

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Teams can:

• Trigger actions across both old and new systems in a single workflow
• Aggregate data from claims, policy, and billing systems into unified views
• Run jobs, REST endpoints, or workflows from a single interface

This makes it possible to build AI-powered experiences or service automations even if the core systems are still legacy.

Low-code and AI-enabled automation that spans hybrid environments

Superblocks makes it easy to build low-code workflows that automate manual tasks across cloud apps, legacy systems, or both. 

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Teams can:

• Auto-trigger policy checks, payment processing, or compliance alerts
• Sync data across multiple systems on a schedule or by event
• Use custom code blocks for complex business logic or edge-case handling
• Integrate AI models directly into workflows to drive intelligent decision-making

Built-in compliance, auditability, and governance features

Superblocks is designed with enterprise governance features, which is a key reason it’s a viable bridge in regulated industries. It supports role-based access control (RBAC) and automatically maintains audit logs of changes and user actions. It also integrates with SSO providers for user authentication.

On-premise flexibility

When data residency or security requirements rule out full cloud adoption, Superblocks offers a hybrid deployment model. With the On-Prem Agent, sensitive data stays entirely within your network. The control plane runs in the Superblocks cloud for centralized app and user management, while all data processing happens in your VPC or data center.

Real-world use cases: Superblocks in action

To illustrate the above concepts, here are a few real-world style use cases demonstrating how an insurer might use Superblocks to modernize specific processes. 

Claims intake automation around a legacy claims system

Imagine an insurance carrier that still uses a COBOL mainframe application for processing claims. The customer experience is lacking. Claims are initiated via phone or PDF forms and then manually entered into the mainframe, and customers get little visibility until a decision is mailed weeks later. 

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With Superblocks, insurers can build a fully modern claims intake and triage workflow.

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They can develop a web form for customers to submit claims digitally, including uploading photos of damage. When a customer submits a claim, Superblocks’ workflow triggers a set of automated steps:

• It calls an API or RPA bot that creates a new claim record in the mainframe claims system
• It passes the uploaded files to an AI model for document extraction and damage classification
• It runs a fraud-detection model and scores the claim
• Based on that context, it routes the claim to an adjuster dashboard built in Superblocks

The adjuster interface pulls data from the mainframe policy records, billing systems, and AI model outputs, and presents it in a single view. 

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The legacy system remains the system-of-record for claims (no data is lost, and it can still do the final payment processing), but all surrounding interactions are digitized.

Scheduled mainframe-to-cloud data sync for analytics

Insurers increasingly want to leverage cloud analytics and reporting tools on their enterprise data. But when key data lives in a mainframe or iSeries that isn’t easily accessible to cloud apps, there’s a challenge. 

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Superblocks can help set up scheduled jobs to sync data from legacy to cloud in a governed way. 

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A typical sync job might look like this:

• Extract new transactions or policy changes from a mainframe via an API gateway
• Transform the data in-line by cleaning, normalizing, or reformatting as needed
• Load the output into a cloud warehouse like Snowflake or BigQuery
• Enrich the data by calling AI models for classification or anomaly detection

Every morning, the Superblocks job runs, and by 8 am, the analytics team gets up-to-date data in the cloud environment that’s ready for dashboards, forecasting, and other uses.

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Additionally, because Superblocks integrates with messaging/notifications, it could send an alert if any records failed to sync or if there’s an anomaly.

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This lets insurers extend the life of the legacy system by integrating it with cloud analytics. Over time, as teams trust the cloud copy more, they might shift reporting off the mainframe entirely.

5 tips for maintaining momentum after migration

The teams that get long-term ROI from modernization treat go-live as the beginning of a new optimization cycle.

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Here are some best-practice tips for maintaining momentum post-migration:

1. Build in test coverage for every migration stage: Keep automated tests for core functionalities and critical integrations running regularly. Nightly regression suites help catch data drift, unexpected errors, or side effects from ongoing changes.
2. Use RBAC and audit logs to ensure governance: Enforce proper Role-Based Access Control (RBAC) in the new environment from day one. Use audit logs to track system changes, user actions, and data access.
3. Create a Center of Excellence (CoE) for reuse and scale: Build a dedicated team of experts and evangelists who drive continuous improvement. This group can drive reuse across projects, capture lessons learned, and keep modernization from becoming a one-off effort.
4. Use feature toggles to ship safely: Feature toggles allow you to deploy new features into production in a dormant state, test them with a small set of users, and then gradually turn them on for others.
5. Monitor performance and iterate based on feedback: Use application performance monitoring (APM) tools to track load times, errors, and user behavior. Pair this with active feedback loops from frontline teams. If something’s slow, confusing, or high-friction, you’ll know early and can refine it.

Final thoughts: Start small, scale smart

Insurers don’t need to rip out their legacy systems to modernize. The smarter move is to evolve them one high-impact use case at a time.

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With platforms like Superblocks, teams can build modern apps and workflows that sit on top of legacy systems, connect with AI models, and deliver real-time experiences. All without disrupting what works.

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Over time, this approach turns legacy from a liability into an advantage. It preserves decades of business logic while gaining the agility of modern tech.

Bridge the gap between legacy and modern infrastructure

Superblocks provides a pragmatic path to modernization by augmenting legacy systems instead of abruptly replacing them. Insurers can deliver modern UIs and automated workflows on top of their existing cores, gradually phase in new components, all while maintaining enterprise-grade security and compliance. 

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We’ve looked at some of the features that make this possible, but just to recap:

• Multimodal app building (AI + visual + code): Start with AI to scaffold your dashboard, then refine it visually or extend it with full code. Switch between modes as needed, all in the same flow.
• Integrations with systems you rely on: Provides 60+ native integrations for databases, AI tools, cloud storage, and SaaS apps.
• On-prem deployment: Deploy the Superblocks agent in your VPC to keep sensitive data and logic inside your network. Still manage apps, users, and permissions through Superblocks Cloud.
• Audit logging and action history: Track changes, updates, and actions across your apps to support compliance, accountability, and operational transparency.
• Observability and traceability: Send logs, metrics, and traces to Datadog, New Relic, or Splunk.
• Real-time streaming: Stream live telemetry from sources like Kafka, Kinesis, and Pub/Sub directly into your dashboards.
• Exportable code: Own your applications fully. Superblocks lets you export all your apps as standard React apps so you can host and maintain them independently.
• Automatic deployments: Integrates directly with CI/CD tools like GitHub Actions, CircleCI, and Jenkins, so you can deploy updates just like any other codebase.

If you’d like to see how these features can help your business stay flexible and in control, book a demo with our team now. 

Frequently asked questions

Can legacy insurance platforms be integrated with cloud tools?

Yes, legacy insurance platforms can be integrated with cloud tools using middleware or custom integration layers. Most legacy platforms weren’t built with APIs or real-time data access in mind, so teams typically use ETL tools, API gateways, or integration platforms to bridge the gap.

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These layers extract data from legacy systems and expose it in formats that cloud tools can work with.

How does Superblocks help modernize legacy systems?

Superblocks helps insurers modernize legacy systems by allowing them to build apps and workflows that connect to both old and new infrastructure through APIs or direct queries. You can orchestrate data movement, automate decisions, and even integrate AI without touching the legacy codebase.

What are common pitfalls in insurance modernization projects?

Some of the pitfalls insurers fall into during modernization are:

• Starting too big without proving value
• Failing to map system dependencies
• Poor test coverage, especially during data migration
• Lack of buy-in from business users
• Treating modernization as a one-off project instead of an ongoing process

Is low-code secure enough for insurance companies?

As long as the platform supports proper governance, access control, and regulatory compliance, low-code can meet the security needs of insurance organizations. Superblocks, for example, includes enterprise-grade features like RBAC, SSO integration, audit logging, and on-prem deployment options.

What’s the best strategy: rebuild or wrap?

For most insurers, wrapping is the better place to start. It lets you deliver value quickly while reducing risk. Rebuilding has a role, but should be used selectively for systems that are truly unsalvageable or blocking innovation.

How can I modernize my claims process?

Start by mapping the current flow. Identify what data is needed, where decisions happen, and which parts are manual. Then use a platform like Superblocks to build a digital claims intake app, automate triage logic, and integrate with core systems like your claims' database, document repository, and policy administration system. 

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You can also connect AI models for tasks like fraud detection or document analysis.

Are there low-code solutions for underwriting automation?

Yes. Several platforms support insurance underwriting, including Pega, which offers a pre-configured underwriting workbench. For more complex or custom underwriting flows, Superblocks provides more flexibility.