Claims Processing Modernization: How Insurance Giants Extract Logic from Legacy Workbenches

70% of legacy rewrites fail before they ever reach production. For insurance giants, this isn't just a statistic—it's a multi-million dollar liability hidden inside a 30-year-old claims workbench. When the documentation is missing, the original developers are retired, and the codebase is a "black box," the traditional "rip and replace" strategy is a suicide mission.

TL;DR: Claims Processing Modernization is shifting from high-risk manual rewrites to Visual Reverse Engineering, allowing enterprises to extract business logic and UI components from legacy workbenches in weeks rather than years.

The $3.6 Trillion Technical Debt Trap#

The global technical debt has ballooned to $3.6 trillion, and nowhere is this more visible than in the insurance sector. Claims processing systems—often referred to as "workbenches"—are the operational heart of these organizations. They handle everything from policy verification to fraud detection and settlement. However, 67% of these legacy systems lack any form of up-to-date documentation.

Architects are often tasked with modernizing these systems under impossible constraints. You can't turn the system off because it processes $100M in claims daily. You can't easily modify it because a single change in a COBOL routine or a legacy Java applet might break a downstream regulatory reporting module.

The result? The "Big Bang" rewrite. An 18-24 month roadmap that usually ends in a bloated budget and a product that still doesn't match the functional parity of the original system.

Why Manual Modernization Fails#

Manual modernization is essentially "software archaeology." Engineers spend 40 hours per screen just trying to map the fields, understand the hidden state transitions, and document the validation logic. In a complex claims workbench with 500+ screens, the math simply doesn't work.

From Black Box to Documented Codebase#

The future of Claims Processing Modernization isn't rewriting from scratch; it's understanding what you already have. This is where Replay changes the paradigm. Instead of reading through millions of lines of spaghetti code, Replay uses the running application as the source of truth.

By recording real user workflows—a claims adjuster processing a complex medical liability claim, for example—Replay captures the "Visual Truth" of the system. It records the DOM mutations, the network calls, the state changes, and the UI layout.

💰 ROI Insight: Manual screen extraction takes an average of 40 hours per screen. With Replay’s automation suite, that time is compressed to 4 hours. For a 100-screen application, that's a saving of 3,600 engineering hours.

Capturing the "Hidden" Business Logic#

In insurance, business logic is often buried in the UI layer—validation rules that only trigger on specific field combinations or hidden calculations that occur before an API call. Traditional static analysis tools miss these because they can't see the runtime behavior.

Replay extracts this logic and generates clean, modular React components and TypeScript definitions. It creates a bridge between the legacy "Black Box" and the modern cloud-native environment.

typescript
// Example: Extracted Business Logic from a Legacy Claims Workbench
// Generated by Replay AI Automation Suite

interface ClaimValidationResult {
  isValid: boolean;
  errors: string[];
  riskScore: number;
}

/**
 * Extracted from: ClaimsWorkbench/PolicyValidation.java (Legacy)
 * Logic: Cross-references loss date with policy effective dates 
 * and applies state-specific regulatory adjustments.
 */
export const validateClaimPeriod = (
  lossDate: Date, 
  policyStart: Date, 
  policyEnd: Date,
  stateCode: string
): ClaimValidationResult => {
  const errors: string[] = [];
  
  // Logic preserved from legacy workflow recording
  if (lossDate < policyStart || lossDate > policyEnd) {
    errors.push("Loss date falls outside of policy coverage period.");
  }

  // State-specific logic extracted from runtime behavior
  const riskScore = calculateStateRisk(stateCode, lossDate);

  return {
    isValid: errors.length === 0,
    errors,
    riskScore
  };
};

The Replay Workflow: 4 Steps to Modernization#

How do insurance giants actually use Replay to move from a legacy workbench to a modern React-based Design System? It follows a structured, repeatable process.

Step 1: Recording the Source of Truth#

Subject Matter Experts (SMEs) or adjusters perform their standard tasks while Replay records the session. This isn't just a video; it's a deep-packet capture of the application's front-end state.

Step 2: Visual Extraction and Componentization#

Replay’s engine analyzes the recording and identifies recurring UI patterns. It automatically populates the Library (Design System) with atomic components (buttons, inputs, tables) and complex organisms (claim summary cards, policy headers).

Step 3: Blueprinting the Architecture#

Using the Blueprints (Editor), architects can see the "Flows" of the application. This provides a visual map of how data moves from Screen A to Screen B, effectively documenting the system's architecture without reading a single line of legacy code.

Step 4: Generating Modern Assets#

Replay generates the technical artifacts required for the new system:

• •React/TypeScript Components: Clean, accessible code.
• •API Contracts: Swagger/OpenAPI definitions based on captured network traffic.
• •E2E Tests: Playwright or Cypress scripts that mimic the recorded user behavior.

⚠️ Warning: Most modernization projects fail because they ignore "edge case" business logic that only appears once a month. Visual recording ensures these workflows are captured and documented.

Implementation Detail: Preserving Business Logic#

When modernizing a claims system, the UI is only half the battle. The real value lies in the data transformations. Replay identifies the mapping between legacy data structures and the desired modern state.

typescript
// Example: Generated React Component with Integrated Legacy Logic
import React, { useState, useEffect } from 'react';
import { Button, TextField, Alert } from '@replay-ui/insurance-library';

export const ClaimsAdjustmentForm: React.FC<{ claimId: string }> = ({ claimId }) => {
  const [claimData, setClaimData] = useState<any>(null);
  const [validation, setValidation] = useState<{ errors: string[] }>({ errors: [] });

  // Replay-generated hook based on legacy API traffic analysis
  const { data, loading } = useLegacyClaimData(claimId);

  const handleApprove = () => {
    // Logic extracted from legacy 'Cmd_Approve_Click' event
    if (data.totalAmount > 50000 && data.adjusterLevel < 3) {
      setValidation({ errors: ["Approval exceeds authority limit."] });
      return;
    }
    // Proceed with modernized workflow
  };

  return (
    <div className="p-6 space-y-4">
      <h2 className="text-xl font-bold">Adjust Claim: {claimId}</h2>
      {validation.errors.map(err => <Alert type="error" message={err} />)}
      <TextField 
        label="Total Loss Amount" 
        value={data?.amount} 
        readOnly 
      />
      <Button onClick={handleApprove} variant="primary">
        Approve Claim
      </Button>
    </div>
  );
};

Security and Compliance in Regulated Environments#

For Financial Services and Healthcare, "cloud-only" is often a non-starter. Claims processing involves PII (Personally Identifiable Information) and PHI (Protected Health Information).

Replay is built for these environments. It offers:

• •On-Premise Deployment: Keep all recording and extraction data within your own VPC.
• •SOC2 & HIPAA Readiness: Built-in PII masking during the recording phase ensures that sensitive data never leaves the local environment or enters the extraction engine.
• •Audit Trails: Every component generated is linked back to the original recording, providing a clear "line of sight" for compliance auditors.

📝 Note: Unlike AI code assistants that suggest "plausible" code, Replay generates code based on the actual execution and visual output of your specific legacy system.

The Strangler Fig Pattern 2.0#

The traditional Strangler Fig pattern involves placing a proxy in front of the legacy system and replacing features one by one. While effective, the "discovery" phase of this pattern is usually manual and slow.

Replay accelerates the Strangler Fig pattern by providing the blueprints for the "new" features immediately. Instead of spending 3 months analyzing the "Check Printing" module, you record it in 30 minutes and have the React components and API contracts ready by the end of the day.

• •Speed: From 18 months to weeks.
• •Accuracy: 1:1 visual and functional parity.
• •Maintainability: Generated code follows your organization's modern linting and architectural standards.

Frequently Asked Questions#

How long does legacy extraction take?#

While a full enterprise-grade rewrite typically takes 18-24 months, Replay customers see an average time saving of 70%. Most core workbenches can be visually documented and componentized within 4 to 8 weeks, depending on the number of unique workflows.

What about business logic preservation?#

Replay doesn't just copy the UI; it captures the behavior. By recording the network requests and state changes associated with user actions, Replay generates the API contracts and validation logic required to replicate that behavior in a modern environment.

Does Replay support mainframe or terminal-based systems?#

Yes. As long as the system can be accessed via a browser or a terminal emulator that runs on a modern OS, Replay can record the interactions and begin the process of "Visual Reverse Engineering." We specialize in transforming "green screens" into modern, accessible web interfaces.

How does this integrate with our existing CI/CD?#

Replay exports standard React code, TypeScript definitions, and JSON blueprints. These can be committed directly to your Git repositories (GitHub, GitLab, Bitbucket) and integrated into your standard deployment pipelines.

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Ready to modernize without rewriting? Book a pilot with Replay - see your legacy screen extracted live during the call.