$3M Post-Mortem: Why Traditional UML Mapping Failed the Insurance Core Modernization

The project was codenamed "Project Phoenix," a $3 million initiative designed to migrate a 25-year-old claims processing engine from a legacy mainframe environment to a modern React-based microservices architecture. Fourteen months later, the project was scrapped. The post-mortem was brutal: despite thousands of pages of Unified Modeling Language (UML) diagrams and architectural mappings, the development team couldn't reconcile the "documented" logic with the actual behavior of the production system.

This isn't an isolated incident. According to Replay's analysis, 70% of legacy rewrites fail or exceed their original timeline, often due to the same fundamental flaw—relying on static documentation for dynamic, evolving systems. When we conducted a postmortem traditional mapping failed analysis for this Tier-1 insurer, we discovered that the gap between the UML diagrams and the actual UI state logic was wide enough to swallow the entire $3M budget.

TL;DR: Traditional UML and manual mapping fail in legacy modernization because they represent how a system should work, not how it actually works. This $3M insurance failure was caused by a 67% lack of accurate documentation and a "semantic gap" between business logic and UI behavior. Replay solves this by using Visual Reverse Engineering to convert real user workflows into documented React code, reducing the modernization timeline from years to weeks and cutting manual effort by 90%.

The Fatal Flaw: Why This Postmortem Traditional Mapping Failed#

In the insurance industry, business logic isn't just in the backend; it’s buried in the UI event handlers of legacy PowerBuilder, Delphi, or VB6 applications. When the "Project Phoenix" team started their discovery phase, they spent six months interviewing "subject matter experts" (SMEs) and drawing complex UML sequence diagrams.

However, the postmortem traditional mapping failed because the UML artifacts were decoupled from the source of truth. In a legacy environment, the source of truth isn't the documentation; it's the executable.

The Documentation Trap#

Industry data shows that 67% of legacy systems lack documentation entirely. For the remaining 33%, the documentation is usually out of date. In the case of Project Phoenix, the UML diagrams represented the system as it was envisioned in 1998, not the patched, "spaghetti-code" reality of 2024.

According to Replay's analysis, manual mapping requires an average of 40 hours per screen to document, design, and code. For an insurance suite with 500+ screens, that’s 20,000 man-hours just for the frontend.

Modernize without rewriting from scratch

The $3.6 Trillion Technical Debt Crisis#

The failure of Project Phoenix is a microcosm of a larger global issue. We are currently facing a $3.6 trillion global technical debt mountain. For financial services and insurance providers, this debt isn't just a line item; it's an existential threat.

When we look at why the postmortem traditional mapping failed, we see a recurring pattern: the "Semantic Gap." This is the distance between what a business analyst thinks a button does and what the legacy code actually executes. Traditional mapping attempts to bridge this gap with human language, which is inherently ambiguous.

Video-to-code is the process of recording a user interacting with a legacy application and using machine learning to extract the underlying component structure, state transitions, and business logic into modern code.

By using Replay, organizations can bypass the manual mapping phase entirely. Instead of asking an SME what happens when a "Claim Denied" flag is toggled, you simply record the process. Replay’s AI Automation Suite then generates the corresponding React components and state management logic.

Technical Deep Dive: From Legacy State to React Components#

One of the primary reasons the postmortem traditional mapping failed was the inability to capture "hidden state." In the legacy insurance app, certain fields would only become editable if a specific combination of "Policy Type" and "Region" was selected—logic that was never documented in the UML.

With Replay, this logic is captured visually. Here is an example of how a complex legacy insurance form is transformed into a clean, type-safe React component using Replay's output.

Code Example 1: Modernized Claims Component#

typescript
import React, { useState, useEffect } from 'react';
import { useClaimsLogic } from './hooks/useClaimsLogic';
import { Button, Input, Select, Alert } from '@/components/ui';

// This component was generated via Replay's Visual Reverse Engineering
// based on a recording of the legacy "ClaimEntry_v4" screen.

interface ClaimFormProps {
  policyId: string;
  onSuccess: (data: any) => void;
}

export const ModernizedClaimEntry: React.FC<ClaimFormProps> = ({ policyId, onSuccess }) => {
  const { state, actions, validation } = useClaimsLogic(policyId);
  
  // Replay captured the conditional logic where 'AdjusterCode' 
  // is required only for 'Commercial' policy types.
  const isAdjusterRequired = state.policyType === 'COMMERCIAL';

  return (
    <div className="p-6 bg-white rounded-lg shadow-md">
      <h2 className="text-2xl font-bold mb-4">Claims Entry</h2>
      
      <div className="grid grid-cols-2 gap-4">
        <Input 
          label="Policy Number" 
          value={state.policyNumber} 
          disabled 
        />
        
        <Select
          label="Claim Type"
          options={state.claimTypeOptions}
          onChange={(val) => actions.setClaimType(val)}
        />

        {isAdjusterRequired && (
          <Input 
            label="Adjuster Code"
            error={validation.errors.adjusterCode}
            onChange={(val) => actions.setAdjusterCode(val)}
          />
        )}
      </div>

      <div className="mt-6 flex justify-end gap-2">
        <Button variant="outline" onClick={actions.reset}>Cancel</Button>
        <Button variant="primary" onClick={() => actions.submit(onSuccess)}>
          Submit Claim
        </Button>
      </div>
    </div>
  );
};

Bridging the Design System Gap#

The postmortem traditional mapping failed also because the design team tried to build a new design system in a vacuum. They created beautiful Figma files that were impossible to map to the legacy data structures.

Replay's Library (Design System) feature allows you to extract the atomic elements of your legacy UI and map them directly to a modern Tailwind or Material UI theme. This ensures that the modernized application maintains functional parity while benefiting from a modern UX.

Learn more about Building Design Systems from Legacy UIs

Why Traditional Mapping Fails in Regulated Environments#

In Healthcare, Insurance, and Government, the stakes are higher. A missed validation rule in a UML diagram isn't just a bug; it's a compliance violation. The postmortem traditional mapping failed for Project Phoenix because the auditors couldn't verify that the new system handled "PII (Personally Identifiable Information)" exactly like the legacy system.

Industry experts recommend a "Capture-First" approach to modernization. Instead of manual interpretation, use a platform that provides a verifiable audit trail from the legacy screen to the new code. Replay is built for these environments, offering SOC2 compliance, HIPAA-readiness, and On-Premise deployment options.

Code Example 2: Extracted State Management Logic#

Replay doesn't just generate the UI; it extracts the "Flows" or the architectural sequence of the application.

typescript
// Replay Blueprint: Claims Workflow State Machine
// Extracted from 12 separate user recordings of the "Claims Approval" process.

export type ClaimsState = 'DRAFT' | 'PENDING_REVIEW' | 'ADJUSTER_ASSIGNED' | 'APPROVED' | 'DENIED';

interface ClaimsContext {
  claimId: string;
  amount: number;
  requiresSupervisor: boolean;
}

export const claimsStateMachine = {
  initial: 'DRAFT',
  states: {
    DRAFT: {
      on: { SUBMIT: 'PENDING_REVIEW' }
    },
    PENDING_REVIEW: {
      on: {
        ASSIGN: 'ADJUSTER_ASSIGNED',
        REJECT: 'DENIED'
      }
    },
    ADJUSTER_ASSIGNED: {
      on: {
        APPROVE: (ctx: ClaimsContext) => 
          ctx.amount > 10000 ? 'SUPERVISOR_REVIEW' : 'APPROVED',
        DENY: 'DENIED'
      }
    },
    // ... more state transitions extracted by Replay AI
  }
};

Replay: From 18 Months to Weeks#

The most damning statistic in the postmortem traditional mapping failed report was the timeline. The enterprise average for a core system rewrite is 18 months. Project Phoenix was at month 14 with nothing to show.

By using Replay, that 18-month timeline is compressed into days or weeks.

1. •Record: SMEs record themselves performing standard workflows in the legacy app.
2. •Reverse Engineer: Replay’s AI analyzes the video, identifies components, and maps the data flow.
3. •Refine: Developers use the Replay Blueprints (Editor) to fine-tune the generated React code.
4. •Deploy: The result is a documented, componentized React application that is functionally identical to the legacy system but architecturally modern.

According to Replay's analysis, this workflow results in a 70% average time savings. You aren't rewriting from scratch; you are translating with precision.

Explore the Replay AI Automation Suite

Lessons Learned from the Postmortem#

If the "Project Phoenix" team had used a visual reverse engineering approach, the outcome would have been different. The postmortem traditional mapping failed because it relied on human memory and static diagrams. Modernization requires a living, breathing map of the system.

Key Takeaways:

• •UML is a lie: In legacy systems, the code has evolved far beyond the original design.
• •Documentation is a bottleneck: Waiting for manual documentation is the fastest way to kill a project budget.
• •Visual truth is supreme: If you can see it on the screen, Replay can turn it into code.
• •Start with Flows: Don't just map screens; map the user journeys.

The $3M loss was avoidable. By shifting from manual UML mapping to an automated, visual-first approach, the insurer could have spent that budget on innovation rather than trying to figure out how their own legacy system worked.

Frequently Asked Questions#

Why does traditional UML mapping fail in enterprise modernization?#

Traditional UML mapping fails because it relies on manual interpretation and outdated documentation. In complex legacy systems, business logic is often "hidden" in UI event handlers or undocumented patches. This creates a "semantic gap" where the documented plan doesn't match the actual system behavior, leading to massive delays and budget overruns.

How does Replay's "Video-to-Code" process work?#

Replay uses Visual Reverse Engineering to analyze screen recordings of legacy applications. The AI identifies UI components (buttons, inputs, tables), detects state changes, and maps out user flows. It then generates production-ready React code and TypeScript interfaces that mirror the functionality of the legacy system, saving up to 70% of development time.

Can Replay handle highly regulated industries like Insurance or Healthcare?#

Yes. Replay is designed for regulated environments. It is SOC2 compliant and HIPAA-ready. For organizations with strict data sovereignty requirements, Replay offers On-Premise deployment options, ensuring that sensitive data and proprietary business logic never leave your secure environment.

Is Replay a "No-Code" tool or a developer tool?#

Replay is a professional developer tool. While it uses AI to automate the "discovery" and "boilerplate" phases of modernization, it produces clean, standard React code that developers can own, modify, and integrate into their existing CI/CD pipelines. It is designed to empower Enterprise Architects and Senior Developers, not replace them.

Ready to modernize without rewriting? Book a pilot with Replay