Modernizing Financial Underwriting: Extracting 20 Years of Rule Logic from Legacy UIs

Most financial underwriting modernization projects die in the "discovery phase"—a polite term for high-priced consultants spending six months trying to read undocumented 20-year-old COBOL, Delphi, or VB6 code. When you are dealing with a $3.6 trillion global technical debt mountain, the traditional approach of manual archaeology isn't just slow; it’s a fiscal liability.

In the financial services sector, the underwriting engine is the "black box" that governs profitability. Over 20 years, these systems have been patched, hotfixed, and modified by developers who have long since retired. The result? 67% of legacy systems lack any form of accurate documentation, and 70% of big-bang rewrites fail or exceed their timelines by years.

TL;DR: Modernizing financial underwriting requires shifting from manual code archaeology to visual reverse engineering with Replay, reducing screen migration from 40 hours to 4 hours while preserving 20 years of undocumented business logic.

The Underwriting Paradox: Logic Trapped in the View Layer#

In legacy financial systems, the "business logic" is rarely isolated in a clean API layer. It is often hardcoded into the UI components—validation rules that prevent a loan from being approved if a specific debt-to-income ratio isn't met, or conditional fields that only appear for specific jurisdictions.

When you attempt to modernize these systems, you face the "Documentation Gap." You can't move to a modern React-based micro-frontend architecture because nobody knows exactly what the old system does under every edge case.

The Cost of Manual Modernization#

The manual approach involves a developer sitting with an underwriter, watching them work, and trying to recreate the logic in a new ticket. This process takes an average of 40 hours per screen. With Replay, this is reduced to 4 hours.

Moving from Black Box to Documented Codebase#

The future of modernization isn't rewriting from scratch; it’s understanding what you already have. Replay changes the paradigm by using the video as the source of truth. By recording real user workflows within the legacy underwriting system, Replay’s AI Automation Suite extracts the underlying structure, state transitions, and business rules.

Step 1: Record the Workflow#

An underwriter performs a standard "Risk Assessment" workflow in the legacy application. Replay captures the DOM mutations, network requests, and user interactions. This transforms a "black box" session into a structured data stream.

Step 2: Extract the Blueprint#

Replay’s Blueprints (Editor) analyzes the recording to identify patterns. It recognizes that a specific dropdown menu triggers a complex validation rule. Instead of a developer guessing the logic, Replay generates the technical specification.

Step 3: Generate Modern React Components#

Replay doesn't just show you what happened; it generates the code. It produces documented React components that mirror the legacy behavior but utilize modern design patterns.

typescript
// Example: Generated Underwriting Logic Component from Replay Extraction
// Source: Legacy Delphi Underwriting Module (Circa 2004)
// Preserves: Multi-tier risk validation logic

import React, { useState, useEffect } from 'react';
import { RiskScoreCard, ValidationAlert } from '@internal/design-system';

interface UnderwritingData {
  creditScore: number;
  annualIncome: number;
  existingDebt: number;
  jurisdiction: string;
}

export const ModernizedUnderwritingForm: React.FC<{ initialData: UnderwritingData }> = ({ initialData }) => {
  const [data, setData] = useState(initialData);
  const [riskTier, setRiskTier] = useState<'Low' | 'Medium' | 'High' | 'Decline'>('Low');

  // Business logic extracted via Replay AI Automation Suite
  useEffect(() => {
    const dtiRatio = (data.existingDebt / (data.annualIncome / 12)) * 100;
    
    if (data.creditScore < 580 || dtiRatio > 45) {
      setRiskTier('Decline');
    } else if (data.creditScore < 660 || (data.jurisdiction === 'NY' && dtiRatio > 38)) {
      // Note: Extracted specific NY state regulatory override logic
      setRiskTier('High');
    } else {
      setRiskTier('Low');
    }
  }, [data]);

  return (
    <div className="p-6 border rounded-lg shadow-sm">
      <h2 className="text-xl font-bold mb-4">Underwriting Decision Engine</h2>
      <RiskScoreCard tier={riskTier} />
      {/* Modernized UI components mapped to legacy data fields */}
      <input 
        type="number" 
        value={data.annualIncome} 
        onChange={(e) => setData({...data, annualIncome: Number(e.target.value)})}
        className="input-primary"
      />
      {riskTier === 'Decline' && <ValidationAlert message="Fails Tier 1 Regulatory Compliance" />}
    </div>
  );
};

💡 Pro Tip: When extracting logic, focus on the "Hidden State." Legacy systems often have invisible dependencies where changing one field affects five others. Replay’s Flows (Architecture) feature maps these dependencies visually so you don't break the engine during migration.

Why "Big Bang" Rewrites Fail in Finance#

The 18-month average enterprise rewrite timeline is a conservative estimate. In highly regulated environments like Insurance and Banking, the timeline is often extended by "Regression Terror"—the fear that the new system won't handle a specific 15-year-old edge case that is critical for compliance.

Manual documentation is the bottleneck. When 67% of systems have no documentation, the developers are essentially flying blind. Replay provides:

• •API Contracts: Automatically generated from legacy network traffic.
• •E2E Tests: Generated from the recorded user sessions to ensure parity.
• •Technical Debt Audit: Identifying which parts of the legacy UI are actually used vs. dead code.

⚠️ Warning: Never attempt to modernize a financial system without a parity-testing strategy. Without automated extraction, you are guaranteed to miss the "Long Tail" of business rules buried in the legacy UI.

The Replay Workflow: From Recording to Production#

Step 1: Assessment and Library Setup#

Before recording, we define the target Design System in the Replay Library. This ensures that the extracted components aren't just functional, but adhere to your modern brand guidelines.

Step 2: Recording "Golden Paths"#

Subject Matter Experts (SMEs) record the primary workflows. For underwriting, this includes:

1. •New Application Entry
2. •Document Verification
3. •Risk Tier Override
4. •Final Approval/Rejection

Step 3: Extraction and Refinement#

Replay's AI analyzes the recordings. It identifies that a "Button Click" in the legacy system actually triggers three separate legacy API calls and a local state change. It bundles this into a clean, modern React hook.

typescript
// Example: Extracted Hook for Legacy API Orchestration
// This preserves the exact sequence of the 20-year-old backend requirements

export const useLegacyUnderwritingActions = () => {
  const submitApplication = async (payload: any) => {
    // Replay identified this specific sequence from network extraction
    const step1 = await api.post('/v1/validate-identity', payload.identity);
    if (step1.status === 'VALID') {
      const step2 = await api.post('/v2/credit-check-internal', payload.credit);
      return step2.data;
    }
    throw new Error("Identity Verification Failed - Legacy Protocol 403");
  };

  return { submitApplication };
};

Step 4: E2E Parity Validation#

Replay generates Playwright or Cypress tests based on the original recording. You run these against the new component to ensure it behaves exactly like the old one.

💰 ROI Insight: By automating the extraction of these "Golden Paths," enterprises typically see a 70% reduction in total modernization time. What used to take 2 years now takes 6 months.

Built for Regulated Environments#

Financial services cannot use "Black Box AI" that sends data to the public cloud. Replay is built for the enterprise:

• •SOC2 & HIPAA Ready: Data handling meets the highest security standards.
• •On-Premise Available: Keep your sensitive underwriting logic and PII within your own firewall.
• •Audit Trails: Every extracted component is linked back to the original video recording, providing a clear "Chain of Custody" for logic extraction.

Frequently Asked Questions#

How does Replay handle logic that isn't visible in the UI?#

While Replay excels at extracting logic present in the view layer and network traffic, it also maps the "State Transitions." By observing how the UI reacts to different data inputs, Replay can infer backend constraints and document them in the generated API contracts.

Can we use Replay for systems with no source code?#

Yes. That is the core strength of Visual Reverse Engineering. Since Replay operates on the rendered output and the browser/system interactions, it doesn't need access to the original (and likely lost) COBOL or VB6 source files to understand the behavior.

What is the learning curve for our engineering team?#

If your team knows React and TypeScript, they can use Replay. Replay outputs standard, clean code that fits into your existing CI/CD pipeline. The platform is designed to augment your developers, not replace their workflow.

How does this compare to traditional "Low-Code" platforms?#

Low-code platforms often lock you into a new proprietary ecosystem. Replay does the opposite: it extracts logic out of a legacy proprietary ecosystem and gives you standard, open-source React code that you own forever.

---

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