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February 18, 2026 min readbanking loan origination system

The Invisible Logic: Capturing Edge-Case UI States in a Banking Loan Origination System

R
Replay Team
Developer Advocates

The Invisible Logic: Capturing Edge-Case UI States in a Banking Loan Origination System

The most dangerous part of a banking loan origination system (LOS) isn't the primary "Happy Path"—it’s the 400 conditional sub-states that only appear when a borrower has a non-resident alien status, three sources of secondary income, and a collateral property located in a flood zone. In the enterprise world, these are known as "edge cases," but in a legacy environment, they are often undocumented ghosts living in the machine.

When you attempt to modernize a legacy banking loan origination system, you aren't just fighting old code; you are fighting the $3.6 trillion global technical debt mountain. Most modernization projects fail because they underestimate the complexity of these UI states. According to Replay's analysis, 70% of legacy rewrites fail or exceed their timeline specifically because the "hidden" logic of the UI was never captured in the initial requirements.

TL;DR: Modernizing a banking loan origination system is notoriously difficult due to undocumented edge cases. Traditional manual rewrites take 40 hours per screen and have a 70% failure rate. Replay uses Visual Reverse Engineering to convert video recordings of real user workflows into documented React code, reducing modernization timelines from years to weeks and cutting development time by 70%.

The Documentation Deficit in Financial Services#

Industry experts recommend that before a single line of code is written for a new system, the existing logic must be fully mapped. However, the reality is stark: 67% of legacy systems lack any form of up-to-date documentation.

In a typical banking loan origination system, the UI logic is often hardcoded into the view layer or buried in stored procedures. If a developer needs to know why a specific "Escrow Waiver" checkbox disappears when the Loan-to-Value (LTV) ratio hits 80.1%, they usually have to go "spelunking" in 20-year-old COBOL or Java Swing code.

Video-to-code is the process of using computer vision and AI to analyze screen recordings of legacy software in action and automatically generate the underlying component architecture, state logic, and styling.

By using Replay, architects can record a loan officer navigating these complex paths. Replay’s engine doesn't just "see" pixels; it identifies patterns, component boundaries, and state transitions, turning a 10-minute recording into a production-ready React component library.

The Cost of Manual Extraction vs. Visual Reverse Engineering#

The traditional approach to modernizing a banking loan origination system involves a "Clean Room" rewrite. Business analysts watch users, write Jira tickets, designers recreate mockups in Figma, and developers write React from scratch. This manual process averages 40 hours per screen.

MetricManual Legacy RewriteReplay Visual Reverse Engineering
Time per Screen40+ Hours4 Hours
Documentation Accuracy45% (Human error prone)99% (Machine captured)
Average Project Timeline18–24 Months4–8 Weeks
Edge Case CaptureOften missed until UATCaptured during recording
Cost to BusinessHigh ($250k+ per module)Low (70% savings)

Capturing Edge-Case UI States: A Technical Deep Dive#

In a banking loan origination system, state management is everything. Consider a "Commercial Credit Application" screen. Depending on the "Entity Type" selected (LLC, S-Corp, C-Corp), the entire subsequent form must morph.

When you record these transitions using Replay, the platform's Flows feature maps the state machine. It identifies that

text
State A
(LLC) leads to
text
Component Set B
(Member Details), while
text
State C
(C-Corp) triggers
text
Component Set D
(Shareholder Disclosure).

Example: Legacy State Mapping#

Before Replay, a developer might find a messy conditional block in a legacy JSP file like this:

typescript
// The "Old Way" - Trying to decipher legacy conditional logic function handleLegacyFormDisplay(entityType: string, ltvRatio: number) { if (entityType === 'LLC' && ltvRatio > 80) { // Why is this here? Nobody knows. document.getElementById('escrow-section').style.display = 'block'; renderMemberTable(); } else if (entityType === 'CORP') { renderShareholderTable(); hideSection('tax-exemption'); } // ... 500 more lines of spaghetti }

This logic is fragile and lacks type safety. When Replay processes a recording of this workflow, it generates a clean, modular React component that encapsulates this logic within a modern state management pattern.

Example: Generated Modern React Component#

Replay’s AI Automation Suite transforms that visual recording into structured TypeScript code. Here is how it handles the same edge-case logic:

tsx
import React, { useState, useEffect } from 'react'; import { MemberTable, ShareholderTable, EscrowSection } from './components'; import { useLoanState } from './hooks/useLoanState'; /** * Generated by Replay Blueprints * Component: LoanOriginationForm * Source: Commercial_LOS_Recording_v4.mp4 */ interface LOSFormProps { initialData?: any; onStateChange: (state: string) => void; } export const LoanOriginationForm: React.FC<LOSFormProps> = ({ initialData }) => { const { entityType, ltvRatio, updateField } = useLoanState(initialData); // Replay captured that 'EscrowSection' only appears under specific LTV conditions const showEscrow = entityType === 'LLC' && ltvRatio > 80; return ( <div className="p-6 space-y-4 bg-slate-50 rounded-lg"> <h2 className="text-xl font-bold">Loan Origination Details</h2> <select value={entityType} onChange={(e) => updateField('entityType', e.target.value)} className="form-select" > <option value="LLC">LLC</option> <option value="CORP">Corporation</option> </select> {entityType === 'LLC' && <MemberTable />} {entityType === 'CORP' && <ShareholderTable />} {showEscrow && ( <EscrowSection alertType="high-risk" message="LTV exceeds 80% threshold for LLC entities." /> )} </div> ); };

By converting the visual reality into code, Replay ensures that the "Why" of the UI is preserved. You can learn more about this in our article on Legacy Modernization Strategy.

The Replay Architecture: Library, Flows, and Blueprints#

Modernizing a banking loan origination system requires more than just code generation; it requires an ecosystem. Replay provides three core pillars to manage this:

1. The Library (Design System)#

As you record different screens of your LOS, Replay identifies recurring UI patterns—buttons, input fields, data grids, and modals. It automatically extracts these into a centralized Design System. This prevents the "Component Explosion" problem where five different developers create five different "Submit" buttons. For more on this, see Design System Automation.

2. Flows (Architecture)#

Flows visualize the user journey. In a banking loan origination system, the flow from "Application Entry" to "Underwriting" involves dozens of micro-decisions. Replay maps these visually, allowing architects to see the entire application's logic at a bird's-eye view.

3. Blueprints (The Editor)#

Blueprints is where the magic happens. It is the bridge between the video recording and the final React code. Within Blueprints, architects can refine the AI-generated components, adjust Tailwind CSS classes, and wire up API endpoints to the newly created UI.

Security and Compliance in Financial Modernization#

For institutions managing a banking loan origination system, "Cloud-only" is often a dealbreaker. Security is paramount when dealing with PII (Personally Identifiable Information) and sensitive financial logic.

Replay is built for regulated environments:

  • SOC2 & HIPAA Ready: Our processes meet the highest standards of data protection.
  • On-Premise Deployment: For Tier-1 banks, Replay can be deployed entirely within your own VPC or on-premise data center.
  • PII Masking: Our recording tools automatically mask sensitive data fields before they ever leave the user's browser, ensuring that social security numbers and account balances are never captured in the training data.

Why 18 Months is No Longer Acceptable#

The 18-month average enterprise rewrite timeline is a relic of the manual era. In that time, market conditions change, regulations shift (like new CFPB requirements), and the original project sponsors often move on.

According to Replay's analysis, by using Visual Reverse Engineering, teams can move from "Recording" to "Functional Prototype" in days rather than months. This allows for an iterative modernization approach—upgrading the most critical modules of the banking loan origination system first, rather than attempting a risky "Big Bang" migration.

The $3.6 trillion technical debt problem isn't going to solve itself through manual labor. It requires a shift toward automation. By capturing the visual truth of how a system is actually used, Replay eliminates the guesswork and the documentation gap.

Frequently Asked Questions#

How does Replay handle complex data grids in a banking loan origination system?#

Replay’s AI is trained to recognize complex data structures, including nested tables and paginated grids. It identifies the data-binding patterns in the legacy UI and generates modern React-table or AG-Grid implementations that mimic the original functionality while providing modern features like filtering and sorting.

Can Replay capture UI states that are triggered by backend errors?#

Yes. By recording a user performing "negative testing" (e.g., entering an invalid credit score or an expired date), Replay captures the error states, validation messages, and conditional styling associated with those edge cases. This ensures the new React application handles errors exactly like the legacy system.

Does Replay require access to the legacy source code?#

No. Replay works via Visual Reverse Engineering. It analyzes the rendered output of the application. This makes it ideal for modernizing "black box" legacy systems where the source code is lost, undocumented, or written in obsolete languages that current staff cannot read.

Is the generated code maintainable?#

Absolutely. Replay generates clean, human-readable TypeScript and React code using standard patterns and Tailwind CSS. It does not produce "spaghetti code." The output is designed to be checked into your Git repository and maintained by your development team just like any other modern codebase.

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