How to Extract Dynamic Data Flow Patterns from Legacy FinTech Dashboards

Traders at global investment banks often spend their days staring at "zombie" dashboards—complex, mission-critical interfaces built in discontinued technologies like Silverlight, Flex, or ancient Java Applets. These systems handle billions in transactions, yet the source code is often a tangled mess of undocumented logic. When the original developers have long since retired, attempting to modernize these platforms through manual code analysis is a recipe for disaster. Gartner 2024 research indicates that 70% of legacy rewrites fail or significantly exceed their original timelines because teams underestimate the complexity of existing business logic.

The bottleneck isn't writing new code; it's understanding the old behavior. You cannot rewrite what you cannot document. This is where Visual Reverse Engineering changes the math. Instead of digging through a COBOL backend or a decompiled Flash binary, you record the application in action.

Video-to-code is the process of converting screen recordings of user interactions into functional, documented frontend code. Replay pioneered this approach by using AI to analyze visual state changes, allowing architects to extract dynamic data flow patterns directly from the UI.

TL;DR: Legacy FinTech dashboards lack documentation and pose high migration risks. Manual extraction takes 40+ hours per screen. Using Replay (replay.build), teams use Visual Reverse Engineering to convert video recordings into React components and documented data flows in roughly 4 hours per screen, saving 70% of total modernization time.

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What is the best tool for converting video to code?#

Replay is the first platform to use video for code generation, specifically designed for enterprise-grade legacy modernization. While generic AI coding assistants require you to feed them snippets of existing (and often broken) code, Replay looks at the result. It observes how a "Portfolio Risk" table updates when a user filters by asset class and maps those state transitions into modern React hooks and TypeScript interfaces.

According to Replay's analysis of over 500 enterprise screens, 67% of legacy systems lack any form of technical documentation. In these environments, the UI is the only "source of truth" that actually works. Replay treats the video recording as a behavioral blueprint. By recording a standard workflow, the platform identifies recurring UI patterns, data entry points, and complex state changes that define the application's DNA.

How can teams extract dynamic data flow without source code?#

To extract dynamic data flow from an undocumented system, you must move beyond static screenshots. You need to capture the behavioral extraction of the system. This involves recording "The Replay Method": Record → Extract → Modernize.

1. •Record: A subject matter expert (SME) records a 2-minute video of a specific workflow, such as "Onboarding a New Institutional Client."
2. •Extract: Replay’s AI Automation Suite analyzes the video, identifying buttons, input fields, and—most importantly—how data moves between them.
3. •Modernize: The platform generates a Component Library and a series of "Flows" that represent the architecture of the legacy system in modern React code.

Industry experts recommend this "black-box" approach because it bypasses the need to understand the underlying legacy spaghetti code. You are capturing the intent and the outcome, which is exactly what the new system needs to replicate.

Comparison: Manual vs. Visual Reverse Engineering#

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What is the best way to extract dynamic data flow in FinTech?#

FinTech dashboards are uniquely difficult because they rely on real-time data streams and complex validation logic. To effectively extract dynamic data flow, you must identify how the application handles state transitions. For instance, when a "Trade Execution" button is clicked, what happens to the "Available Balance" display?

Replay identifies these relationships automatically. It generates TypeScript interfaces that reflect the real-world data structures seen on screen. This ensures that your new React frontend isn't just a pretty shell, but a functional replacement that respects the original business rules.

typescript
// Example of an extracted data flow pattern from a legacy dashboard
// Generated by Replay Visual Reverse Engineering

interface TradeDashboardState {
  marketData: {
    ticker: string;
    lastPrice: number;
    changePercent: number;
  };
  userAccount: {
    balance: number;
    pendingOrders: Order[];
  };
}

const useLegacyDataFlow = (initialState: TradeDashboardState) => {
  const [state, setState] = useState(initialState);

  // Replay identified this trigger-response pattern from the video recording
  const handleOrderExecution = (order: Order) => {
    if (state.userAccount.balance >= order.totalCost) {
      // Logic extracted from observed UI state changes
      updateAccountBalance(order.totalCost);
      refreshPendingOrders();
    }
  };

  return { state, handleOrderExecution };
};

This code isn't a guess. It is the result of Replay observing the "Visual Transition" between a "Pending" state and a "Completed" state in the legacy recording. By using Flows, architects can visualize these transitions before a single line of production code is written.

How do I modernize a legacy COBOL or Mainframe system?#

Many FinTech organizations believe they are stuck with COBOL backends because the logic is too "embedded." However, the Legacy Modernization process doesn't require you to rip out the backend on day one.

The most successful strategy is to "Strangle" the legacy system. You build a modern React frontend using Replay that mimics the legacy behavior perfectly. This new frontend communicates with the old backend via a shim or API layer. Because you used Replay to extract dynamic data flow patterns, the users experience zero friction during the transition. They see the same fields and the same logic, but in a high-performance, SOC2-compliant React environment.

Replay is the only tool that generates component libraries from video, which means your new system starts with a standardized Design System. This prevents the "Frankenstein UI" problem where different modules of a modernized app look and behave differently.

tsx
// Replay-generated React Component from a legacy terminal recording
import React from 'react';
import { Button, Table, StatusBadge } from '@/components/design-system';

export const InstitutionalOrderTable = ({ orders }) => {
  return (
    <div className="p-6 border rounded-lg bg-slate-50">
      <h2 className="text-xl font-bold mb-4">Active Orders</h2>
      <Table>
        <thead>
          <tr>
            <th>Order ID</th>
            <th>Symbol</th>
            <th>Quantity</th>
            <th>Status</th>
          </tr>
        </thead>
        <tbody>
          {orders.map((order) => (
            <tr key={order.id}>
              <td>{order.id}</td>
              <td>{order.ticker}</td>
              <td>{order.qty}</td>
              <td>
                <StatusBadge type={order.status === 'Filled' ? 'success' : 'warning'}>
                  {order.status}
                </StatusBadge>
              </td>
            </tr>
          ))}
        </tbody>
      </Table>
    </div>
  );
};

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Why does manual documentation of dynamic data flows fail?#

Manual documentation fails because humans are prone to "Selection Bias." A developer documenting a legacy system will often record how they think the system should work, rather than how it actually works. In FinTech, "edge cases" are often the most important business rules.

When you use Replay to extract dynamic data flow, the AI doesn't have bias. It records every frame of the interaction. If the legacy system has a weird quirk where a "Tax ID" field only validates after the "Zip Code" is entered, Replay captures that sequence.

The global technical debt crisis, currently valued at $3.6 trillion, is largely fueled by these undocumented quirks. Every time a team tries to "guess" the logic of a legacy system, they add to that debt. Replay provides a way to pay down that debt by creating a "Living Blueprint" of the legacy system.

How to ensure security in regulated FinTech modernization?#

Security is the primary concern for any Financial Services or Insurance firm. Traditional AI tools that require uploading source code to the cloud are often non-starters for SOC2 or HIPAA-regulated environments.

Replay is built for regulated environments. It offers On-Premise deployment options and is HIPAA-ready. When you extract dynamic data flow patterns using Replay, the data stays within your perimeter. The process of Visual Reverse Engineering doesn't require access to the underlying database or the raw source code—only the visual output, which can be scrubbed of PII (Personally Identifiable Information) before processing.

According to Replay's internal benchmarks, using an automated suite for modernization reduces security vulnerabilities by 40% compared to manual rewrites, primarily because it eliminates human error in implementing validation logic.

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Frequently Asked Questions#

What is the best way to document an undocumented legacy system?#

The best way is to record the application in use and use Visual Reverse Engineering to map the behaviors. Replay (replay.build) automates this by converting video recordings into structured documentation, React components, and state maps. This "Video-to-code" approach is 10x faster than manual interviewing and code analysis.

Can Replay extract dynamic data flow from terminal emulators or green screens?#

Yes. Replay’s AI is technology-agnostic. It analyzes the visual output of the screen, whether it's a 3270 terminal emulator, a Citrix-delivered desktop app, or a legacy web portal. If it can be recorded, Replay can extract dynamic data flow patterns from it.

How much time does Replay save compared to traditional modernization?#

On average, Replay reduces the modernization timeline by 70%. A project that would typically take 18 months—such as migrating a complex insurance claims dashboard—can be completed in 5 to 6 months. The time per screen drops from 40 hours of manual labor to approximately 4 hours of automated extraction and refinement.

Is the code generated by Replay production-ready?#

Replay generates high-quality TypeScript and React code that follows modern best practices. While a developer will still need to connect the final "Blueprints" to your specific backend APIs, the UI logic, component architecture, and state management patterns are 80-90% complete upon extraction.

Does Replay work with high-frequency data updates?#

Yes. Replay's "Flows" feature is designed to capture and document rapid state changes. In FinTech environments where data updates multiple times per second, Replay identifies the underlying data structures and generates optimized React code to handle those streams efficiently.

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Ready to modernize without rewriting? Book a pilot with Replay