Chatham Cuts Trade Validation to Under 4 Minutes With OpenAI

Overview

Chatham Financial, a leading advisor on complex capital markets decisions, has significantly reduced the time required for trade validation by integrating OpenAI’s advanced language models into its operational workflows. By leveraging Codex for software development and GPT-5.6 for AI-driven features, the firm has cut validation times from approximately 30 minutes to under 4 minutes per transaction.

This efficiency gain is part of a broader strategic shift at Chatham, which aims to transform proven processes into governed, repeatable workflows. The initiative allows the firm’s experts to focus less on routine execution and more on high-value client advisory services. The results underscore how financial institutions are moving beyond using AI merely as a speed multiplier, instead reengineering workflows to prioritize judgment and accuracy.

Redesigning Trade Validation with Process Zero

At the heart of Chatham’s efficiency gains is Process Zero, a reengineering consulting service that redesigns workflows around desired outcomes rather than historical habits. For trade validation, the firm identified the minimum inputs and evidence required, determined where human judgment was essential, and decided how AI tools could support the process.

Trade validation is a critical control function. Chatham’s Controls and Data Integrity team ensures that every system record accurately reflects both what the client authorized and what was actually executed. Discrepancies in this data can lead to significant financial and compliance risks.

Using Codex, Chatham developed a custom trade validation application. This tool automates the gathering of supporting transaction evidence and compares key terms to flag discrepancies for human review. The application is currently being rigorously tested against results produced by experienced human reviewers to ensure reliability before wider automation.

“In early measurement, the application reduced review from approximately 30 minutes to under 4 minutes. Just as important, we are validating its performance against real transactions and experienced reviewers before we expand automation.” — Alex Nordlinger, Co-head of Chatham’s AI Advisory practice

The firm emphasizes that accuracy and auditability remain paramount. The goal is not simply to speed up the current process but to produce easier-to-audit and more accurate results. Chatham plans to extend this application to additional trade types and automate more of the workflow while maintaining strict professional oversight.

Scaling Employee-Built Applications

Chatham’s adoption of OpenAI technology is not limited to centralized IT projects; it is deeply embedded in the daily workflows of its employees. Staff members use ChatGPT and Codex for research, analysis, drafting, and software development. This widespread internal adoption has fostered a culture of innovation where employees act as builders as well as users.

Through an internal platform called Chatham Vibes, employees create tailored applications to solve specific work challenges. These applications leverage a range of AI models, with GPT-5.6 Terra serving as the default for AI features and GPT-5.6 Sol available as an optional upgrade for more complex requirements.

These employee-built tools are increasingly supporting client-facing workflows. Examples include applications that help teams review maturing-cap trades, prepare pricing workbooks, generate fixed-income rate sheets, and produce hedging dashboards. In these scenarios, the AI handles data aggregation and initial analysis, while Chatham professionals apply market context, client understanding, and professional judgment to refine the output.

“We are not approaching AI simply as a faster way to run every process. With OpenAI, we can start with the outcome we want, identify where judgment matters, and design the best way to deliver it using the capabilities now available.” — Matt Henry, Chief Executive Officer, Chatham Financial

This hybrid model ensures that AI serves as a practical tool that augments human expertise rather than replacing it. The firm’s professionals evaluate the AI-generated work, make necessary refinements, and determine what ultimately reaches the client.

Building Chatham Onyx with AI

A cornerstone of Chatham’s technological strategy is Chatham Onyx, its next-generation capital markets operating system. Onyx brings assets, debt, and derivatives into a unified environment where clients and advisors can work from connected, governed data. Crucially, the platform allows for AI-assisted analysis without losing traceability to the underlying source data.

Codex plays a vital role in the development lifecycle of Onyx. Teams use the tool to plan, build, test, document, and review software, effectively shortening the path from concept to durable product capability. This approach allows Chatham to iterate quickly while maintaining high standards for accuracy, security, and accountability.

“Codex is helping our teams turn product vision into working capabilities more quickly, while our standards for accuracy, security, and accountability remain the same.” — John DeGuenther, Chief Technology Officer, Chatham Financial

Onyx leverages a tiered model architecture to optimize performance and cost. Tasks requiring simple analysis or non-production testing are routed to more cost-effective models like GPT-5.4 and GPT-4.1. In contrast, complex tasks that demand maximum accuracy and value are handled by GPT-5.6 Sol and GPT-5.6 Terra.

One notable feature built on this infrastructure is ChatFIN. This tool summarizes patterns in historical market data, helps users understand their portfolios, and locates and links to legal documents for debt, derivative, and lease terms. By providing easy access to information and insights, ChatFIN allows advisors to spend more time interpreting data and applying it to specific client situations.

Creating Capacity for Expert Work

The overarching goal of Chatham’s AI integration is to reclaim time for its most valuable asset: its experts. By using OpenAI for structured comparisons, evidence organization, exception identification, and efficient information exploration, the firm reduces the administrative burden on its professionals.

This shift allows advisors to spend less time assembling information and more time on activities that require deep subject matter expertise. These include interpreting complex data, managing difficult cases, and providing strategic advice to clients.

Chatham’s leadership views this not just as a technological upgrade but as a fundamental change in how expertise is delivered. The constraint has never been a lack of knowledge within the firm, but rather the hours experts spend on preparatory tasks before they can apply their judgment.

“Our constraint has never been expertise. It is the hours our experts spend getting to the point where they can apply it. OpenAI is helping us take those hours back, and the further we go, the more time our experts can spend applying their judgment where it creates the most value for clients.” — Mike Noonan, Co-Chief Operating Officer, Chatham Financial

Looking ahead, Chatham plans to expand trade validation across additional product lines, continue refining the ecosystem of employee-built applications, and utilize Codex to develop new capabilities for Onyx. As these initiatives mature, the firm expects to further enhance the speed, accuracy, and value of its capital markets advisory services.