Atlantic Capital Partners
How a mid-market investment bank secured AI adoption across trading, advisory, and portfolio management — without blocking the tools analysts depend on.
AI adoption outpaced security controls.
Atlantic Capital Partners — a mid-market investment bank with operations across wealth management, M&A advisory, and institutional trading — had a productivity problem masquerading as a security risk.
Financial analysts were pasting client portfolio data, M&A deal memos, and earnings projections into ChatGPT to draft client reports and summarize due diligence documents. Software engineers were using GitHub Copilot with access to proprietary trading algorithms and internal API credentials. The firm's CISO identified the exposure during a routine access review: sensitive financial data was flowing to external AI model endpoints with no inspection, no policy enforcement, and no audit trail.
The risks were concrete. CUSIP securities identifiers in AI prompts could constitute material non-public information disclosure. Client SSNs and credit card numbers in conversation logs created regulatory exposure under SEC Rule 17a-4 and PCI-DSS. M&A deal terms in AI training data could trigger insider trading investigations. And the firm had a SOC 2 Type II audit approaching in 90 days.
Blocking AI tools entirely wasn't an option — analyst productivity had measurably improved since adoption. The firm needed to keep the tools and eliminate the risk.
Arbitex Gateway — deployed in-path across ChatGPT and Copilot traffic.
Atlantic Capital deployed Arbitex Gateway as the enforcement layer between their employees and external AI providers. All ChatGPT and GitHub Copilot traffic routes through the gateway, where every request and response is inspected by the 3-tier DLP pipeline before any data reaches a model endpoint.
The security team configured six DLP rules targeting the firm's highest-risk data categories:
CUSIP identifiers, M&A deal keywords, and client portfolio data trigger BLOCK actions — the request never reaches the model. SSNs and credit card numbers trigger REDACT — the sensitive values are replaced with placeholders before the model processes the request, preserving analyst workflow while eliminating data exposure. Internal financial projections use AI-powered contextual validation to distinguish between public market commentary and proprietary earnings models.
Identity integration via SAML 2.0 ties every AI interaction to a specific user, department, and role. The tamper-proof audit log provides tamper-resistant evidence for compliance reviews, mapping every enforcement action to the relevant regulatory control.
Measurable impact in the first 30 days.
Within the first month, Arbitex processed over 15,000 DLP scans per day across the firm's AI traffic. The gateway blocked 94 incidents where CUSIP identifiers, M&A deal terms, or client portfolio data would have reached external model endpoints — each one a potential SEC violation that was prevented transparently, without disrupting the analyst's workflow.
The firm passed its SOC 2 Type II audit with the Arbitex audit log serving as the primary evidence for AI data governance controls. Auditors noted the tamper-proof audit trail integrity and the ability to reconstruct the full enforcement history for any user, any interaction, any time period.
Zero data breach reports were filed in the six months following deployment. Analyst productivity — measured by report turnaround time — remained at post-AI-adoption levels, confirming that governance and productivity were not in conflict.
“We were 90 days from a SOC 2 audit with no visibility into what our analysts were sending to AI tools. Arbitex gave us enforcement and an audit trail in the same deployment. Our auditors got the evidence they needed, our analysts kept the tools they depend on, and I stopped losing sleep over CUSIP identifiers in ChatGPT logs.”
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