AI Data Security · Financial Institutions
How Do You Show Proof of
AI Governance When the
SEC Asks?
Sanctioned AI, shadow AI and autonomous agents are already moving client records, trading data and privileged deal information through your institution.
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Why Now
Financial Services AI Adoption
Has Outrun Governance
Banks, broker-dealers, wealth managers and insurers run sanctioned AI across the front, middle and back office, usually faster than compliance can track. The data it moves is specific: client PII, trading records, underwriting files, M&A information and proprietary model code, already inside the production workflows your institution is examined on.
Three AI Channels Your Governance Has Never Seen in One Place
Sanctioned platforms, unapproved tools and autonomous agents each create a different kind of exposure, and each needs to be governed on the classification policy your institution already built, not a separate one bolted on for AI.
Copilot and ChatGPT Are Inside Your Client Data
Extend your existing classification policy to prompts, responses and file uploads across ChatGPT Enterprise, Copilot and AWS Bedrock. MIP tagging stops Copilot from surfacing credit files, M&A documents or account records it was never cleared to reach — with zero reclassification.
Personal AI Accounts Are Already on Your Trading Floor
Unsanctioned tools, personal accounts and browser extensions are discovered and ranked by risk level. Analysis distinguishes personal from corporate accounts, and enforcement runs inline, blocking data exfiltration via unknown AI applications in real time.
Agents Connect Directly to Your Systems of Record
The AI Agent Gateway sits inline between every agent and its applications, and no agent holds the credential directly. Field-level DLP redacts sensitive fields before the agent reads them, write operations await human approval, and every transaction is logged with dual attribution.
Regulatory Proof
Hand Over Hard Evidence, Not a Story
For financial institutions, AI governance is no longer a security initiative compliance hears about afterward. SEC AI disclosure expectations, DORA, NIS2, GDPR and the EU AI Act have made it a board-level, examinable obligation, and most institutions cannot yet produce the record.
What a Regulator, Auditor or Board Asks For
Which AI tools and agents touched sensitive or regulated data, and when What policy decision was made, and what action followed it Who authorized it, human or agent, and who can be held accountable Whether the answer covers activity from before the tool was even in place
What the Platform Produces
A closed-loop record: detection, policy decision and enforcement action logged together for the same event, not detection alone Dual attribution on every agent action, resolving to both the agent and the triggering person Exportable in CSV, JSON or PDF, or sent directly into your SIEM Historical backfill, so the record covers activity that predates deployment, not only what happens next
Evaluation Questions
Most Vendors Show a Dashboard. Few Show an Enforcement Action
Before naming a vendor, financial institutions are better served asking the architecture questions directly. The category has largely converged on visibility. It has not converged on enforcement.
Before or After the Request
Is data classified before AI reaches it, or only inspected after a prompt has already been sent?
How Deep Does Protection Go?
Does coverage stop at the network edge, or does it reach API-based sanctioned AI and agent-to-application calls a proxy never sees?
Automated Action or Manual Review
Is the response inline enforcement, or a posture report someone has to act on later?
Agent Identity and Access
When an agent calls a business application, does it hold that application's credential directly, or is the credential brokered so a compromised agent cannot authenticate on its own?
Extend Existing Controls or Start Over
Does extending coverage to AI require a new classification taxonomy, or does it inherit the one your institution has already spent years tuning?
Discovery without control is just a risk report. Classification without enforcement is a report, too. The deal is decided on what actually stops data from leaving.
Why It Works
Built on Your Existing Classification. Live in Under 60 Minutes.
Zero reclassification, nothing
to rebuild
Existing DLP taxonomy, including financial-data classifiers such as PAN, account numbers and trading records, alongside PII, source code and credentials, extends to every AI channel automatically. No new taxonomy. No retrained classifiers.
Guided by ARIA, under 60 minutes from first login
Forcepoint's onboarding assistant walks an admin from first login to a governed AI environment in under 60 minutes, with no professional services engagement, and recommends a starting policy set based on region, industry and data sensitivity.
Backfilled, not blank; one record from day one
Historical backfill surfaces AI activity that happened before the connector went live, so the dashboard, and the audit trail, is not starting from zero the day it is turned on.
AI Data Security · Financial Institutions
See What You Could Show a Regulator Tomorrow
A populated dashboard on day one, not a slide deck: your sanctioned AI, your shadow AI and your agents,
on one policy, one console and one audit trail.