Member data exposure in everyday prompts
Staff paste account numbers, Social Security numbers, and transaction details into public AI tools to draft responses or summarize cases. That data can be stored and used to train models outside your control.
Loan officers, member service reps, and back-office staff are already pasting member information into AI tools. KonaSense gives you the visibility and controls to keep member data protected while your people move faster.

AI adoption in credit unions is happening with or without approval. Every prompt, upload, and copied note is a chance for member data to leave your control.
Staff paste account numbers, Social Security numbers, and transaction details into public AI tools to draft responses or summarize cases. That data can be stored and used to train models outside your control.
When AI use is invisible, you cannot prove how member information was handled. Examiners increasingly expect AI governance evidence under NCUA Part 748 and the GLBA Safeguards Rule.
Dozens of AI tools and browser extensions enter through loan officers, tellers, and back-office staff. Most bypass the third-party due diligence NCUA expects under Letter 07-CU-13.
Loan applications, account statements, and member lists get uploaded to AI assistants. A single upload can expose hundreds of member records at once.
KonaSense protects member data at the point of use, so your teams keep the productivity of AI while compliance keeps the evidence examiners expect.
Continuous, real-time visibility into every AI interaction across the organization, whether it comes from a person or an agent.
Real-time protection against data exposure, prompt injection, and unsafe AI behavior, enforced at the point of use.
Policy control, compliance evidence, and human-in-the-loop oversight across every AI workflow.
DLP matches patterns in data and asks one question: is something sensitive here. KonaSense Skills understand the intent, role, and consequence behind each AI interaction, so they can block, coach, or require human approval based on what is actually happening. Skills are configurable to the specific challenges of your business.
Staff pasting member PII into public AI to draft responses
Exemplo de prompt“Draft a reply to this member: SSN 412-88-3391, account 90231, past-due auto loan, balance and transactions below.”
Resposta da KonaSenseKonaSense redacts the SSN, account number, and transaction details inline and coaches the rep to the approved, NCUA aligned assistant before anything reaches a public tool.
Por que o DLP não pega issoPattern based DLP might flag an SSN, but it will not steer the rep to a safe workflow or preserve the evidence an examiner expects.
Loan applications and member lists uploaded to unvetted AI assistants
Exemplo de prompt“Upload this loan application PDF and member list spreadsheet and summarize the risk.”
Resposta da KonaSenseKonaSense detects bulk member records in an upload to an unsanctioned tool, blocks the exfiltration at the point of use, and records the attempt for NCUA third-party due diligence evidence.
Por que o DLP não pega issoEndpoint DLP struggles with document uploads to browser based AI and cannot produce the governance evidence NCUA expects under Letter 07-CU-13.
KonaSense sensors intercept AI interactions wherever they happen, with no code changes required and deployment in under a day.
Chrome and Edge sensor covering ChatGPT, Gemini, Copilot, Claude, and more than 50 AI tools. It intercepts prompts, uploads, and responses in real time with block, redact, and coach actions at the point of use.
Mais informações →Real-time governance for developer AI agents across VS Code, Claude Code, GitHub Copilot, Cursor, Codex, and Codex CLI. It intercepts tool calls and agent actions before execution with cryptographic audit evidence.
Mais informações →Get the AI Risk Brief for Credit Unions and see how member owned institutions govern AI use while staying NCUA aligned.