How to Write an RFP Question Set for AI Proctoring Vendors

Why Standard RFPs Miss the Risk

Standard procurement packages for proctoring tools often emphasize unit price, proctor ratios, LMS connectors, and a checklist of monitoring features. Those items matter for operations, but they do not surface how an AI proctoring system decides that a session is suspicious, what evidence supports that decision, or how biometric and behavioral signals are retained after the exam ends.

When integrity decisions are automated, a thin RFP leaves buyers comparing marketing claims instead of model behavior, data exposure, and accountability. The result is a selection that may look competitive on features and cost while remaining weak on bias testing, human review, retention controls, and incident terms.

A technically grounded question set reframes evaluation around risk: how flags are produced, who can override them, what data leaves the exam environment, and what evidence the vendor can show under audit.

Core Technical Components That Require Scrutiny

Organize the RFP around five evaluation areas so responses stay comparable and defensible across vendors.

• Model behavior How flagging logic is built, tested, and explained
• Data handling Collection, storage, retention, and deletion of biometric data
• Security architecture Encryption, access controls, and subprocessor exposure
• Governance controls Human review, bias testing, and revalidation cadence
• Accountability Audit rights, certifications, and breach notification terms

Under model behavior, ask how the system defines integrity events, whether thresholds are configurable, how face and behavior models contribute to a final score or flag, and what an administrator sees when reviewing a case. Require vendors to describe false-positive handling and whether the test-taker can receive a human-reviewed outcome before a consequence is applied.

Under governance controls, require documentation of human-in-the-loop review, bias and accuracy testing for facial recognition and behavioral models, and a model versioning and change management process that includes how threshold updates are validated before deployment.

Data Handling and Security Architecture Questions

AI proctoring commonly processes video, audio, and keystroke or other behavioral signals. The RFP should force precise answers on what is collected, why each category is required, where it is stored, who can access it, and when it is deleted.

Align retention and deletion questions to the buyer’s legal context, including BIPA, FERPA, and GDPR requirements where they apply. Ask for timelines that cover active exam use, post-exam review windows, and long-term archives, plus the mechanism used to honor deletion requests.

On security architecture, probe encryption in transit and at rest, access control design, logging of administrative access to exam media, and the list of subprocessors that touch biometric or behavioral data. Ask how isolation works between customers and what happens to data when a contract ends.

Governance and Auditability Questions to Include

Governance questions convert vendor claims into evidence buyers can file, compare, and revisit after award. Include at least the following items in the formal question set:

• What documented human-in-the-loop review occurs before an automated integrity flag results in a consequence for the test-taker?
• What bias and accuracy testing has been performed on facial recognition and behavioral models, and can results be shared with the buyer?
• What is the model versioning and change management process, including how threshold updates are validated before deployment?
• What data retention and deletion timelines apply to video, audio, and keystroke data, and how are they aligned to BIPA, FERPA, and GDPR requirements?
• What independent audit evidence exists, such as SOC 2 Type II reports or ISO 27001 or ISO/IEC 42001 certification, versus self-attestation alone?
• What are the contractual terms for incident notification timelines, audit rights, and liability in the event of a biometric data breach?

Score these answers with a consistent rubric. Prefer primary evidence (reports, sample review workflows, retention schedules, redacted model cards) over narrative assurances. Record gaps explicitly so residual risk is visible to legal, security, and academic integrity stakeholders before signature.

Structuring the RFP for a Defensible Decision

Structure the packet so technical, privacy, security, and commercial responses can be evaluated without mixing criteria. A practical layout is:

1. Scope and exam environments in scope
2. Model behavior and integrity decision workflow
3. Data handling, retention, and learner rights
4. Security architecture and subprocessors
5. Governance, testing, and change management
6. Audit evidence, certifications, and contractual accountability
7. Implementation, support, and commercial terms

Require answers in a fixed template with page limits for narrative sections and mandatory attachments for policies, sample reports, and certifications. That format reduces theatrical feature tours and makes side-by-side comparison straightforward for a cross-functional review board.

Document weighting before responses arrive. If biometric exposure and human review are non-negotiable for your institution, state that up front and treat missing evidence as a scored defect rather than a clarification round that dilutes the bar for every bidder.

Where Runtime Governance Fits After Selection

A well-constructed RFP identifies the right vendor. It does not, by itself, prove that the deployed system continues to operate inside the boundaries your evaluation established. Thresholds change, models are updated, integrations expand, and review staffing shifts after go-live.

Runtime governance closes that gap by monitoring whether production behavior still matches the assumptions captured in the RFP: human review before consequence, retention windows, access patterns, and material model or policy changes. Procurement diligence and runtime oversight are complementary controls, not substitutes.

Build the contract and operating model so the evidence you demanded during selection (audit rights, change notice, incident timelines, retention commitments) remains enforceable and observable after deployment.