Research on how AI answers for regulated enterprises

Learn how internal AI validation checks selected chatbot answers against approved facts and procedures, and where it fits within AI governance.

The FCA Board-commissioned Mills Review recommends examining how general-purpose LLMs outside the perimeter influence retail financial decisions.

Public AI answers about your institution and the AI you deploy are two governance surfaces. The difference is control and evidence access, and what that changes.

EU AI Act Article 50 — the AI-transparency rules from 2 Aug 2026 — marks AI content as AI-made, but not whether it's accurate about your institution. Where the gap is.

AI governance solutions govern the AI you deploy — but not the public AI answering customers about you. Lawnise on governing that external answer-risk surface.

Is ChatGPT accurate? Trust it on general, settled knowledge — verify anything specific, current, or organisation-level. Lawnise's practical trust-vs-verify guide.

How Lawnise verifies public AI answers against official sources before turning a flagged answer into a published research finding.

A German court has provisionally enjoined Google over false statements in its AI Overview. Lawnise reads the non-final ruling as an early signal about public AI answer governance.

ChatGPT is strong on general knowledge, but specific, current facts about an organisation need verification. Lawnise explains the contextual accuracy gap.

Contextual accuracy is whether an AI answer is correct about your specific case, not merely correct in general. Lawnise explains why that distinction matters.

A cross-market Lawnise barometer: read together, our readings of Singapore banking, Singapore insurance, Malaysian banking and Malaysian insurance show one pattern — the facts firms and schemes have already published are right, and a recurring few public-AI answers restate them wrong, where a customer acts. One pattern, several markets; a growing program, not a single accuracy score.

A Lawnise barometer of how accurately public AI answers questions about Malaysian insurance. This reading's certified findings concern complaint-escalation timing, which unit begins a complaint, and what the protection scheme covers, alongside accurate handling in the reviewed examples. As of August 2026.

A Lawnise barometer of how accurately public AI answers questions about Malaysian banks. This reading's certified findings concern public AI reaching for the wrong country's institutions, a complaint pointed at a body that is not the regulator for it, and the national credit system misdescribed, alongside accurate handling in the reviewed examples. As of August 2026.

A Lawnise barometer of how accurately public AI answers questions about Singapore's insurance sector. This reading's certified findings concern a complaint routed to another market's ombudsman, a complaint timetable taken from another market, and an omitted accident-response standard, alongside accurate handling in the reviewed examples. As of August 2026.

Public AI assistants now answer customers' questions about your institution — and often get the product, price, complaint timeline, or fraud channel wrong. You can't see or edit those answers, yet the consequences land at your door. This explainer makes the case that their accuracy is a governance surface you already own, and lays out the loop for governing it.

A Lawnise barometer of how accurately public AI answers questions about Singapore banks. This reading's certified findings concern the e-payments protection boundary, who the guidelines cover, and the scope of the Shared Responsibility Framework, alongside accurate handling in the reviewed examples. As of August 2026.