General-purpose AI safety benchmarks were built for chatbots. FINPROOF was built for the most regulated industry on the planet — and it changes everything about how BFSI institutions prove their AI is safe.
On April 27, 2026, India's financial regulators issued Advisory No.6 of 2026. Section 5.1(b) is direct: every Regulated Entity must conduct periodic, structured risk assessments covering prompt injection and adversarial inputs on their AI systems. The compliance deadline is active. The penalty for non-compliance is not theoretical.
Here is the problem. When a Chief Risk Officer calls their AI vendor and asks "how do we demonstrate compliance with §5.1(b)?" — there is no answer. The vendor points to their score on HarmBench, or WildGuardTest, or PINT. These are credible benchmarks. But none of them contain a single example of a SEBI investment advice elicitation attack. Not one example of a KYC bypass attempt framed in banking language. Not one AML structuring query, not one RBI rate manipulation prompt, not one DPDP consent violation scenario.
A guardrail that scores 0.97 on WildGuardMix and 0.00 on FINPROOF is not safe for your banking chatbot. It is safe for Reddit.
— Zytra Tech SolutionsThe gap between general-purpose AI safety and BFSI-specific AI safety is not a matter of degree. It is structural. General models were never shown the attacks that matter in banking because nobody built the dataset to show them. Until now.
FINPROOF — the Financial Proof benchmark — is a 5,389-prompt evaluation standard covering every attack category and benign interaction type that matters for BFSI AI deployments. It was constructed in three phases: a systematic regulatory analysis of SEBI, RBI, DPDP Act, EU AI Act, and SR 11-7 to define the attack taxonomy; a quantum circuit Born machine (QCBM) generation pipeline to ensure distributional coverage; and a contamination audit confirming zero overlap with any existing public training dataset.
The benchmark covers 22 domains across two axes: BFSI regulatory compliance domains B-01..B-11 and adversarial attack pattern domains D0..D8. Every prompt maps to at least one regulatory provision by specific section number — not just framework name.
This is not a theoretical benchmark. FINPROOF was built in direct response to regulatory requirements from the Reserve Bank of India, the Securities and Exchange Board of India, and ongoing EU AI Act implementation guidance. Every prompt category maps to a specific regulatory provision or enforcement action.