SolutionsCapital markets
AI security and governance built for capital markets.
Keep price-sensitive information out of prompts, govern third-party AI and keep a record of AI use an examiner can check.
Price-sensitive data · at the gateway: analyst-bot to ColossalX; advisor-bot held for a person before ColossalX (trade); unknown caller found calling ColossalX (found); ColossalX with data redacted, to provider A (deal code redacted).
In short
AI governance for capital markets, in ColossalX, means classifying unpublished price-sensitive information and redacting the identifiers you define from prompts, an inventory of the models, agents and AI vendors in use, SEBI cyber circulars mapped beside India DPDP and ISO/IEC 42001, and evidence of AI use, timestamped daily, that an examiner can check.
DSCI and BCG found that AI-specific controls such as formal AI governance, agent monitoring and runtime guardrails are
still being built across the sector.
The context
Why capital markets firms are looking hard at AI.
Financial firms pay the most for a breach and are attacked more often; agent attacks exploit weak access control and injection.
INR 40.9 crore
1.6 times
Over half
Capital markets
Where AI meets market data, and what holds it.
Four places where AI meets price-sensitive and client data, each held by a control.
An analyst pastes unpublished results into a prompt to an outside model.
The controlClassification marks price-sensitive data; guardrails redact the identifiers you define, both ways.
Nobody can show an examiner which AI saw which client data.
The controlLineage from gateway traffic: which agent sent which kinds of data to which model.
Third-party AI tools are in use, but nobody assessed or owns them.
The controlShadow AI is found in traffic; the vendor inventory flags tools in use, not assessed.
A research agent misbehaves and nobody can stop it.
The controlContainment on the limits you set, and the ColossalX Kill Switch at 4 scopes.
Regulators and frameworks
What regulators ask for, and how ColossalX relates.
Mapped frameworks, what each asks of a market firm, and the dates that matter.
Mapped to
- SEBI cyber circularsSEBI cyber circularsCyber security and resilience controls for regulated securities market entities.
- India DPDPIndia DPDPConsent and purpose limits for personal data, with consent managers.
- ISO/IEC 42001ISO/IEC 42001An AI management system: policy, roles, risk and controls.
- NIST AI RMFNIST AI RMFGovern, map, measure and manage AI risk across its life.
- SOC 2SOC 2Security, availability and confidentiality controls, evidenced over time.
- EU AI ActEU AI ActFor firms serving the EU: duties scaled to risk, from transparency up.
Regulatory clock: 13 Nov 2026 India DPDP consent manager rules start (PIB, DPDP Rules 2025); 13 May 2027 India DPDP core obligations start (PIB, DPDP Rules 2025).
What you see
What you see, and what you can show an examiner.
An identifier replaced before a prompt left the firm, beside the evidence pack an examiner can check.
An illustrative governed chat: an Indian tax identifier (PAN) in a message is replaced with a token before it leaves, so the model only ever sees the token, and the answer shows that the PAN was redacted and which group model answered.
3notes
- Identifier replaced before sending
- The redaction, shown on the answer
- The group model that answered
Evidence pack · an outline: Inventory Models, agents and vendors, owned; Lineage Which data reached which model; Runtime Redactions, refusals, approval holds; Audit A sealed, timestamped archive. Graded A to D.
What the evidence pack shows4
- Which agent sent which kinds of data to which model, drawn from gateway traffic.
- Each redaction, refusal and approval hold, with the policy that made it.
- Third-party AI in use but not assessed, carried into the risk register as owned work.
- Evidence graded A to D, verified by a second person and timestamped daily.
Honest by design
What we will not tell you.
Redaction · only what is defined: research-agent to provider A · outside model, "Draft talking points on the unannounced merger". Checks: Your deal-code patterns passed, Personal data presets passed. Verdict: allowed, No defined pattern matched.
x, not measured
Redaction finds the identifiers its presets and your own patterns describe, not ones nobody defined.
All 4 limits
- SEBI's AI and ML guidelines were still a consultation when reviewed; ColossalX maps the cyber circulars.
- Provider and model kill switches catch the requests that name that provider or model.
- ColossalX holds no certification and is delivered as SaaS only.
Questions
Questions buyers ask
What has SEBI proposed for AI and ML use?
SEBI consulted on guidelines for responsible use of AI and ML in Indian securities markets, proposing senior-management accountability, testing and monitoring, audit trails and accountability for third parties. No final circular had been found when this page was last reviewed. ColossalX maps the SEBI cyber circulars and keeps the inventory, lineage and evidence those proposals point to.
How do we keep unpublished price-sensitive information out of AI tools?
Classify it and define the identifiers that mark it. ColossalX classification covers unpublished price-sensitive information, guardrails at the AI gateway redact the identifiers you define in prompts and answers, and shadow AI discovery finds the AI tools used around the gateway. Data lineage then shows which agent sent which kinds of data to which model.
What audit trail of AI use does ColossalX keep?
The AI gateway keeps a decision record per request, and data lineage shows which agent sent which kinds of data to which model. Session recordings replay an agent request by request. Evidence is graded A to D, timestamped daily and withdrawn, never deleted, and audits end in a sealed, timestamped archive.
Which SEBI circulars does ColossalX map?
ColossalX maps its controls to the SEBI cyber circulars and assesses them from live signals, with one score per framework trended nightly, beside India DPDP, ISO/IEC 42001, NIST AI RMF, the EU AI Act, SOC 2 and GDPR. Frameworks are mapped to and assessed against, never certified, and jurisdiction-pack content is a starting point for your counsel.
Can we govern third-party AI vendors?
Yes. The risk register keeps an AI vendor inventory that flags vendors in use but not assessed, shadow AI discovery finds AI services nobody approved, and threat intelligence matched to your vendors and models turns a warning into a recorded decision, which can become a restriction at the gateway.
Next step
Know your x before the examiner asks.
See ColossalX on a market firm's questions: which AI saw which data, and what you can show an examiner.
- 01Tell us what you run
- 02See the four verbs on it
- 03Decide where to start