Handbook / Catalogues / Financial Services
For institutions where "usually right" is not a release criterion.
Cohorte's programs for banks, insurers, asset managers, and fintechs. Built on the founder's published research in conformal prediction and self-consistency. Designed to survive the regulators you actually answer to.
Why FS needs different training
In a bank or insurer, an AI output is not "a nice generation." It is a credit decision, a fraud flag, an underwriting note, a suitability assessment, a transaction-monitoring alert. Each is governed. Each has a regulator. Each has a model-risk function whose job is to ask: what does this system do when it is wrong, and how would you know?
The supervisors named the gap.
Both regimes require documented evaluation, verification, and ongoing monitoring of any model influencing a business decision. Most "AI training" programs teach the model. They do not teach independent validation, ongoing monitoring, or governance.
Two regimes, one operational obligation.
DORA (in force since January 2025) covers ICT third-party risk. The EU AI Act puts most credit-scoring and insurance pricing into the High-Risk Article 6 category, triggering Articles 12 (logging), 14 (human oversight), 15 (accuracy/robustness).
The market is moving.
JPMorgan deploys LLM Suite to ~200,000 staff under strict access controls. Goldman has GS AI Platform with internal evaluation gates. The question is no longer "should we train on AI." It is "how do we train on AI without breaking model risk."
Why Cohorte
The methodology your model-risk team is going to ask for, taught by the practitioner who published it.
"Provably right within stated bounds."
The mathematical primitive that converts a model output into a statistically rigorous confidence interval. The closest existing analogue to the VaR / ES discipline already familiar to a market-risk team.
Source: "Conformal Prediction for Trustworthy LLM Outputs," arXiv 2604.04561.
Detecting confabulation.
If the same prompt run five times produces five different answers, the model is not reasoning. The verification gate that catches this before output reaches a customer-facing channel or a regulator-facing log.
Source: "Self-Consistency as an Operational Verification Layer," arXiv 2604.11623.
The red team your CISO asked for.
Prompt injection. Indirect injection through retrieval corpora. Tool-call hijacking. The systematic taxonomy your security team uses to scope penetration testing of an LLM application.
Source: "Exploitation Surface of LLM-Enabled Agentic Systems," arXiv 2604.04230.
Open-source. Inspectable. Yours.
TrustGate (verification gates), Guardrails (policy enforcement), Agent-Auth (authorization), Agent-Monitor (observability). Six public repositories. Your engineers can audit the layer before deploying it.
Where: github.com/Cohorte-ai.
The use cases we train against
The AI work financial institutions are actually shipping in 2026.
| Use case | Where it sits | Risk category | Verification primitive |
|---|---|---|---|
| Customer service copilot | Retail bank, insurer | Conduct & mis-selling | Self-consistency, response guardrails, escalation gates |
| Underwriting assistant | Life / P&C insurer | AI Act high-risk · fairness | Conformal bounds, adversarial fairness tests |
| Credit memo drafting | Commercial / corporate bank | Credit risk · disclosure | Source attribution, citation-grounded generation, audit logs |
| KYC / AML alert triage | Compliance, financial crime | AML & sanctions | Decision logs, human-in-the-loop gates, explanation generation |
| Suitability assessment | Wealth, retail brokerage | MiFID II suitability | Rule-based gates, output classification, regulator-facing logs |
| Fraud / transaction monitoring | Payments, retail bank | SR 11-7 / SS1/23 | Conformal anomaly bounds, false-positive tracking |
| Equity research / sell-side notes | Asset manager, sell-side | Disclosure · market abuse | Source attribution, content classifier, publication gate |
| Code generation for trading systems | Quant, market risk | Model risk | Static analysis, regression evaluation |
| Internal knowledge agent | Bank-wide | Conduct · IP leakage | Access control, DLP gates, query auditing |
The FS portfolio
Same operating layer underneath every program. Vertical-specific tuning bends the exercises and the regulatory annex. Pricing is fixed; scope is negotiable.
FS Pilot · €8K–€12K · 4 weeks
Verification scopingFS Team Bootcamp · €4,200/seat · 12 weeks
Private cohortFS Curriculum License · €12,000 / year
Up to 25 seatsFS AI Readiness Program · from €35,000 · 3-6 months
Assessment + advisory + playbookThe FS objections we always hear
Asked, answered, on the table.
"You don't have a named retail-bank reference."
Correct. PwC is the closest analogue (60+ systems, 4,000 Copilot users, governance built in). For FS buyers needing a named-FS reference, the Pilot is the right entry point.
"Our model-risk team has SR 11-7 expectations you may not meet."
Curriculum is explicitly mapped to SR 11-7 §III and SS1/23 principles 1 through 4. We walk your model-risk team through the mapping on the discovery call.
"We have an internal AI / ML team."
Good. We are not a replacement. Internal teams teach the stack; Cohorte teaches the operating discipline (taste, scope, verification, governance) that internal teams typically do not own.
"We need on-site delivery inside the firewall."
Supported. AI Readiness assessment and two of four Team Bootcamp sessions on-site in Paris, London, Frankfurt, Amsterdam, Brussels, Casablanca. No Cohorte infrastructure dependencies.
"Procurement / vendor risk has a 60-day onboarding."
The Pilot is the way around this: fixed-price, fixed-scope, often clears procurement under a faster threshold. We have run Pilots while full vendor onboarding is in progress.
"AI training is not in this year's budget."
Cohorte is not Qualiopi-certified today (in progress, 2026 roadmap), so direct CPF and direct OPCO funding aren't available right now. The standard path is direct L&D budget; OPCO-routed engagements go via a Qualiopi-certified partner. The Pilot at €8K-€12K typically fits inside discretionary spend mid-year.
Bring your worst FS use case.
Suitability copilot. Credit memo. KYC triage. Fraud assistant. €8,000 fixed. Four weeks. The brief that survives the model-risk meeting.