Edwy

Fintech primer

Fintech and Trading AI Primer

A scaffolded Phase 3 learner journey for regulated trading AI evaluation, on-prem constraints, supervision and evidence review, audit-grade decision loops, and AI literacy inside market-facing teams.

For the family-office CIO, asset manager, and treasury-desk leader evaluating institutional decision AI.

Local and external decision boundaries connected by a governed bridge
Draft for Pooneh review: governed deployment boundaries.
Primer walkthrough videoRecording in progress
Recording slot. Pooneh and Nima will replace the ID and transcript after recording.

Transcript field ready for curriculum authoring.

8 modules
Test your understandingView Wilfrid course paths
  1. Module 1What AI actually does inside a trading workflow in 2026For family-office CIOs, asset managers, and treasury-desk leaders who need plain language before demos set expectations.
  2. Module 2How institutional decision desks evaluate AI toolsFor CIOs and asset-management leaders comparing AI claims against governed decision obligations.
  3. Module 3Why on-prem matters for regulated trading AIFor decision-desk teams whose data and review environment cannot assume cloud-only paths.
  4. Module 4What NI 31-103, SEC, and FINRA rules mean for AI evaluationFor institutional evaluators translating regulatory and supervision obligations into tool questions.
  5. Module 5Audit-grade trading AI at the decision loopFor decision-desk leaders who need audit-grade to mean more than a retained log.
  6. Module 6Reading the AI hype cycle for finance marketsFor market-facing teams who need to separate real assistance from vapor.
  7. Module 7When AI helps decision-loop explainability and when it does notFor treasury and asset-management teams deciding where explanation support is appropriate.
  8. Module 8Where AI literacy needs to grow inside a treasury or asset-management teamFor leaders turning executive curiosity into shared institutional evaluation discipline.

Fintech understanding check

0 of 3 questions completed locally.

1. Institutional decision AI should be evaluated only by the quality of a demo.

Answer feedback appears here.

2. Why can local deployment boundaries matter for regulated market-facing teams?

Answer feedback appears here.

3. Name one reviewable decision-loop artifact.

Answer feedback appears here.

Wilfrid handoff

Go deeper when Wilfrid is ready

Wilfrid is the course tutor we're building for the Fintech / trading vertical. Edwy keeps this public primer lightweight; Wilfrid is where a future learner can practice the topic in depth.

I read all of this - what now?

Read the full Fintech primer and want to talk about institutional decision infrastructure? Get in touch about Egbert. Barg Labs is building Egbert for institutional decision infrastructure.

Fintech and Trading AI Primer | Edwy