Finance Professionals
Applied AI in Financial Services
Learn how AI is transforming the financial sector. Master process architecture, regulatory compliance, and automated workflows to reduce manual tasks and validate ideas faster.
Duration: 24h Total
Certificate of Completion
What You'll Learn
- Learn to prompt effectively for higher-quality results
- Enable faster validation of ideas, prototypes, and workflows
- Reduce manual daily tasks and improve productivity on research, analysis, documentation, and reporting tasks
- Use AI safely without exposing internal data (policies, licensing, platforms)
- Understand when AI output requires validation or expert review
- Get familiar with modern AI tools, policies, licensing, and allowed platforms
- Introduce AI-driven workflows relevant to real work environments
Curriculum Overview
Module 1
Introduction
1h- ▪Program overview, participant expectations, and baseline knowledge setting.
Module 2
AI Methodologies & Tools
2h- ▪Key terminologies (LLMs, RAG, Agents)
- ▪Model types and capabilities (Text, Vision, Multimodal, Code)
- ▪Vector databases and retrieval workflows
- ▪Tooling ecosystem (model providers, frameworks, orchestration, eval tools)
- ▪Data pipelines, governance, and enterprise integration considerations
Module 3
AI for Business Systems
3h- ▪AI-assisted extraction & structuring of business processes from docs
- ▪Mapping workflows/systems/data flows with LLM support
- ▪Identifying gaps and automation opportunities
- ▪Supporting architecture/tooling decisions
- ▪AI-assisted documentation (specs, SOPs, policies, process guides)
- ▪Traceability across requirements, processes & systems (includes BPMN, workflow, and enterprise systems examples)
Module 4
AI for Regulatory Compliance & Audit
3h- ▪AI-assisted interpretation of regulations & standards
- ▪Mapping requirements to controls/processes/systems
- ▪Evidence collection & documentation with AI support
- ▪AI-assisted gap assessments & review checklists
- ▪Workflow automation for continuous compliance
- ▪Audit simulation (queries, findings, corrective actions)
- ▪Cross-domain applicability (quality, security, data, AI)
Module 5
Industry Context: AI in Financial Services
3h- ▪Automating operational processes and internal workflows
- ▪Document-heavy workflows (KYC, audits, reporting)
- ▪Risk & anomaly detection for fraud & compliance
- ▪Customer intelligence & service automation
- ▪AI-assisted decision support for analysts & managers
- ▪Rapid tool prototyping with no-code & LLMs
- ▪Regulatory & responsible AI constraints
Module 6
Using AI in Daily Workflows
4h- ▪Principles of prompt engineering tailored for research, synthesis, structuring, and reviews
- ▪Designing reusable prompt patterns for repeated deliverables
- ▪Creating and configuring Custom GPTs
- ▪Building internal knowledge-based GPTs with files & datasets
- ▪Using LM Studio to run models locally for privacy-sensitive use cases
Module 7
Vibe Coding for Prototyping
4h- ▪Using Claude Code / Cursor for implementing prototype logic
- ▪Generating UI fragments and backend scripts through conversational coding
- ▪Building lightweight APIs or connectors for demo purposes
- ▪Iterative coding via prompt–test–refine cycles
- ▪Reducing time-to-prototype for internal or client-facing demos
Module 8
AI Tools for MVP Validation
4h- ▪Building simple UIs and app flows with no-code app builders (Bubble, Glide, Softr)
- ▪Automating workflows and data movement with Make/Zapier/n8n
- ▪Connecting APIs and LLMs to simulate backend logic
- ▪Validating product concepts through interactive demo flows
- ▪Sharing prototypes with stakeholders for quick feedback
Interested in this course?
Contact us to get the full syllabus, pricing details, and discuss how we can tailor this for your team.
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