AI and agents in finance
Costed use cases from front to back office, agents, tools and method for an insurer's investments.
Access: an e-mail address is enough, you receive a sign-in code. Free modules need no bank card.
What you will be able to do
- Understand language models, their limits and the difference between assistant, workflow and agent
- Write professional prompts and manage data, risk and compliance
- Map use cases from front to back and estimate their gains, with stated assumptions
- Analyse costed cases: front, middle and back office, closing, reporting, internal control
- Build and defend a business case: full costs, ROI, answers to objections
- Design, evaluate, govern and industrialise a business agent, from pilot to scale-up
Who it is for
Finance and investment departments, front, middle and back office teams and consultants preparing AI and agent projects.
Prerequisites
No prerequisites for the foundation modules; the advanced modules assume the earlier ones.
Included
- Video with chapters
- PDF slides
- Marked quiz
- Verifiable certificate
Programme
Fundamentals
- 00AI in 2026: from generative AI to agents, what has changed for finance
- 01How a language model works: strengths, limits, hallucinations
- 02Professional prompting applied to finance
- 03Overview of tools: assistants, AI embedded in business software, agent platforms
- 04Data and AI: reference data, unstructured documents, quality
- 05Risk and compliance: AI Act, GDPR, DORA, confidentiality
- 06Mapping use cases from front to back, the value / feasibility matrix
- 07What AI delivers: value levers and sourced orders of magnitude
Intermediate
- 08Front office: research, summarising manager notes, portfolio analysis, ESG
- 09Middle office: checking manager flows, reconciliations, anomalies
- 10Back office: corporate actions, coupons, OTC confirmations, margin calls
- 11Accounting close: reconciliations, entries, account substantiation
- 12Variance analysis: automated commentary on results, budget and valuations
- 13Reporting: Solvency II QRTs, management reporting, SFDR
- 14Internal control and audit: continuous controls, anomaly detection
- 15Building and defending the business case: full costs, ROI, objections
Advanced
- 16AI agents: architecture (model, tools, memory, planning) and patterns
- 17RAG and business knowledge bases
- 18Designing a business agent: tools, MCP, IT connection, multi-agent
- 19Evaluating and making reliable: tests, guardrails, human in the loop
- 20Governance of AI models: AI Act, model risk, ACPR expectations
- 21Industrialising: security, costs, operation, build or buy
- 22The AXENT method: maturity diagnostic, prioritisation, 8-week pilot, scaling up
- 23Complete AXENT Vie case: the investment department's costed AI roadmap, presented to an executive committee
Training a team? Access for several employees, on quotation. admin@axent-consulting.com