Professional Programme
AI for Finance Professional Programme
Build your own AI finance and AI banking agents, then design, test, govern and approve them safely inside a virtual bank, before any real money is touched.
Who it is for
Finance, treasury, risk and audit professionals, bank and corporate teams adopting AI, executive-education cohorts and MBA / PGDM finance students.
What learners come away able to do
Use AI across analysis, forecasting, risk, credit and markets, and decide when an AI agent's output may be trusted: the simulation does the maths, the agent explains, a person approves.
The programme modules
Module 1
AI concepts for finance professionals
The AI terms a finance team hears at work, in plain words: what each means for a decision, and where to try it.
Module 2
AI foundations for finance
What AI and large language models can and cannot do in finance, and how to ask them well.
Module 3
AI-assisted financial analysis and research
Use an AI analyst and a research assistant, then find the claim the AI cannot support.
- AI Financial Analyst — Find the Claim It Cannot Support
- Review the analyst's note: keep, fix or remove each paragraph
Module 4
Evidence-based AI answers
Check an AI answer against the passages it came from: what backs each claim, what has no source, a made-up circular, when to add a caveat or withhold, and what to cite.
- Evidence-based AI answers: check the sources before you trust the answer
Module 5
Forecasting and treasury AI
Choose a cash-forecast model, read its band, explain the miss, and run group cash with an agent's morning brief.
- Cash forecast: choose the model, read the band, explain the miss
- Group cash: chase the statements, sweep, pool and fix the bank limit
- Morning liquidity desk: three agent briefs to accept or reject
Module 6
AI in risk and credit
Expected loss, cover ratios and capital first, then sign off a loan agent's decisions.
- Approve, Restructure or Decline the Term Loan on DSCR
- A New Lending Book: Does the Spread Pay for the Loss and the Capital?
- Sign off the loan agent: six runs to accept or send back
Module 7
Building and testing AI agents
Design an agent's tools, instructions and limits, and test it on cases before anyone relies on it.
- Coach or cheat? Eight student-coach exchanges
Module 8
Governance, controls and human approval
Spot a planted instruction, hold a payment batch, release a large payment only under four-eyes approval.
- Spot the hidden instruction: data or a planted command?
- Check the payment agent's batch: approve, hold or reject
- Large Transaction Dual-Authorization Decision
Module 9
AI in markets and portfolio
Judge an agent's rebalance, book, refer or block its FX tickets, and make the equity analyst's call.
- Trust portfolio review: judge the agent's rebalance proposal
- Pre-deal desk: book, refer or block six FX tickets
- You Are the Equity Analyst
Module 10
AI observability and governance
Read an agent's run trace, measure its return instead of guessing it, and decide whether it stays on, is restricted, switched off or escalated.
- Read the run trace: should this agent stay switched on?
Module 11
FP&A and audit with AI
Check an AI assistant's variance commentary and journal-entry flags against the figures, then accept, correct, clear or escalate. Run the governed FP&A and Audit Agent, and approve or reject a colleague's run as the second person.
- FP&A with an AI assistant: budget against actual
- Journal-entry review with an AI assistant: investigate, clear or escalate
Module 12
Governed AI Bank capstone
Run FinTreasury Bank's agents for a day as its AI governance lead: autonomy and thresholds, the day's proposals under four-eyes, one incident, and a faculty-graded governance report. The governed morning is the counted simulation.
- Capstone: a governed morning at FinTreasury
- The Governed AI Bank
What learners do
Simulations
Accept, fix, hold or reject each AI output: analyst notes, forecasts, loans, payment batches, trades and portfolio proposals. See what a wrongly approved output would have done, and where a guardrail or a second approver stopped it.
Agents
Build an agent in the Agent Builder on a practice model, and run governed agents on FinTreasury Bank's simulated data.
Governance
Spot a planted instruction, check an AI answer against the passages it came from, hold a payment batch, release a large payment only under four-eyes approval, and apply what Indian regulators expect of AI in finance.
Capstone
Run FinTreasury Bank's agents for a day as its AI governance lead: autonomy and thresholds, the day's proposals under four-eyes, one incident, and a faculty-graded governance report. The governed morning is the counted simulation.
- Governed AI Bank capstone: one day at FinTreasury Bank
- AI Governance in Financial Services
- A governed morning at FinTreasury: sign off your agent
Certificate
Certificate of Completion — AI for Finance Professional Programme, with a Record of Completion listing each module and simulation completed, and a QR code anyone can verify. A TrezCap certificate evidences work completed on the platform; it is not an academic award.
Delivered in collaboration with your institution
Your institution brings its brand, learners, faculty and capstone review; TrezCap brings the modules, simulations, agents, marked quizzes, progress records and the verifiable certificate. Co-branded certificates are available.
Price
The programme price is on the Pricing page. Free for now. For details, write to hello@trezcap.com. Nothing to install and no coding needed.
Not covered: Connecting an agent to a live AI model: the Agent Builder runs on a practice model; Training machine-learning models such as credit-scoring or fraud models; Python or other programming; Autonomous agents acting without a person's approval.
Ready to see TrezCap in action?
Want to see what happens behind the screen? Request a demonstration and we’ll walk you through the full simulation environment.
Or write to us at hello@trezcap.com