GCC APPLIED AI CURRICULUM — FINANCIALS TRACK
A rigorous, audit-first curriculum designed for GCC Financial Analysts, Controllers, and FP&A leaders. Empowering finance teams to compress monthly close commentary, variance triage, and dashboard reporting while maintaining strict GAAP/IFRS numeric integrity.
Establishes the core grounding methodology that prevents hallucinated financial metrics. Teaches analysts how to construct prompt templates with explicit citation tags and strict human review gates.
You are a financial analysis assistant. RULES: 1. ONLY reference numbers present in the VERIFIED_TABLE below. 2. DO NOT perform calculations. Use only pre-computed metrics. 3. Every claim must cite the exact Table Row ID. [VERIFIED_TABLE] Row 1: Gross Margin FY25 = 42.4% (+180 bps YoY) Row 2: Operating Cash Flow = $14.2M (94% EBITDA conversion) [/VERIFIED_TABLE]
Trainees are paired in Route A (Finance Pro) + Route B (Data/Tech Analyst) pairs. Finance leads the domain/audit correctness; Data leads pipeline automation.
| Day & Session | Time | Module / Activity | Dual-Track Learner Responsibility |
|---|---|---|---|
| Day 1 • Morning | 09:00 – 11:30 | M1: AI-Assisted Financial Analysis (DuPont) | Finance sets ratio definitions; Data builds prompt bindings. |
| Day 1 • Mid-Day | 11:30 – 14:00 | M2: Automated Reporting & GL Narratives | Finance defines variance materiality; Data sets JSON schema. |
| Day 1 • Afternoon | 14:30 – 17:30 | M3: FP&A Forecasting & Driver Scenarios | Finance specifies business drivers; Data tests LLM sensitivity. |
| Day 1 • Evening | 17:30 – 19:00 | M4: Spreadsheet AI & Copilot Formulas | Hands-on natural-language formula build & verification spot-checks. |
| Day 2 • Morning | 09:00 – 12:00 | M5: Python for Finance & pandas Pipelines | Data codes trial-balance parser; Finance verifies reconciliation ties. |
| Day 2 • Mid-Day | 12:30 – 15:00 | M6: LLM-Powered Variance Root-Cause Triage | Building automated exception commentary with sign-convention checks. |
| Day 2 • Afternoon | 15:00 – 17:00 | M7: Automated CFO Dashboards | Feeding real-time GL variance commentary into executive dashboards. |
| Day 2 • Capstone | 17:00 – 19:00 | M8: Live Capstone Demo & Defense | Live run of automated reporting pipeline judged against 100-pt rubric. |
Designed specifically for corporate GCC Controllers, FP&A Managers, and Shared Services teams who work exclusively in Microsoft 365, Excel Power Query, Power Automate, and Power BI.
Drag-and-drop ingestion of 12 subsidiary CSVs, automated unpivot, and debit-credit tie-out checks in 4 minutes with zero code.
Prompting Copilot in Excel for complex nested XLOOKUP/LAMBDA formulas with mandatory 3-step manual verification.
Automated workflow triggering on new trial balances, generating Copilot variance commentary, and routing approval cards to Teams.
Embedding dynamic AI commentary blocks directly beside executive CFO dashboard visuals that refresh automatically.
Runs 100% within your existing corporate Microsoft 365 / Google Workspace licenses. No local admin rights, no command-line tools, and no software installations needed on locked-down enterprise laptops.
Test the real-time transaction risk scoring rules taught in Module 5 and the FDE Lab series.
class FinTechRiskEngine:
def evaluate_transaction(self, tx: Dict[str, Any]) -> Dict[str, Any]:
risk_score = 0.10
if tx["amount"] > (tx["historical_daily_avg"] * 4):
risk_score += 0.45
if tx["location"] == "INTERNATIONAL":
risk_score += 0.30
decision = "DECLINE_AND_ALERT" if risk_score >= 0.75 else "APPROVE"
return {"risk_score": risk_score, "decision": decision}
Every capstone is judged by the Course Director panel on a live running pipeline. Minimum pass: 60 pts. Controls minimum: 13/25.
Measured (not estimated) manual baseline hours, frequency, and error rate before AI automation.
Every AI claim is explicitly bound to a source GL line or verified ratio. Demonstrates reproducible pipeline.
Named human reviewer checklist, verification protocol, and fallback handling when data is stale.
Strict adherence to sign conventions (F/U), DuPont ratio tie-outs, and defensible materiality gates.
Live end-to-end execution during defense with demonstrated time compression metrics.
"Transforms informal AI usage into an auditable, controller-approved operating discipline with strict human review gates."
"Ensures that every AI commentary ties out to verified General Ledger lines — built for external audit acceptance, not toy demos."
"Directly closes the onshore productivity challenge by equipping delivery teams with working Python and spreadsheet automations."