Construction & Infrastructure Finance: From Feasibility to Financial Close
Flagship: build the complete project finance model in MS Excel and stress it with Monte Carlo simulation in Python — PPP structures, debt sizing (DSCR, LLCR, PLCR), mezzanine and bond structuring, and real cases from the Nairobi Expressway and Lake Turkana Wind Power to the Mombasa Port PPP, Kenya SGR and Heathrow T5.
The executive challenge
The problem this program solves
Africa has the world's largest infrastructure gap — and the constraint is not capital, it is bankable, well-modelled projects. Too many feasibility studies are advocacy, too many models cannot survive a lender's credit committee, and financial close is missed by months because debt sizing and risk allocation were never properly engineered. This flagship programme takes you through the full transaction lifecycle — feasibility, PPP structuring, risk allocation, debt sizing, documentation and financial close — building the complete financial model in MS Excel and stress-testing it with Monte Carlo simulation in Python, on the projects that define African infrastructure.
Context
Why this matters now
Capability
What you will be able to do
- Build a complete, investor-grade project finance model in MS Excel — revenues, opex, debt sizing, covenant headroom and the cash flow waterfall.
- Size debt with DSCR, LLCR and PLCR, and structure PPP risk allocation that governments, sponsors and lenders all sign.
- Run Monte Carlo risk simulation in Python — project IRR distributions, sensitivity heatmaps and P50/P90 debt service headroom with numpy, pandas and scipy.
- Structure mezzanine, bond and DFI tranches, and negotiate a transaction through term sheet, due diligence and financial close.
The IPAT Course Standard
The ten-day journey
Each day is a deliberate progression in managerial capability — from strategic context, to analytical frameworks, to applied practice, to executive judgement under pressure, to a capstone that produces something your organisation keeps. The ten-day format runs as two five-day residencies, extending the journey into institutional implementation.
IPAT Signature Case™
Sixty Claims and an Election Year
A national modernisation at a consumer-goods manufacturer is 40% over budget and 18 months late. The contractor has filed sixty claims; the board must choose between completion, termination for default, or a negotiated reset — before an election year.
Your decision: Choose the path, the commercial posture and the message to government and lenders.
IPAT Data Lab™
A programme portfolio at a container terminal operator cannot see which projects are quietly failing.
Dataset: Synthetic cost, schedule and quality data for a 25-project portfolio at a container terminal operator.
Your task: Diagnose the overrun drivers, separate noise from signal, and design recovery for the worst three.
A project performance dashboard and intervention plan.
Data → Analysis → Decision, not Data → Code → Certificate
IPAT DIOS™ Framework · Data Intelligence for Official Statistics & Organisations
From raw data to strategic intelligence in five phases
Software-led programmes at IPAT do not teach syntax — they teach statistical data architecture, the discipline that turns construction data into a strategic asset. The programme runs on the five-phase IPAT DIOS™ arc, adapted end-to-end to Python & pandas.
Assess
Diagnose the current state of construction data processing: a baseline of Python & pandas proficiency, data silos, manual bottlenecks and reproducibility gaps in the workflows your institution runs today.
Architect
Design standardized, reproducible data structures: consistent naming conventions, master schemas and version-controlled projects in Git, so every construction analysis stands on the same interoperable foundation.
Automate
Replace manual, error-prone steps with automated pipelines: ingest, clean and transform construction data with pandas, NumPy and SciPy, and automate with reproducible Jupyter and Quarto pipelines the routine reporting that consumes weeks of analyst time.
Analyze
Create decision intelligence: cross-tabulation with proper variance estimation, time-series visualization, geospatial mapping and predictive modelling — applied to realistic, anonymized construction data.
Accelerate
Build for what is next: AI-ready datasets, machine learning for imputation and estimation, and interactive Streamlit and Plotly dashboards that put construction intelligence directly in decision-makers’ hands.
Day 10 · The Capstone
What will you change when you return to work?
Take a live project — an expressway, a wind farm or a port terminal — from feasibility study to financial close: the full Excel financial model, the Monte Carlo risk report in Python, and the term sheet you would defend to a lending committee.
Methodology
Frameworks you will master
- • IPAT DIOS™ Framework
- • IPAT Transformation Architecture™
- • IPAT Data-to-Decision Framework™
- • Stage-gate delivery governance
- • Earned value management
- • Lean and Six Sigma foundations
Cohorts
Upcoming cohorts
New dates are being scheduled
Register with your preferred start date and our admissions team will match you to the next available cohort — or contact us to arrange an in-house delivery for your organisation.
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