Built by practitioners, for practitioners.
We build the banking models we wished existed when we needed them — commercially useful, transparent, and designed for real decisions.
The modelling gap in banking
If you work in banking FP&A, treasury, or consulting, you've seen the same problem. On one side: oversimplified templates that use flat growth rates and back-of-envelope interest calculations. On the other: heavyweight regulatory models that take months to build, require dedicated teams to maintain, and obscure the commercial logic behind layers of compliance.
Neither serves the person who needs to answer questions like: "What happens to our NIM if rates drop 100bps?" or "How does a new product launch affect our capital ratios?" or "What's our credit cost trajectory under a stress scenario?"
That's the gap we fill. Our models are sophisticated enough for real banking analysis but practical enough to use without a dedicated model risk team. Every formula is visible. Every assumption is stated. Every output is traceable.
Where our experience comes from
Banking FP&A
Balance sheet forecasting, NIM analysis, product-level P&L, and board reporting for retail and commercial banks.
Treasury & ALM
Funding strategy, interest rate risk, repricing gap analysis, FTP frameworks, and liquidity management.
Credit Risk
PD/LGD modelling, ECL provisioning, vintage analysis, stress testing, and portfolio credit quality monitoring.
Capital & Regulatory
Basel III/IV capital adequacy, RWA optimisation, ICAAP/ILAAP, Pillar 2 buffers, and recovery planning.
Derivatives & Hedging
IRS valuation, yield curve construction, hedge effectiveness, MTM accounting, and risk sensitivity analysis.
Financial Advisory
Due diligence models, acquisition financing, capital raising, strategic planning, and investor presentations.
How we build models
Eight principles that guide every model we create. These aren't aspirations — they're constraints we enforce in every workbook.
Separate inputs, calculations, outputs, and checks
Every workbook is structured by function. Blue tabs for inputs, white for calculations, green for outputs, red for controls. You always know where you are.
Monthly time periods
Banking moves in months, not quarters or years. All models use monthly granularity with a 24-month forecast horizon. Annual summaries are derived, not assumed.
Simple, robust logic first
We prefer transparent formulas over clever ones. If a simpler approach gives the same analytical value, we use it. Complexity is earned, not defaulted to.
Scenario capability built in
Every model supports Base, Upside, and Downside scenarios. Scenario drivers are separated from calculations so you can test different futures without touching the engine.
Readable formulas
No nested IF statements 200 characters deep. No hidden named ranges. Formulas are broken into logical steps with clear intermediate calculations.
No manual hardcoding in calculations
Every number in a calculation tab comes from an assumption or a prior calculation. If you need to change something, you change it once in the inputs.
Version control and release notes
Every model includes version tracking. When we update a model, you know exactly what changed and why. No mystery diffs.
Designed for non-expert users
The buyer isn't always the builder. Our models are designed so that someone who didn't create them can pick them up and start using them productively.
What these models are (and aren't)
What they are
- Commercially useful for actual decisions
- Cohort-based with behavioural dynamics
- Transparent and fully auditable
- Modular and composable
- Professional, ready to present
What they aren't
- Generic finance templates
- Academic exercises
- Regulatory compliance tools
- VBA / macro-dependent
- Oversimplified planning sheets