Technical Guides

Due Diligence Process

The due diligence process ties together every workstream and posture covered elsewhere on this Knowledge Centre into a single, phase-gated timeline — from a non-binding letter of intent through confirmatory diligence, transaction documentation, and the final approval gates a transaction must clear before closing. This guide sets out that end-to-end sequence explicitly, including where investment committee review, lender review, and independent assurance each sit within it, and how transaction documentation accumulates in parallel with the diligence findings that inform it.

Dynamic Arrays and Power Query in Financial Modelling

Dynamic arrays and Power Query are the two Excel capabilities that have changed most significantly since the structural conventions in the FAST Standard and the ICAEW Financial Modelling Code were first written. Dynamic array functions such as SORT, FILTER, and UNIQUE let a single formula return and automatically resize a range of results, replacing formulas that previously had to be copied down or entered as legacy array formulas. Power Query lets a model ingest and clean external data through a recorded, repeatable transformation sequence rather than a manual copy-paste-and-clean step. Both are genuine productivity gains, and both introduce dependency structures that a conventional row-by-row, cell-by-cell review does not automatically surface — a spilled range is owned by one formula rather than many, and Power Query's transformation steps sit entirely outside the worksheet grid.

ESG Due Diligence

ESG due diligence assesses a target's environmental liabilities, social and labor practices, and governance structure — a workstream that has moved from a peripheral check to a standard part of institutional transaction processes, particularly for infrastructure, industrial, and real asset targets where environmental exposure can be material and long-lived. Its findings translate into the transaction model in two ways: a quantifiable environmental remediation liability enters as a specific reserve, while broader governance or social findings more often affect the buyer's risk assessment, financing terms (where lender ESG requirements apply), or the discount rate applied in valuation.

ESG and Climate Risk Adjustments in DCF Discount Rates

Two competing approaches exist for reflecting ESG and climate risk in a DCF valuation: adding a climate or ESG risk premium to the discount rate, or adjusting the forecast cash flows directly under explicit transition-cost and physical-risk scenarios. This guide sets out both approaches, why a single discount rate premium conflates distinct risk types (physical, transition, regulatory) and compounds awkwardly over a multi-decade forecast and terminal value, why institutional practice increasingly favors adjusting cash flows under explicit scenarios as an extension of standard scenario analysis, and why no single standardized methodology yet exists industry-wide for this specific problem.

EV Infrastructure Models

EV charging infrastructure investment economics are driven by utilisation ramp risk, since demand builds gradually as vehicle adoption grows, site-level revenue mechanics that vary by charger type and location, grid connection cost that can be a material and uncertain component of total capital cost, and a network effect between charger density and adoption that complicates simple site-by-site investment appraisal. This guide covers how to model each of these drivers.

Education Facility Operations Models

An education facility operations financial model specialises the general social infrastructure framework to a building type governed by the academic calendar: maintenance timed to extended term-break closure periods rather than year-round scheduling, capacity planning driven by enrolment forecasting rather than a fixed occupancy assumption, and community or out-of-hours facility use as a distinct secondary revenue stream. This guide covers how to build that specialised operations-phase model.

Electricity Market Fundamentals

Electricity markets are structured as regulated (tariff-set), merchant (wholesale-price), or hybrid arrangements, and the specific market a power project sells into determines how its revenue and dispatch are actually set. This guide covers the market-structure fundamentals a power project financial model needs to represent: tariff-setting and cost-of-service regulation, wholesale market and merit-order dispatch, and the hybrid structures — capacity markets, contracts for difference — that combine elements of both.

Emissions Reduction Models

An emissions reduction, or marginal abatement cost, model ranks available abatement options by cost per tonne of emissions reduced, providing the analytical basis for prioritising capital toward the lowest-cost reduction opportunities first. This guide covers how to build an abatement cost curve, the distinction between capital-funded abatement measures and operational efficiency measures, and how the curve should tie directly to investment decision-making rather than remaining a standalone analytical exercise.

Energy Model Audit

A structural audit of an energy or power project financial model tests whether the formulas actually built calculate correctly across the technical output chain, revenue stack, operating cost build, and debt sculpting modules specific to this domain — distinct from validation, which additionally assesses whether the underlying assumptions and methodology are reasonable. This guide sets out the audit scope specific to a power project model, building on the general financial model audit discipline this domain applies.

Energy Model Documentation Standards

Documentation for an energy or power project financial model should record, at minimum, the source and confidence level of every technical assumption, the pricing basis for each revenue stack component, and the logic behind any circular debt sculpting calculation, in addition to the general model documentation practice applied to any financial model. This guide sets out this domain-specific documentation standard.

Energy Model Validation

Independent validation of an energy or power project financial model tests three distinct pillars: conceptual soundness of the resource yield, degradation, and price forecasting methodology, implementation accuracy of that methodology in the actual model build, and ongoing outcomes performance once the asset is operational. This guide sets out how each pillar applies to this domain, extending the general model validation discipline with the resource- and market-specific judgment this asset class requires.

Energy Revenue Models

A power project's electricity revenue is rarely a single price applied to total output — it is typically a stack of contracted (PPA), capacity, and merchant components, each with its own price-setting mechanism and risk profile. This guide covers how to build that revenue stack as separately priced, explicitly modelled modules, and how to combine them into a single reconciled revenue output without losing the visibility each component requires.

Energy Storage Economics

Beyond the project-level modelling mechanics of a specific battery asset, energy storage economics is the broader framework for understanding how storage creates and captures value in an electricity market: stacking multiple value streams whose relative maturity and pricing evolve over time, the risk that storage value per unit erodes (cannibalizes) as more storage capacity enters the same market, and storage's emerging role as an alternative to conventional transmission and distribution infrastructure investment. This guide covers this market-level economic framework, distinct from the asset-level battery modelling mechanics covered elsewhere in this pillar.

Enterprise Data Centre Models

Enterprise, or captive, data centres are facilities an organisation builds and operates for its own internal IT use rather than leasing to external tenants. This guide sets out how to model this business model as an internal cost centre with chargeback to business units, and how to structure the build-versus- colocate-versus-cloud capital allocation decision that increasingly frames enterprise data centre investment.

Enterprise Value to Equity Value Bridge

An FCFF-based DCF produces enterprise value, the value of the whole operating business attributable to all capital providers combined. Converting that figure to the value attributable to equity holders specifically requires a defined set of adjustments: deducting net debt, minority interests, and preferred stock, and adding back non-operating assets. This guide walks through each adjustment, where its inputs should be sourced from the balance sheet, and the diluted share count calculation needed to arrive at value per share.

Evolution of Financial Modelling

Financial modelling has evolved through several distinct stages, manual ledger calculation, early electronic spreadsheets, best-practice-driven structured spreadsheet modelling, and now AI-assisted construction, each expanding what could be built and how fast, without changing the underlying requirement that a model's calculated output be traceable and verifiable. This guide traces that evolution and sets out what AI genuinely changes about modelling practice, and what it does not.

Excel Performance and Large Model Optimisation

A financial model's calculation performance degrades predictably as it grows — more formulas, more volatile functions, more cross-workbook links, and more array-heavy calculations all add directly to the time Excel needs to recalculate the workbook. This is a construction and maintenance discipline distinct from structural correctness — a model can be perfectly correct and still be unusable in practice if a single keystroke triggers a multi-minute recalculation. This guide covers the specific mechanisms that drive recalculation cost in a large institutional model and the techniques used to manage it, primarily volatile function discipline, calculation mode management, and workbook size and link-count control.

Exploration & Production Models

Exploration and production (E&P) asset models translate segment-level upstream economics into a specific, buildable model at the well and pad level: type curves for individual wells, a rig-count-driven drilling schedule, per-well capital and operating cost, and the production ramp-up that results from drilling activity over time. This guide sets out how E&P models are structured at this granular level, complementing the segment-wide reserve and fiscal mechanics covered in Upstream Financial Models.

Export Credit Agency Models

An export credit agency (ECA) supports national exporters by providing guarantees, insurance, or direct financing against buyer and country non-payment risk, and its portfolio economics differ from a conventional bank's in several structural ways. This guide covers how an ECA model should represent the cover ratio (the percentage of a transaction's risk the ECA actually assumes), premium pricing calibrated to country and buyer risk grade, and the claims-and-recovery cycle that is substantially longer and more variable than conventional bank credit losses.

Field Development Financial Models

Field development financial models translate a discovered, appraised field into a specific development plan: phased capital expenditure, first oil or first gas timing, plateau production rate, and the facility sizing and tie-back-versus-standalone decisions that shape the project's capital intensity. This guide sets out how a field development model is structured around these decisions and how it feeds into the Final Investment Decision that follows.