Technical Guides

Renewable Energy Due Diligence

Due diligence for a renewable energy acquisition or financing combines the standard financial, legal, and tax workstreams with a technical workstream centered on the independent resource yield assessment, and a commercial workstream reviewing the PPA or offtake structure and the project's interconnection position. This guide covers how these workstreams should be coordinated for a renewable energy transaction specifically, building on the general due diligence process this domain specializes.

Renewable Incentive Models

Renewable energy projects frequently rely on production or investment incentives — tax credits, feed-in tariffs, or tradeable renewable energy certificates — to reach commercial viability, and each incentive type carries its own eligibility, timing, and durability characteristics that a financial model should represent explicitly. This guide covers how to model the major incentive types, the rules governing stacking multiple incentives, and the sunset or phase-out risk incentive-dependent revenue carries.

Rental Escalation Modelling

Rent escalation across a real estate rent roll is rarely a single uniform growth rate; individual leases carry fixed contractual uplifts, indexation to a stated index subject to a cap and collar, or open market review to prevailing rent, sometimes within the same portfolio. This guide sets out how each escalation mechanism should be modelled per lease and why blending them into a single portfolio-wide growth assumption misrepresents the rent roll's actual composition and risk.

Repowering Models

As a power project approaches the end of its original design life or PPA/incentive tenor, its owner faces a repower-versus-decommission-versus-life-extension decision, each with a distinct capital, timeline, and risk profile. This guide covers how to model this end-of-life decision: comparing repowering capital cost against greenfield development economics, valuing the retained permitting and interconnection position a repowering project keeps that a greenfield project must acquire from scratch, and the timing considerations that shape when this decision should actually be made.

Reserve Accounts in Project Finance Models

Reserve accounts, principally the debt service reserve account (DSRA) and the maintenance reserve account (MRA), are funded, ring-fenced cash balances that sit within a project finance model's cash waterfall, protecting lenders against a temporary debt service shortfall and funding known future major maintenance or lifecycle capital events respectively. This guide sets out how to build the funding, top-up, and drawdown mechanics for each reserve type, and the common errors that misrepresent the protection they actually provide.

Reserve-Based Valuation Models

Reserve-based valuation discounts the future net revenue expected from producing a defined reserve base, most commonly reported as PV-10, the present value of estimated future net revenue from proved reserves discounted at 10%, a standardized measure under U.S. SEC reporting requirements. This guide sets out how reserve-based valuation is constructed, how it relates to general discounted cash flow valuation practice, and the reserve category and price deck choices that most affect the resulting value.

Residential Development Model Structure

Residential development models specialize the general development appraisal structure around unit typology mix, phase-specific pricing, and, in most jurisdictions, an affordable or social housing obligation that must be integrated into the gross development value and cost build rather than treated as an external adjustment. This guide sets out how the unit schedule, pricing matrix, and affordable housing treatment should be built.

Resolving WACC Circularity in a DCF Model

A circular reference arises in a DCF model whenever WACC's capital structure weights are drawn from the model's own calculated enterprise value, since that value is itself the output of discounting cash flow at WACC. This guide sets out why the circularity occurs, the two standard resolution approaches — using a fixed target capital structure to eliminate the circularity entirely, or a controlled iterative calculation with documented convergence settings where target weights are not appropriate — and the structural audit checks that confirm whichever approach is used has been implemented correctly and consistently.

Retail Banking Models

Retail banking serves individual consumers at high volume, and this shapes the standard bank model structure in specific ways: loan segmentation is driven by product type (mortgages, auto loans, credit cards) and statistical risk scoring rather than bespoke commercial credit assessment, deposit behaviour is dominated by a large base of smaller-balance, individually stable accounts, and the cost structure is shaped by branch and digital channel infrastructure serving high transaction volumes at low per-transaction value.

Retail Real Estate Model Structure

Retail models specialize the income-producing asset structure around turnover rent mechanics, where a portion of rent is contingent on tenant sales performance, and tenant mix, where anchor tenant covenant strength and footfall contribution materially affect the value of surrounding smaller units. This guide sets out how turnover rent should be modelled, how tenant mix and anchor covenant risk should be represented, and how service charge recovery feeds the NOI build.

Revenue Cycle Modelling

The revenue cycle module translates gross billed charges into net patient service revenue and, ultimately, collected cash, through contractual allowances, claims denial and resubmission, and the resulting accounts receivable balance. This guide covers how to build that module: the gross-to-net waterfall, how denial and collection assumptions should be sourced and tested, and how days in accounts receivable feeds the working capital forecast.

Revenue Forecasting Methods

Revenue can be forecast using several structurally different methods, and the choice of method has a direct effect on how defensible and auditable the resulting forecast is. This guide sets out the four principal methods used in institutional financial models — top-down forecasting from market size and share, bottom-up forecasting from unit economics, trend and growth-rate extrapolation from historical results, and cohort-based forecasting for subscription and other recurring-revenue businesses — with guidance on when each method is appropriate and how the methods can be combined within a single forecast.

Risk Analysis in Investment Appraisal

A single-point NPV or IRR calculation, built on one specific set of assumptions, does not on its own convey how a capital budgeting conclusion would change if those assumptions turned out to be wrong. Risk analysis in investment appraisal addresses this by layering a defined set of techniques on top of the base calculation: sensitivity analysis, which tests the effect of changing one input at a time; scenario analysis, which tests coherent alternative sets of assumptions together; and Monte Carlo simulation, which models a full probability distribution of outcomes across many simultaneously varying inputs. This guide sets out what each technique tests, how they complement rather than substitute for one another, and how they apply specifically to a capital budgeting decision.

Risk Weighted Assets

Risk-weighted assets (RWA) convert a bank's balance sheet exposures into a common risk-adjusted base, applying higher weights to riskier exposures and lower weights to safer ones. RWA forms the denominator of every Basel capital ratio, making the risk-weighting methodology a first-order driver of reported capital strength. This guide covers the standardized and internal ratings-based (IRB) approaches to calculating RWA, how a model should build the RWA base from segmented exposures, and how risk-weight density should be tracked as its own diagnostic output.

Sales Absorption Modelling Methods

Beyond the general principle that absorption should be phase- or typology-specific, this guide sets out the mechanical methods for building an absorption curve, S-curve versus linear pacing, how to source and apply comparable evidence, and how to sensitivity-test absorption pace independently of sales price so a reviewer can distinguish demand risk from pricing risk.

Scenario Analysis for DCF Valuation

Scenario analysis tests a DCF's value output under a small number of internally consistent, named states of the world — typically base, upside, and downside cases — where every driving assumption changes together as a coherent set, in contrast to sensitivity analysis, which isolates the effect of one or two variables at a time. This guide sets out how to build a scenario switch mechanism in a DCF model, the discipline required to keep each scenario's assumptions genuinely internally consistent, and how scenario output should be presented alongside sensitivity analysis rather than as a substitute for it.

Scenario Planning for Forecasting

Building a base, upside, and downside case is a planning and governance process, distinct from the Excel mechanics used to implement a scenario switch. This guide covers that process: how to define a coherent set of driver changes for each case, how to govern which assumptions are allowed to move between cases and by how much, how to document the rationale behind each case so it can be defended to a reviewer, and how the process relates to the underlying switch-cell mechanism that makes the resulting cases operable inside the model.

Sell-Side and Vendor Due Diligence

Sell-side due diligence is a seller's own internal review, run ahead of going to market, to anticipate and pre-empt the findings a buyer's due diligence team is likely to surface. Vendor due diligence is a related but distinct practice: a seller commissions an independent advisor to prepare a formal due diligence report specifically for distribution to multiple prospective bidders, reducing duplicated buyer-side cost and shortening the process timeline. This guide covers both, and the specific point at which a vendor due diligence report's independence needs to be genuine rather than nominal for bidders to actually rely on it.

Sensitivity Analysis for DCF Valuation

Sensitivity analysis tests how a DCF's enterprise or equity value output changes as key assumptions are varied, most importantly the discount rate and the terminal growth rate or exit multiple, given their disproportionate combined effect on total value. This guide sets out how to build one-way and two-way sensitivity tables for a DCF specifically, which variable pairs are most informative to test together, and how to interpret the resulting output as a decision input rather than a single point estimate.

Sensitivity Table Integrity in Financial Models

Sensitivity table integrity refers to whether the results displayed in an Excel data table in a financial model reflect the current state of the model's calculations or whether they represent stale values from a previous calculation state. An Excel data table runs a series of calculations by substituting different input values into designated cells and recording the outputs. If automatic calculation is disabled, if the data table's input cells are incorrectly specified, or if the data table has been converted from dynamic to static values, the sensitivity results displayed may not correspond to the model as it currently stands. This is a high-risk structural failure because it provides false assurance about the model's sensitivity to changes in key assumptions.