Technical Guides

Asset Management Documentation Standards

Asset management documentation standards address a specific institutional risk this pillar's models face more acutely than most: an asset's operating life frequently outlasts the original model builder's and asset manager's own tenure by decades, and undocumented assumptions become effectively unverifiable once that institutional knowledge is lost. This guide covers what an asset management model should document, why traceability to source matters more here than in a shorter-horizon transaction model, and how documentation should be maintained as the model itself is updated over time.

Asset Management Due Diligence

Asset management due diligence examines the quality of an infrastructure asset or portfolio's ongoing asset management practice, ahead of an acquisition, refinancing, or major investment decision, distinct from the technical and commercial due diligence workstreams that examine the asset's physical and market fundamentals. This guide covers what asset management due diligence should test: asset register and condition data quality, reserve adequacy, and the presence and disclosure of any renewal funding gap the acquirer or lender would be inheriting.

Asset Management Models

An asset management firm's financial model is driven by assets under management (AUM) and the fee rate charged against them, not by a balance sheet spread — the firm typically holds client assets off its own balance sheet entirely. This guide covers how to structure an asset management model: the AUM roll-forward (opening AUM, net flows, market performance), management and performance fee calculation, and the operating leverage that makes this business model's cost base scale very differently from a bank's.

Asset Management Plans

An asset management plan (AMP) is the document, and underlying financial model, through which an asset owner sets out how a portfolio of infrastructure assets will be operated, maintained, renewed, and funded over a defined planning horizon, typically ten to thirty years. This guide covers how the financial projections in an asset management plan should be structured: the link from the asset register and condition assessment to a funded forecast, the level-of-service targets the plan is built to sustain, and the funding gap analysis that distinguishes a credible plan from an aspirational one.

Asset Optimisation Models

An asset optimisation model compares the renew, repair, and dispose (or do-nothing) options available for each asset or component in a portfolio, ranks them by service outcome achieved per unit of funding spent, and selects the combination of interventions that maximises portfolio-wide service delivery within a capital constraint. This guide covers how to build that optimisation logic, extending the prioritisation approach in capital replacement planning into a formal option-ranking and selection model.

Asset Performance KPIs

Asset performance KPIs are the defined metrics an asset owner tracks to measure whether an infrastructure asset or portfolio is delivering against its level-of-service commitment, spanning physical condition, availability, cost efficiency, and service delivery dimensions. This guide covers which KPIs an asset management financial model should track, how each connects back into the funding and renewal model rather than existing as a standalone reporting exercise, and how KPI selection should match the specific level-of-service targets the asset owner has committed to.

Asset Performance Review

An asset performance review periodically compares an infrastructure asset's actual operating revenue, cost, maintenance experience, and condition outcomes against its financial model's original projections, distinct from a structural audit testing whether the model itself is formulaically correct. This guide covers how to conduct this review, what variance should trigger a model update, and how to avoid the common failure of running a performance review that never actually changes the forward model.

Asset Renewal Models

An asset renewal model forecasts when each major component of an infrastructure asset will need replacement or major refurbishment, sizes the cost of that renewal event, and connects it to the reserve funding mechanism that pays for it. This guide covers how to build a renewal model: age-based versus condition-based renewal timing, the renewal cost curve across a portfolio, and how renewal funding and drawdown mechanics should be structured, extending the general reserve treatment already established for project finance maintenance reserve accounts.

Assumption Design Best Practices

How a forecast's assumptions are designed determines whether the forecast can actually be audited, sensitized, and defended in front of a reviewer, independent of whether the assumed values themselves are reasonable. This guide sets out five construction disciplines for assumption design: separating input cells from calculation formulas, labelling every assumption clearly with its unit, consolidating assumptions onto a dedicated tab, entering each driver once at a single point rather than repeating it, and structuring input cells so they can be sensitized cleanly without breaking the calculations that depend on them.

Audit Methodologies for Financial Models

Financial model audit methodologies fall into three primary categories: manual line-by-line review, automated structural analysis, and deterministic rule-based checking. Each methodology differs in scope, speed, consistency, and the types of errors it is designed to detect. The appropriate methodology depends on transaction complexity, time constraints, and institutional risk appetite.

Availability Models

Availability modelling extends beyond a single availability percentage assumption into how contractual availability guarantees, planned and unplanned outage risk allocation, and liquidated damages provisions should be represented in a power project financial model. This guide covers how availability should be modelled as a contractually structured mechanic, connecting the O&M contract's actual terms to the model's revenue and cost outputs.

Availability Payment Modelling

Availability payment modelling builds the revenue mechanics of an availability-based infrastructure contract into an ongoing operations-phase financial model: the base payment, the deduction formula responding to unavailability or performance failure, indexation, and the lifecycle reserve funding the structure typically requires. This guide covers that operations-phase build, complementing the audit-perspective treatment of the same mechanism covered in the availability payment model glossary entry and the PPP model checklist.

Balance Sheet Forecasting

Balance sheet forecasting is the central forward-looking exercise in a bank model: forecasting segmented asset volumes (loans, securities) and liability volumes (deposits, wholesale funding) period by period, then reconciling the two through an explicit funding plan. This guide covers how to structure that forecast, how to build the funding plan that closes any gap between asset growth and deposit growth, and how the forecast should be checked against capital adequacy and liquidity constraints rather than produced in isolation from them.

Bank Financial Statements

A bank's three financial statements carry a different structure and internal logic from a standard corporate three-statement model. The balance sheet is the primary earnings driver rather than a supporting schedule; the income statement separates net interest income from fee and other income and shows loan loss provisions as their own distinct line ahead of non-interest expense; and the cash flow statement requires bank-specific adjustments that a corporate model's indirect method does not anticipate. This guide sets out each statement's bank-specific structure and how the three connect.

Banking Best Practices

This page synthesizes institutional best practice across the full Banking Financial Modelling domain into a single reference, drawing together the balance-sheet-first construction discipline, capital and liquidity governance, institution-type specialization, and model risk management practices covered in depth elsewhere on this Knowledge Centre. It is the capstone page for this domain, intended as a starting orientation for a reader new to banking financial modelling and a quick reference for an experienced practitioner, in both cases pointing to the full dedicated guide for any practice that needs deeper treatment.

Banking Business Model

A bank does not sell a product for a price; it intermediates funds, earning a spread between what it charges borrowers and what it pays depositors and wholesale funders, augmented by fee and commission income from services that do not consume balance-sheet capacity. This guide explains how that economic model translates into financial model architecture: why the balance sheet — not a revenue line — is the model's primary driver, how the spread business and the fee business should be modelled as two distinct income streams, and how this shapes the sequencing of every other module in the model.

Banking Documentation

Documentation for a bank model must satisfy general model documentation discipline while also evidencing several bank-specific requirements: the sourcing and justification of regulatory-linked assumptions (risk weights, capital thresholds, liquidity run-off rates), the model's assigned risk tier and rating, and its validation and approval history. This guide covers what banking documentation needs beyond the general standard, and why undocumented regulatory assumption sourcing is one of the most common findings in a bank model review.

Banking KPIs

A bank model should expose a defined set of bank-specific KPIs as explicit model outputs, built directly from the model's own calculations rather than computed ad hoc outside the model for a board pack. This guide sets out the core banking KPI set — profitability metrics (net interest margin, return on assets, return on equity), efficiency (cost-to-income ratio), and asset quality (non-performing loan ratio, provision coverage ratio) — how each should be calculated, and how they should be structured as a dedicated output module rather than scattered across the model.

Banking Model Audit

A structural audit of a bank model tests whether the formulas and logic as actually built calculate correctly — whether the segmented balance sheet, interest income build, credit loss provisioning, and capital adequacy modules covered across this domain are internally consistent and free of the structural errors (broken links, hardcodes, inconsistent formulas) that affect any complex Excel model. This guide covers what a banking-specific structural audit should check, and how it differs from both model validation and any regulatory capital or liquidity calculation review.

Banking Model Risk

Model risk in banking is a distinct, heavily formalized discipline, because banks rely on models for decisions with direct regulatory and financial stability consequences — credit decisions, capital adequacy, and liquidity management chief among them. This guide extends the general Model Risk pillar with the banking-specific model taxonomy (credit, valuation, capital, liquidity models), the three-lines-of-defense structure common to bank model risk management frameworks, and why banking model risk management is typically more formalized than in most other industries.