Bankability & Data Trust

Data Trust & Evidence

Where the data comes from, how current and complete it is, what was measured, modelled or entered by you, and how the calculation was checked.

• Data Trust & Evidence moduleFor every module result in a project: an evidence register (source, provider and licence, period, resolution, spatial coverage, class — measured, modelled / reanalysis, user-supplied, assumed default or derived — how it was used and its limitations), quality checks and a Data Trust level High / Medium / Low per module. The level is a weighted checklist with the points of each criterion shown, together with what it rests on, which assumptions, what is missing and how far it can be trusted. It is not a certification.
• Sources, licences and datesReports name their data sources — on the cover (data basis), in the source notes of the sections and in the assumptions review before the final report: which public or licensed source (terrain, climate, OpenStreetMap, hazard catalogues, PVGIS / ERA5, published grid data) was used, with dates where the source provides them; unit rates in the engineering library are sourced and dated.
• Measured, modelled and user data kept apartYour uploads (survey terrain, boreholes, met-mast or solar time series, price series, BoQ) are used in place of open data and the report names the source; estimated values (for example grid capacity where no operator data is published) are marked as estimated.
• Uncertainty stated, not hiddenP50–P99 energy for solar and wind, estimate classes with accuracy ranges for cost, scenario and tornado sensitivities in the finance model.
• Missing data and conflictsData Trust lists missing required inputs and flags contradictions: capacity in the documents vs the module input, coordinates of modules far apart, CAPEX outside a benchmark band, yield outside a plausibility band, currency and FX; document intake lists conflicting values between revisions; report QA checks numbers in the text against the engines.
• Stale dataDated inputs (climate periods, price levels, library rates) are compared with a staleness limit you can set.
• Independent checkSolar, wind, BESS, electrical, water, mass-haul and line-mechanics results side by side with named open tools on the same inputs, with a green / amber / red band and the reason for any difference.
• Validation registryThe public validation report lists every comparison with values, differences, tool versions and dates (web page, PDF and JSON).
• Reproducible analysis recordThe project workspace keeps every analysis of a project: date, software version and build, an inputs fingerprint, the inputs and the key results — earlier analyses are never overwritten. The Data Trust report repeats the fingerprint per module with the source versions and the run date; trust levels are kept in the analysis history for comparison.

Validation report · Validated against

Bankability Assessment & Lender Due-Diligence Support

The technical, commercial and financial review of a project: what the evidence shows, which assumptions it rests on and what is still missing.

• Sector Bankability AssessmentSolar PV, BESS, wind, transmission & grid, and construction & infrastructure profiles in five categories: technical feasibility and design assumptions; CAPEX, OPEX, revenue and financial-model assumptions; land rights, permits, grid connection and contracts; risks, sensitivities and missing documents; independent expert review status. Items are answered from WaiMAP results where evidence exists, otherwise marked as document required. Output: a readiness level (Early screening, Developing, Advanced for lender review), gaps, a document request list and next steps — never a pass / fail certificate. Low data trust caps the readiness level.
• Technical due diligenceWeighted checklist of 91 items in 22 areas for PV, BESS and hybrid projects; EPC key terms, tests and hold points, red flags and a readiness verdict with the evidence each item needs.
• CAPEX, OPEX and revenue assumptionsBudget engine with dated benchmarks, estimate classes, escalation and contingency; engineering library of sourced unit rates.
• Financial modelAnnual project-finance model: debt sculpting, DSCR, LLCR, equity and project IRR, NPV, LCOE / LCOS, break-even tariff, scenarios and tornado.
• Storage economicsBESS economic analysis (EIRR, ENPV, benefit / cost, switching values), delivery models and risk allocation matrix.
• Site, grid and permitting risks8-axis go / no-go screen (resource, grid, land, environment, hazards, market, social, logistics), grid-connection options, ESIA screening.

Data Trust level — how it is derived

A weighted checklist per module; the report shows every criterion with its points. High ≥ 75, Medium ≥ 50, Low below 50.

• Sources and licences documented15 points
• Primary data quality (measured › user site data › derived › modelled › default)20 points
• Required inputs complete15 points
• Uncertainty quantified10 points
• No contradictions15 points
• Data current (staleness limit)10 points
• Independent check (green / amber; red caps the level)15 points

Readiness level — not a pass / fail

The Bankability Assessment reports a readiness level, gaps, document requests and next steps.

• Early screeningConcept or screening evidence; key documents and site data still missing, or a critical red item.
• DevelopingMain analyses done with partly confirmed data (coverage ≥ 40 %, score ≥ 50 %); gaps listed.
• Advanced for lender reviewCoverage ≥ 75 %, score ≥ 75 %, no red item — ready for an independent engineer and the lender to review. Low data trust caps the level at Early screening, medium at Developing.