How Quantixr produces a Business Risk Score — and what it deliberately won't do.

Every assessment runs through the same deterministic pipeline. A reviewer submits structured business information and a bank statement. Quantixr extracts and calculates financial metrics inside the application — never via a language model — and then combines those metrics with location, operational, and digital signals into four scored dimensions: Financial Health, Location Context, Business Stability, and Digital Footprint.

The four dimensions are weighted and summed into a single Business Risk Score between 0 and 100, mapped to a tier band. The same inputs always produce the same score. Reviewers see the component breakdown and the underlying figures, so the result can be inspected and challenged rather than taken on trust.

The score is built from structured, auditable inputs in four categories:

• Trading data — the business's own bank statement, parsed deterministically for revenue, expenses, cash flow, and recurring obligations.
• Official statistics — Statistics South Africa (Stats SA) economic and demographic datasets at suburb and municipality level.
• Reported crime data — SAPS crime statistics published at police-station and suburb level.
• Municipal & open data — City of Cape Town and comparable open-data portals covering economic activity and business density.
• Digital signals — verified Google Business listings, the business's website, and its public social profiles.

Public datasets in South Africa are not updated in real time. Stats SA releases are periodic, SAPS crime data is reported in fixed cycles, and municipal open-data feeds vary in freshness. A score therefore reflects the most recent reliably-published figures, not yesterday's reality.

Where an exact suburb match is not available, Quantixr falls back to a city-level average and labels the result as approximate in the reviewer's report. Where a bank statement cannot be parsed, the financial component is withheld rather than guessed, and the remaining weightings are renormalised. We would rather show less than show something we cannot defend.

The score is a decision-support signal, not a verdict. It compresses imperfect information into a single number and should be read alongside the underlying figures, not in place of them.

South African data carries the imprint of the country's history. Reported crime statistics are influenced by where policing is concentrated and where incidents are reported in the first place. Economic activity indices reflect formal economic measurement and systematically under-represent informal trade, which is the lived reality for a large share of SMEs.

Suburbs that have historically been under-served by infrastructure, banking, and municipal investment will look "thinner" in the data than they are in practice. We are explicit about this: Location Context describes the measured environment around a business; it is not a judgement about the business itself or the people who operate it.

We deliberately cap the influence of any single environmental signal, never let location dominate the score, and surface the underlying components separately so reviewers can apply their own judgement rather than defer entirely to the headline number.

Artificial intelligence is used in one narrow place: producing a short, plain-English summary of an already-calculated profile, plus a small set of risk observations and improvement suggestions.

The AI never sees raw bank statement text. It never performs arithmetic. It never decides the score. It receives only the figures the deterministic engine has already produced, and its output is constrained to a fixed structure with risk-neutral language. The numbers you see are not generated by a model — they are calculated, then described.

• Quantixr does not make decisions for or against any business. It produces a risk signal; decisions remain with the reviewing organisation.
• Quantixr is not a registered financial services provider and does not issue affordability rulings or scoring products regulated under the NCA.
• Quantixr does not interact with the small business being assessed. SMEs do not log in, and no marketing or outreach is sent to them.
• Quantixr does not use AI to compute, adjust, or override financial figures, and does not generate narrative claims that go beyond the structured inputs.
• Quantixr does not sell, share, or repurpose submitted business data for any use outside the reviewer's own assessment workflow.