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CREDIT DECISIONING

Credit decisions that are consistent, explainable, and fast.

SCREDIT combines weighted scorecard scoring, configurable risk bands, and policy-driven approval routing so every application gets the same disciplined evaluation, and every decision can be explained afterward.

THE PROBLEM

When decisioning lives in individual judgment, consistency leaves with the person.

Two analysts, two answers. Approval authority enforced by memory. Decisions that cannot be reconstructed six months later. Judgment matters in credit, but without a scoring and routing framework around it, outcomes depend on who happened to pick up the file.

CAPABILITIES

What SCREDIT delivers

Weighted Scorecard Engine

Score applications and accounts on weighted components spanning financials, payment behavior, and bureau data, with weights you configure to match your policy.

Weighting That Fits the Customer

A small trading account and a large one should not be judged on the same emphasis. Set different component weightings for small, mid-market, and large customers so the same policy reads each fairly.

Different Policies Under One Roof

Run more than one scorecard across the organisation. A subsidiary, a region, or a newly acquired business can carry its own components and weights while the group still sees one consolidated view of exposure.

Configurable Risk Bands

Map scores to named risk bands that drive limits, terms guidance, and review frequency consistently across the portfolio.

Approval Authority Thresholds

Define who can approve what by exposure and risk level, and let the system route each decision to the right level automatically.

Bureau Data in the Decision

Pull commercial bureau data into the scoring and review workflow so external signals sit beside your internal experience.

Financial Analysis Integration

Feed ratio and trend results from financial statement analysis directly into scorecard components.

Decision Audit Trail

Record what was scored, what the score was, who approved it, and under what authority, for every decision.

IN THE PRODUCT

Decisioning, in the product

The SCREDIT applications queue. Summary cards show two submitted awaiting first review, one million five thousand dollars in review across three applications, and two hundred sixty thousand dollars pending information. A table lists ten credit applications with application number, customer, credit term, requested amount, applied date, assigned analyst and status, ranging from submitted through in review, pending information, approved and declined.
Applications queue — every request, its terms, its owner and its stateSCREDIT demo environment · illustrative data, not a customer
The SCREDIT assessment view for a single credit application. A header names the applicant, the requested amount of one hundred eighty-five thousand dollars, NET30 terms and an in-review status. A grading model breakdown lists four scored components — bank references, company profile, financial statement and trade references — each with its weighting, whether the supporting data is present, the value recorded and the score it produced. A score summary panel gives the overall score of eighty-seven against a target of eighty-five, names the model that produced it, and states the company size band it was scored against.
Application assessment — the components behind a score, and the model that produced itSCREDIT demo environment · illustrative data, not a customer
The SCREDIT Customer 360 portfolio view. Header figures show five and a half million dollars of portfolio exposure at fifty-five per cent utilisation, two and a half million dollars of available headroom across ten accounts, two accounts at risk or over limit, and three reviews due within thirty days. Each customer row carries a score, a risk band from low through watch, high, unrated and critical, a utilisation bar against its credit line, an account status and a next review date.
Customer 360 — exposure, utilisation and review dates across the portfolioSCREDIT demo environment · illustrative data, not a customer
OUTCOMES

What changes on the desk

Consistent Decisions at Scale

Apply the same evaluation logic to the hundredth application as to the first.

Same-Day Movement on Scored Applications

Let clean applications flow to the right approver without waiting in an inbox.

Explainable Outcomes

Reconstruct any decision from its scored components and approval record.

Policy That Actually Executes

Turn the credit policy document into enforced workflow rather than aspiration.

Frequently asked questions

How does the weighted scorecard work?

You define the components that matter to your book, such as financial ratios, payment history, and bureau signals, assign each a weight, and define how raw values map to component scores. SCREDIT computes a weighted overall score and places the account in a risk band. The math is transparent: you can always see which components drove a score.

Can we configure the scorecard to our own policy, or is it a black box?

It is fully configurable and deliberately not a black box. Weights, components, thresholds, and risk bands are yours to define, and every score decomposes into its inputs. For trade credit, an explainable scorecard your team trusts beats an opaque model nobody can defend to an auditor or a sales VP.

How does approval routing use authority thresholds?

You define authority levels, for example what a credit analyst, credit manager, and finance director can each approve, by exposure amount and risk band. When a decision is ready, SCREDIT routes it to the right level of authority. Nothing gets approved above someone's authority, and nothing waits on a director that a manager could sign.

Does decisioning replace analyst judgment?

No. The scorecard produces a consistent, evidence-based starting point, and routing ensures the right person makes the call. Analysts and approvers still exercise judgment, especially on marginal scores and large exposures, but they do it on top of structured evidence.

How is this different from the credit score a bureau website gives us?

A bureau score is one input about one company from one vendor. SCREDIT decisioning combines bureau data with your financial analysis and your own receivables experience, weights them by your policy, and wraps the result in approval governance. The bureau tells you about the customer; the scorecard tells you what your policy says to do about them.

What happens when a customer's situation changes after approval?

Decisioning is not only for new accounts. Scores recalculate as inputs change, and risk bands drive review scheduling, so a deteriorating account surfaces for re-review rather than coasting on a limit approved in better times.

We operate several businesses with different credit appetites. Can they run different policies?

Yes. Scorecards are defined per business rather than per platform, so a distribution arm and a construction supply arm can weight components differently, use different risk bands, and set different approval authorities, while group-level reporting still rolls exposure up across all of them. Acquisitions are the common case: the acquired business keeps operating on its own policy while it is brought onto yours, rather than being forced onto day one.

Does the same scorecard apply to a $50k customer and a $5M one?

Only if you want it to. Component weighting can vary by customer size, so the emphasis that makes sense for a small trading account is not forced onto a major one. A thin file on a small account might lean on trade references and payment history, while a large exposure leans harder on audited financials — same policy, appropriate emphasis.

See scorecard decisioning in SCREDIT.

Bring a sample of your current policy and see how it maps to scorecard weights, risk bands, and approval routing.