Financial statements speak once a year. A supply chain speaks every day.
Conventional credit assessment leans on data that arrives late and changes slowly. But a company that issues electronic drafts, guarantee instruments, GAM notes and online documentary credit on a platform generates evidence about itself every month: settled on time or not, in full or in part, one day in arrears or sixty-one days in doubtful. Eco-Trust moves that evidence from the margin to the centre of the decision.
Data recorded nowhere else
A company's behaviour across the life cycle of a credit instrument is recorded only where that instrument was issued and settled. This proprietary signal carries the heaviest weight in the model.
A defensible decision
Every score is issued with its reasons: which pillar added what, and which event subtracted what. The credit decision holds up to internal audit and supervisory inspection.
Warning before default
A gradual decline shows up on the risk dashboard before it turns into serious delinquency. Reviewing a credit limit becomes preventive rather than reactive.
Five years of data gathered in the course of the work, not in a research project
Eco-Trust was not built from scratch, and it does not stand on purchased data. Tejarat Shayan has been serving companies in supply chain finance for five years, and throughout that period every credit instrument issued — electronic drafts, guarantee instruments, GAM notes and online documentary credit — every maturity reached and every settlement made — full or partial, on time or late — has been recorded. Eco-Trust turns that accumulation into a credit assessment service.
Event data, not self-reported data
Every record comes from a real transaction in which money moved. No part of it was filled in by the company about itself, and no analyst passed judgement on it.
Enough depth to reveal a pattern
Five years spans several liquidity cycles, several market swings and several periods of economic pressure. Behavioural patterns reveal themselves in exactly those difficult windows.
An outcome that can be tested
Because the data runs to the end of each cycle, it is known where every case finally landed. That is what makes it possible to measure the model against real default history.
Five pillars, one score
The final score is built from five independent data sources. The weight of each pillar is fixed and documented — not a case-by-case analyst judgement. The proportions are configurable at platform level, and every change is versioned and logged.
Repayment behaviour on the platform
On-time settlement, entry into arrears, entry into doubtful, full versus partial settlement, and the recurrence of each pattern over time. The heaviest pillar in the model, because it is the only input that measures actual conduct rather than assertion.
Iranian Credit Scoring rating
The customer's official rating on the 0–900 scale, normalised onto the Eco-Trust scale. It brings in the customer's conduct across the wider banking network — where the platform's own view does not reach.
Facilities and commitments at other banks
Outstanding facilities, repayment status and upcoming maturities. Shows how much of the customer's repayment capacity is already committed elsewhere.
Account balance and turnover
Balance, stability of turnover and its proportion to the credit requested. The pillar that measures short-term liquidity capacity rather than track record.
Blocks and returned cheques
A deductive pillar. Unresolved returned cheques, judicial blocks and non-performing debt reduce the score and, in defined cases, prevent new credit independently of the overall score.
Day sixty-one is not simply one day later
In the electronic draft system and the other credit instruments, a delay of up to sixty days keeps a customer in the “arrears” class; crossing sixty days moves them to “doubtful” and changes the accounting treatment of the receivable. Eco-Trust takes that boundary as seriously as the system itself does.
How the score is assembled
Move each pillar to see how the score, the risk grade and the suggested credit ceiling change. This runs the same weighting logic as the model itself.
Until a score connects to a decision, it is only a number
Each grade activates a defined set of limits: the credit ceiling multiple, the collateral coverage percentage, the approval level and the review cycle. Assigning a credit limit is the automatic result of that mapping, not a case-by-case negotiation.
| Grade | Score range | Ceiling multiple | Collateral coverage | Approval level | Review cycle |
|---|---|---|---|---|---|
| A1 | 850 to 1000 | 4× base | 0 to 10% | Automatic | Semi-annual |
| A2 | 750 to 849 | 2.5× base | 10 to 25% | Automatic | Semi-annual |
| B1 | 650 to 749 | 1.5× base | 25 to 40% | Credit officer | Quarterly |
| B2 | 550 to 649 | 1× base | 40 to 60% | Credit officer | Quarterly |
| C | 400 to 549 | 0.5× base | 60 to 100% | Credit committee | Monthly |
| D | below 400 | No new credit | — | Credit committee | Monthly |
The “base” in the table above is derived from the company's verified turnover and its actual transaction volume on the chain. The grade multiple is applied to that base — not to a figure the company has declared.
The score is event-driven, not periodic
The score does not wait for month-end. Every meaningful event in the life cycle of those instruments triggers a recalculation, and if the grade changes, the credit limit is reviewed at that moment.
Occurrence
Maturity, settlement, grade change, a fresh bureau enquiry or a returned cheque.
Model run
All five pillars are re-evaluated and a new score is produced with its reasons.
History
The previous score is not deleted; the new version is stored beside it with time and cause.
Effect on limits
A grade change updates the credit ceiling and the collateral coverage.
Notification
The customer, the credit officer and the risk dashboard are informed at once.
The same score has buyers outside the bank
Eco-Trust is not only an internal decision tool. With the company's own consent, its score is made available to third parties as a standard enquiry report. The two principal audiences are industrial companies and holdings, and other banks and financial institutions — and both can call the service directly from their own systems instead of working through a panel.
Companies and holdings
Before a firm enters the chain
Before bringing a new supplier or distributor into its chain, a holding or focal firm has one simple question: is this counterparty dependable? Until now the answer came either from market hearsay or from the firm's own assertions. Eco-Trust answers from actual conduct: how many credit instruments it has had, how often it fell into arrears, how often it settled only in part, and whether its score has been trending up or down.
- Pre-contract enquiry. The counterparty's risk grade, before volume and terms are set.
- Setting payment terms. Cash, deferred or guaranteed — on the basis of the grade, not of negotiation.
- Internal chain credit capacity. When the focal firm itself extends terms to a supplier, the same model sets the ceiling.
- Supplier portfolio monitoring. A grade drop for any watched firm raises an alert — before it reaches a delivery stoppage.
Banks and financial institutions
The layer missing from ordinary credit reports
Official ratings and facilities reports show what condition a customer is in; Eco-Trust shows what the customer does when the due date arrives. For a bank assessing that same customer, this is a fresh layer of data that its existing files do not contain.
- A complement, not a substitute. The behavioural score sits beside the official rating and completes the credit picture.
- Early warning. A grade change usually occurs before a delay reaches the threshold recorded by supervisory systems.
- Two consumption models. Single enquiries from the panel, or a service connection called inside the bank's own assessment workflow.
- Peer and sector view. A firm's relative position against peers of the same sector and size.
Sample Company (Private Joint Stock)
The report shows only the grade, the trend and the decisive events — not individual transactions, not counterparties and not contract amounts.
No one needs to open a panel; call the service
Everything visible in the enquiry panel is also available as a service. A company, holding or bank calls Eco-Trust directly from its own system and the answer lands inside that same workflow — with no intermediate user, no spreadsheet and no human delay. A holding's procurement system can pull the score itself before raising an order for a new supplier, and set payment terms on that basis.
Service documentation, a test environment and a trial key are made available to the applicant's technical team before any contract, in coordination with the business development unit of Tejarat Shayan, so the connection can be tested against sample data first.
A complement to official credit assessment, not a rival
Iran has a designated, licensed credit bureau, and Eco-Trust does not take its place. The difference lies in the nature of the data: the official bureau reports a company's record within the banking network; Eco-Trust reports how that same company behaves in real supply chain transactions. The two complete one another.
| Dimension | Official credit assessment | Eco-Trust |
|---|---|---|
| Data source | Banking network and government systems — facilities, cheques, debt, guarantees | Real instrument life-cycle events in the supply chain, plus those same official enquiries |
| Nature of signal | The company's credit standing in the past | What the company does when the due date arrives — which no ledger records |
| Coverage | All natural and legal persons nationwide | Companies active in the covered supply chains |
| Update frequency | Periodic, tied to the reporting cycle | Event-driven — recalculated on every settlement or grade change |
| Primary use | Lending decisions within the banking network | Admitting a firm to a chain and setting commercial credit terms |
| Legal standing | Licensed institution | Value-added service — a complement, not a replacement |
A model you can defend in front of an auditor
Automated credit assessment is only dependable when someone can stand behind every number it produces. Eco-Trust is not a black box.
- A reason code for every score. The contribution of each pillar and the list of deducting events are issued with the score.
- Full audit trail. Every score is traceable back to the primary event that produced it.
- Versioned weights. Every weight change is logged with user, time and reason; historical scores remain valid under the weights of their own day.
- Documented override authority. An officer may override the model, but only by recording a reason and at a defined permission level.
- Segregated inputs. Internal data and external enquiries are stored separately, so an error in one source cannot contaminate the whole score.
- Back-testing. Model performance is measured against real default history and the weights are calibrated on that basis.
The model stands on recognised frameworks, not on taste
Credit assessment is a discipline with four decades of international literature behind it. Eco-Trust has not reinvented any of it; it has taken the established logic of the field and mapped it onto the real instruments and rules of the Iranian market. The table below says where each part of the model came from.
| Framework | What we took from it |
|---|---|
| Credit risk measurement | |
| Finalised Basel III frameworkBasel Committee — BCBS | Separating probability of default, loss given default and exposure at default; and the principle that a risk grade must map to a credit ceiling and collateral coverage rather than remain a descriptive label. |
| IFRS 9Expected credit loss | The concept of a significant increase in credit risk and asset staging. The same logic that sits behind the arrears and doubtful boundary. |
| Loan origination and monitoring guidelinesEBA/GL/2020/06 | Assessing creditworthiness from data rather than assertion, continuous monitoring after origination, and early warning indicators and watch lists. |
| Model and data governance | |
| Model risk management guidanceSR 11-7 — Federal Reserve | The development, independent validation and back-testing cycle for a model; and the principle that no model stays valid without periodic testing against real data. |
| Risk data aggregation principlesBCBS 239 | Data lineage and traceability of every figure back to its primary event — the difference between an hour and a week during an audit. |
| ISO 31000Risk management | The general framework for identifying, assessing and monitoring risk and defining risk appetite at organisational level. |
| ISO/IEC 42001 and 23894Artificial intelligence | AI management and AI risk management, for those parts of the model that learn: explainability, bias monitoring and human oversight. |
| Data, security and interoperability | |
| ISO/IEC 27001Information security | Information security management across the full company scope — a prerequisite for any service that moves companies' credit data. |
| ISO 20022Financial messaging | A standard vocabulary for exchanging scores, events and grade-change notifications with external systems. |
| BIANBanking service architecture | Mapping Eco-Trust services onto standard banking service domains, so that connecting to any bank uses a shared vocabulary. |
| The governing domestic framework | |
| Asset classification directiveCentral Bank of Iran | The formal basis for classifying receivables and provisioning. Wherever an international framework diverges from it, the domestic rule governs and the global framework is maintained as a parallel ledger. |
| National registries and the credit bureauGovernment systems | The source of the model's external enquiries: returned cheques, non-performing debt, identity verification and the official credit rating. |
The full calculation logic, in the specification document
How the raw data of each pillar becomes a score, what effect the severity, age and recurrence of events have, which conditions operate outside the equation, and where the model's limits lie — together with two worked cases.
Where Eco-Trust sits in the financing cycle
Eco-Trust is not tied to any single platform. It is an independent layer, called before any credit instrument is issued and updated again after every settlement — whether inside a bank's system, a holding's procurement system, or any other supply chain finance platform.
- 1Onboarding and identity verificationVerifying the company, its authorised signatories and its capacity to contract.
- 2Eco-Trust — assessment and scoreThe behavioural score and risk grade, before any credit decision is taken.
- 3Credit file and limitOpening the file, the approval and the credit ceiling on the basis of the grade.
- 4CollateralCreating, valuing and allocating collateral, proportionate to that grade's coverage.
- 5Instrument issuanceElectronic drafts, guarantee instruments, GAM notes or online documentary credit — within the ceiling the score produced.
- 6Discounting and transferAssigning the instrument before maturity on the secondary market.
- 7Settlement and collectionMaturity, accounting classification and pursuit of receivables.
- 8Eco-Trust — recalculation after settlementThe outcome of each settlement feeds back into the score and closes the loop.
For the bank
A credit portfolio broken down by risk grade, with real-time aggregation and a documented basis for provisioning and supervisory reporting.
For the focal firm
Visibility into suppliers' credit health, before their liquidity problems reach the production line.
For the supplier
A record of paying well is capital in itself. A higher score means a larger ceiling, less collateral and faster approval.
The questions that come up most
Short answers to the questions banks' credit teams and holdings' procurement units raise most often.
What is Eco-Trust?
Eco-Trust is a product of Tejarat Shayan in the field of supply chain finance credit assessment. It gives every company, incorporated or individual, a score on a 0 to 1000 scale and a risk grade, based on its actual behaviour across the life cycle of credit instruments. It is Iran's first credit assessment built for the supply chain.
What data is the Eco-Trust score built on?
Five pillars: repayment behaviour on the platform at 40 percent, the Iranian Credit Scoring rating at 20 percent, facilities and commitments at other banks at 15 percent, account balance and turnover at 15 percent, and blocks and returned cheques at 10 percent. The first pillar comes from five years of real data on the issuance, maturity and settlement of electronic drafts, guarantee instruments, GAM notes and online documentary credit across the supply chain.
How does Eco-Trust differ from official credit assessment?
Official credit assessment reports a company's standing within the banking network: facilities, cheques, debt and guarantees. Eco-Trust shows how that same company behaves in real supply chain transactions. Eco-Trust is not a licensed credit bureau and does not replace an official credit report; the official rating is one of the five inputs to this model.
Who can request a credit enquiry?
Industrial companies and holdings, before bringing a new supplier or distributor into their chain, and banks and financial institutions completing their assessment of a customer. Every enquiry is conditional on the recorded consent of the company concerned and its output is limited to the grade and the decisive factors.
Does Eco-Trust offer an API?
Yes. Everything visible in the enquiry panel is also available as a service: score enquiry, batch enquiry, grade-change notification, trend and history, and suggested credit capacity. A company, holding or bank calls the service directly from its own system.
How often is the score updated?
The score is event-driven rather than periodic. Instrument maturity, full or partial settlement, a change in the accounting class of a receivable, a fresh bureau enquiry or a recorded returned cheque each trigger a full recalculation, and if the grade changes the credit limit is reviewed at that moment.
What happens if a company has little history on the platform?
The model does not produce an unsupported number. The weight of the behavioural pillar is reduced and redistributed across the external pillars, and the score is issued flagged as “insufficient history” or “limited history”, so the decision-maker knows how much evidence the number rests on.