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Credit risk management guide

How to Obtain Reliable Credit Information About Your Customers

A sound credit decision starts with relevant, up-to-date information. Learn which financial, legal and payment-behaviour sources to use, how to assess their reliability and how to turn them into appropriate credit terms.

Why customer information matters

Collecting information about a prospective customer is an essential step before agreeing to payment terms. It should also be an ongoing practice throughout the commercial relationship: a customer's financial position and payment behaviour can change rapidly.

Good information serves three complementary purposes:

  • Understand the customer: identify the legal entity, ownership, business history, financial position and track record in meeting commitments.
  • Support commercial negotiations: assess the company's size, profitability, market position and prospects to agree on terms that reflect the opportunity and the risk.
  • Make informed credit decisions: establish an appropriate credit limit and, where necessary, request advance payments, credit insurance or suitable guarantees.
Key principle: credit risk management should support profitable sales while protecting cash flow. Its purpose is not to reject every higher-risk customer, but to identify risks early and manage them through proportionate commercial and payment terms.

What information should you collect about a B2B customer?

Use a combination of financial, legal, behavioural and commercial information. No single source gives a complete picture of creditworthiness.

Financial information

Financial statements, profitability, cash generation, liquidity, indebtedness, equity and recent changes in financial performance. Review both the profit and loss account and the balance sheet.

Legal and corporate information

Legal identity, registration status, ownership, management, insolvency proceedings, material legal events and relevant group relationships.

Payment behaviour

Your own experience of payment delays, disputes, broken promises and payment trends, supplemented where appropriate by trade references and third-party payment data.

Commercial and qualitative information

Business model, customer concentration, market position, management quality, growth prospects and the strategic importance of the relationship.

Financial strength and payment behaviour are complementary. A financially sound company may still pay a particular supplier late, while a customer facing temporary difficulties may maintain a strong record of communication and payment commitments. Analyse both dimensions rather than relying on a single rating.

Information for credit analysis

Consider the customer's industry and economic environment

Industry trends, economic conditions, commodity prices, regulation and market demand can affect a customer's ability to pay. A downturn in construction, manufacturing or distribution, for example, may put pressure on margins, liquidity or financing.

However, industry risk is not the same as company-specific risk. Some businesses outperform their sector, while others struggle in otherwise healthy markets. Use sector information to contextualise the assessment, not to replace an analysis of the individual company.

Third-party ratings may give significant weight to sector-level indicators, particularly in markets where company-level financial disclosures are limited. Compare those assessments with information relevant to your own commercial exposure.

Where can you obtain reliable customer credit information?

The availability of company information varies considerably by jurisdiction, company type and disclosure rules. Published accounts may be available through company registries in some countries, while access may be restricted or limited elsewhere. Verify what is actually available for the customer concerned.

Sources of customer credit information and their limitations
Source What it can provide What to check
The customer Recent financial statements, management explanations, forecasts and operational updates. Reporting date, consistency and supporting evidence.
Official registries Legal identity, filings, corporate events and published financial information where available. Coverage, filing delays and local disclosure rules.
Business information providers Company reports, financial indicators, credit scores and monitoring alerts; examples include Dun & Bradstreet and Creditsafe. Methodology, freshness, geographic coverage and data sources.
Credit insurers Risk assessments, insured limits and, where provided, relevant payment or financial information. Scope of the service and whether the insurer's risk appetite matches yours.
Your accounts receivable records Actual payment dates, overdue balances, disputes and trends in the customer's behaviour towards your business. Data completeness and causes of delays, including internal billing issues.
Trade references Experiences reported by other suppliers, where lawfully and voluntarily shared. Potential bias, comparability and permission to disclose.
Sales teams and customer visits Current business developments, market signals and explanations for changes. Corroboration of subjective assessments.
Specialist investigations Deeper qualitative research in cases involving significant exposure or limited public data. Cost, independence and reliability of findings.

Ask the customer directly

For a significant commercial relationship, requesting information directly from the customer is often one of the most useful approaches. A constructive discussion can provide recent figures, clarify unusual movements in the accounts and build mutual trust.

If a customer declines to share information, first seek to understand why. Confidentiality policies or other legitimate constraints may apply. Where uncertainty remains, consider adjusting the credit limit, payment terms or security rather than drawing an automatic negative conclusion.

The level of investigation should be proportionate to the exposure. A business with a small number of high-value customers can justify more individual analysis; a company serving thousands of small accounts may need a more standardised, automated approach.

How data analytics and AI can improve credit information

Data analytics and AI can help combine financial information, payment histories, due dates, legal events and other relevant signals to detect patterns and prioritise credit reviews. These techniques are particularly useful when monitoring large customer portfolios.

However, model outputs depend on the quality, relevance, representativeness and timeliness of the underlying data. Incomplete datasets, opaque scoring methods or changes in customer circumstances can lead to misleading conclusions.

Practical recommendation: use external scores and AI-generated indicators as decision-support tools, not as unquestionable verdicts. Your own payment history with a customer may be more directly relevant to your exposure, provided it is accurate and interpreted in context.

Apply appropriate data-protection and confidentiality safeguards when collecting, sharing or processing information about individuals and businesses.

Turn customer information into practical credit decisions

  1. Confirm identity and exposure: identify the correct legal entity and estimate the amount and duration of credit requested.
  2. Assess financial capacity: analyse liquidity, profitability, indebtedness and cash generation.
  3. Review payment behaviour: examine your internal records and relevant external evidence.
  4. Consider the business context: account for industry trends, management explanations and commercial potential.
  5. Set proportionate terms: decide on a credit limit, payment terms and, if appropriate, guarantees or credit insurance.
  6. Monitor and update: review the assessment when payment behaviour, exposure or the customer's situation changes.

The objective is to develop the most realistic possible view of the customer's capacity and willingness to pay. Better information helps credit and sales teams make consistent decisions, protect cash flow and sustain profitable business relationships.

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