Account-based credit assessment: why real-time data complements credit bureaus

Classic credit assessment is an established part of risk processes for many companies. Commercial credit reporting agencies provide important information about a company's credit history to date and help identify payment defaults at an early stage.

However, particularly for small and medium-sized enterprises, a purely backward-looking approach reaches its limits. A company's economic situation can change significantly within just a few months — for better or worse. Classic credit information does not always reflect this development immediately.

This is precisely where account-based credit assessment comes in. It supplements existing credit reporting agency information with the analysis of current transaction data from the business account. This creates a more comprehensive picture:

For providers in leasing, factoring, telecommunications, energy supply, or other sectors with recurring payment obligations, this combination can create a more well-founded basis for decisions — particularly where a potential customer would initially be rejected in the classic assessment process.

ConversionUp therefore does not aim to replace established credit reporting agencies, but rather to supplement them specifically with current account data.

What is account-based credit assessment?

In an account-based credit assessment, transaction data from a business account is analysed in a structured manner — following the account holder's corresponding authorisation.

The basis for this is open banking. Via regulated interfaces, authorised account information services can access payment account data that has been authorised for release. PSD2 has created a European regulatory framework for such services.

At ConversionUp, the analysis covers account activity over the past twelve months. This period makes it possible not only to look at a single snapshot, but also to identify longer-term developments and seasonal fluctuations.

Individual transactions are not analysed in isolation. What matters are patterns and financial signals that allow conclusions to be drawn about a company's current economic stability. These include, for example:

• development and regularity of income
• available liquidity reserves
• recurring payment obligations
• returned direct debits
• payment discipline towards suppliers
• tax and social security contributions
• seasonal fluctuations and liquidity bottlenecks

The result can then be integrated into a company's existing credit or acceptance decision.

Account-based credit assessment, PSD2, and AIS: the distinction

These terms are often conflated, but describe different levels.

PSD2 refers to the regulatory framework for payment services and, among other things, for access by authorised third-party providers to payment accounts.

An Account Information Service, or AIS for short, is the regulated technical service through which authorised account information can be retrieved. Account information services are among the payment services regulated by PSD2.

Account-based credit assessment, by contrast, is the specific use case: the available account data is analysed against defined criteria in order to allow a current assessment of the financial situation.

Account access is thus the technical foundation. The actual value creation arises from the structured analysis and the incorporation of the results into the decision-making process.

Account-based credit assessment and credit reporting agencies: history meets the present

Account data and classic credit information answer different questions. They should therefore not be regarded as competing methods.

The decisive question is therefore not: credit reporting agency or account? But rather:

ConversionUp is based precisely on this principle. A classic credit reporting agency review remains the established first step. If the result is clearly positive, the decision can be made immediately.

However, if a rejection or a borderline case arises, account-based credit assessment can be used as a second look. This provides the company with an additional basis for decision-making before a fundamentally interesting customer is finally rejected.

What signals does a business account provide?

A business account contains numerous pieces of information about a company's current financial situation. What matters here is not the examination of individual bookings, but the structured analysis of relevant patterns.

1. Income structure and revenue development

Regular incoming payments are an important signal of a company's operational stability. An analysis can, for example, identify whether income is stable, growing, or continuously declining over the period under review.

Dependence on individual large incoming payments can also be relevant. A company with many regularly paying customers has a different risk profile than a company whose liquidity depends heavily on a few major customers.

2. Liquidity reserves

For solvency, it is not solely the level of income that matters. Equally important is the question of what liquidity is actually available.

The account-based analysis can show how account balances develop over an extended period and whether sufficient financial reserves exist to meet ongoing obligations.

3. Payment discipline towards suppliers

Payments to suppliers and service providers made regularly can indicate orderly business operations. Conversely, an accumulation of late payments or irregular servicing of recurring obligations can indicate mounting financial pressure.

4. Returned direct debits

Returned direct debits can represent a relevant risk signal — particularly if they occur repeatedly. A single returned direct debit need not, on its own, permit a conclusion about a company's creditworthiness. However, if such incidents accumulate, this can indicate liquidity bottlenecks or insufficient account cover.

5. Tax and social security contributions

Regular payments to tax authorities, social insurance bodies, or other public entities form part of normal payment activity for many companies. Irregularities or notable changes can be taken into account in the overall picture of the analysis.

Here too: individual transactions are not assessed in isolation. What matters is the development over an extended period.

6. Recurring obligations

Rent, leasing instalments, financing arrangements, and other regular charges show what fixed payment obligations a company already carries. Combined with the development of income and liquidity, this allows a better assessment of how much financial headroom exists for additional obligations.

7. Seasonal patterns

Many business models are subject to significant seasonal fluctuations. A review covering only a few weeks or months could therefore produce a distorted picture. The twelve-month period considered by ConversionUp makes it possible to account for typical peak and trough phases.

This can significantly improve the informative value of the assessment, particularly for companies with seasonal business models.

Where is account-based credit assessment used?

The integration of current account data can be useful at different stages of the customer lifecycle.

New customer assessment

For new customers, account-based analysis can be used in addition to the classic credit assessment where a more differentiated evaluation is required. This can, for example, be useful for higher contract values, longer contract terms, or company structures that are difficult to assess.

Second look for initially rejected customers

The most important application area for ConversionUp is the secondary review.

Many companies now work with fixed acceptance and rejection criteria. If a prospective customer falls below a certain score or fails to meet individual criteria, the application is rejected automatically.

The problem: a classic credit assessment can only take into account the information available to it. The company's current economic development may remain unaccounted for.

An account-based credit assessment creates a second decision layer here. Instead of immediately and finally rejecting a customer, they can be offered the opportunity to demonstrate their current economic situation through analysis of their business account.

This opens up the possibility, particularly for small and medium-sized providers, of shaping their acceptance processes more differentially without having to replace their existing assessment procedures.

Ongoing review of existing customers

Depending on the business model, a renewed analysis can also make sense for existing customers — for example, before increasing a credit limit, extending a contract, or concluding an additional contract. The respective legal and data protection requirements must, of course, be observed in this context.

Fewer rejections without blindly increasing risk

In many automated assessment processes today, there are only two outcomes: acceptance or rejection.

An additional data source enables a more differentiated decision. This allows companies to identify potentially good customers who would initially fall through the net based on their classic credit information.

Account-based credit assessment can thereby support three key objectives in particular.

Higher acceptance rate

Not every negative or ambiguous credit reporting agency assessment automatically means that a company is currently unable to pay. An additional review of current account data can enable a reassessment.

Controlled default risk

A higher acceptance rate should not arise from simply lowering assessment standards. The better approach is to incorporate additional information into the decision. ConversionUp therefore creates an additional data layer for customers who would otherwise be rejected.

Shorter time-to-yes

Particularly for small and medium-sized business customers, manual follow-up checks are often laborious. Documents must be requested, reviewed, and assessed internally. A standardised account-based analysis can substantially streamline this process and make decisions available more quickly.

PSD2, data protection, and secure account access

Account data is among a company's particularly sensitive information. Accordingly, a clearly regulated and secure process is of great importance.

Access to account information takes place via a regulated account information service and only within the scope of the access that has been authorised. PSD2 provides a regulated framework for the relevant payment services and their providers.

The account holder actively decides whether to allow access.

For companies, this means: account-based credit assessment is not covert data retrieval. The customer is knowingly involved in the process.

In addition, the requirements of the GDPR must be observed when processing personal data. Which legal basis applies to the specific process depends on the particular design and use case in question.

For ConversionUp, "compliant by design" means that data protection and regulatory requirements are not added retrospectively, but form part of the technical and organisational process design from the outset.

Account-based credit assessment as a new building block in risk management

Classic credit reporting agency assessment remains an important part of professional credit assessment processes.

However, a company's economic reality does not consist solely of its past.

Current income, liquidity reserves, payment obligations, and actual payment behaviour can provide additional information that is not visible, or only visible with a delay, in classic credit data.

Account-based credit assessment therefore combines two perspectives:

This gives rise to a particularly relevant use case, especially as a second look for initially rejected business customers. Companies do not need to replace their existing credit assessment processes for this purpose. They can extend them specifically with an additional review stage.

ConversionUp offers a leading B2B solution for account-based credit assessment in this regard and is aimed in particular at small and medium-sized providers who want to get more out of their existing enquiries — without giving up their risk assessment.