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Two key weaknesses of credit rating in preventing fraud

Credit checks and credit ratings alone are insufficient tools for establishing a customer relation in an era of rising economic crime and financial uncertainty.

Credit checks and credit ratings are well-used tools for assessing and communicating credit risk prior to extending credit. They can indicate a company’s financial position and ability to pay, based on available information about the business. However, fraud is characterized by manipulation and falsification of that information. This means that credit‐scoring models can produce misleading results since they rely on data that the company itself has provided, which may be incorrect or fabricated. In an era of rising economic crime and financial uncertainty, credit checks and credit ratings alone are insufficient. Two factors in particular undermine their effectiveness.

Written by

Silje Fostervold

Silje Fostervold
May 9, 2025

1. Reliance on outdated information

Credit checks and credit ratings depend heavily on historical data, and financial statements are one of the primary sources. Financial statements are typically published only once a year in Norway, typically around summer, meaning the information underpinning the evaluation will often be at least six months old, but often up to eighteen months old.

Our analyses show that although financial statements can indicate ongoing operations, a closer examination of other key factors, such as employee headcount, changes in management, or structural reorganizations, may reveal that the company has in fact been transferred to new owners, and thus effectively represents a completely different business than what the financial statements reflect. In a credit‐assessment context, this opens the door for actors to secure financing based on historical financial records that reflect conditions prior to the change of ownership, even though the actual business today is weakened or has ceased operations.

2. Trust in self‐reported information

Credit checks and credit ratings rest on the central assumption that the self‐reported information from companies, especially their annual financial statements, is reliable. In practice, however, experience shows that fraudsters can systematically manipulate or fabricate accounts to appear far more robust than they actually are.

A striking example is “Nannestad Pizza,” which submitted identical financial statements for seven different companies. Upon closer analysis, extensive manipulation of the figures for both 2021 and 2022 was uncovered. The new figures were small enough to avoid triggering a statutory audit requirement, yet large enough to display artificially improved profitability.

Under current rules in Norway, a company must meet two of the following three criteria to require audits: NOK 7 million in revenue, NOK 27 million in total assets, or ten employees. From 1 July 2024, these thresholds increased to NOK 9 million in revenue, NOK 39 million in total assets, or ten employees. By staying below these thresholds, many companies avoid external audit and can then submit inaccurate accounts without detection.

In the Nannestad Pizza case, after the accounting adjustments a mortgage was taken on the company, and assets were attempted smuggled out via border crossings between Turkey and Iran. Compared to industry norms, where the 2020 accounts reflected an ordinary pizzeria, the 2021 statements portrayed the company as highly profitable, based entirely on fabricated figures.

This example highlights the importance of supplementing traditional credit‐assessment tools with independent data sources, advanced analytics, and automated risk detection to uncover discrepancies that do not surface through standard credit checks.

Advanced fraud calls for advanced methods

New indicators of unscrupulous operations and criminal activity may be difficult to detect with traditional credit assessment. It requires comprehensive analyses of a broad spectrum of information sources to identify irregularities, a process that is both time‐ and resource-intensive. Many cases of accounting manipulation are even more sophisticated than the example above.

To streamline this “detective work,” several vendors have developed tools that can identify patterns and signals of fraud in companies that would otherwise receive favorable ratings from traditional credit checks. We are among these providers, and our tools can systematically flag indicators of unscrupulous or criminal activity in businesses. Our solutions enable our users to uncover risk quickly and efficiently, without having to invest large amounts of time in manual data collection, pattern recognition, and documentation.

Here you can read more about what information we provide to assist banks and companies in anti-fraud detection


Written by

Silje Fostervold

Silje Fostervold
Account Manager
silje@enin.ai

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