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The importance of quality data in credit decisions

Collecting, aggregating, unifying and controlling sources of information on companies is time-consuming but it is a necessary expertise to have reliable and quality data. For credit management, it is a necessary step to guarantee informed credit decisions.

Data, an undeniable value for the company

In the age of Big Data, data is perceived as the main fuel for steering strategies and operations. In the context of credit risk management in a BtoB relationship, guaranteeing quality, fresh and exploitable data is essential to all good decisions.

Erroneous, obsolete, incomplete, duplicated, not linked to the company and not centralized, the risks linked to the quality of the data are numerous. This can lead to biased decisions, resulting in errors in outstandings and the prediction of non-payment, sometimes resulting in financial losses.

Data is an essential component of the process of collecting and aggregating (automatically or manually) heterogeneous sources of information. Unified and updated, it brings value. Obsolete or of poor quality, they have only a relative value, and can prove to be a real handicap by distorting the appreciation of the reality of a business relationship.

Heterogeneity and complexity of data

In customer risk analysis, data on companies comes from several external and internal information sources. Very often, this data is raw and comes from multiple databases, files, APIs or manual collection. It can be legal or private, of various qualities and formats.

For example, legal notices: their function is to make public very precise information when a company is created, modified or dissolved. However, the inaccuracy, amputation, obsolescence or temporality of certain information can distort the reality in the analysis of a file. Therefore, in order to exploit the data held on its commercial partners in a precise and accurate manner, controls must be carried out by experts who have a perfect command of the content and sources of information. […]

Guaranteeing quality data is a job

As you can see, collecting and aggregating data on companies is not enough to take advantage of it. It is also necessary to have a broad culture of legal life, as well as of financial analysis of a company to get value from it. This expertise allows to give sense to the temporality of the events in the credit decision making.

In this logic, it is therefore important to know how to surround oneself with a business information partner who must be able to aggregate and unify data on companies with a true qualitative approach.

For credit management, data quality is essential for informed decision-making. This is a real expectation of credit managers when we know that in the age of open data, 10 to 15% of legal data on companies are subject to anomalies or errors.

In a context where reliable data is a real advantage for predictive analysis and the subsequent credit decision, it is important for credit managers to choose a business information provider with the highest quality approach. Indeed, this is a powerful lever to optimize credit risk management.

To meet this major challenge, Ellisphere has set up a team dedicated to data production and quality. For example, this team performs algebraic and consistency checks on the annual accounts published on its Ellipro information platform, with manual rework when errors are detected.

As you can see, without reliable data, solid and efficient decision-making is not possible.

Data production and exploitation: an extremely wide range of expertise required

With the multiplication of Open Data sources available on companies and the increase in the volumes of data potentially accessible, the quality of data must be better than ever.

Regardless of its size, function or sector, every organization must be attentive to the quality of its internal and external data. If not, the lack of quality can end up being very expensive.

In credit management, good use of company data is often closely linked to the choice of a business information provider. In order to refine and guarantee the relevance of credit decisions in a constantly changing economic and legal context, the business information provider must:

  • Be a real expert in the processing of corporate information data, mastering the intricacies of legal publicity with a real quality approach to the data disseminated and monitored,

  • Have implemented a proven methodology for the aggregation of data from heterogeneous sources,

  • Master financial analysis and early detection of default, including the development of decision support tools such as scoring.

In conclusion, having and using reliable data supports good credit decision making, but requires the support of BtoB information experts.

Bernard Simon

Market Manager Risk Management


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