How access to standardised data can help you mitigate credit risk

One of the main tasks of credit and procurement professionals is to assess the creditworthiness of potential customers or suppliers, many of them with a multi-national presence. Complicating this job and making it much more difficult than it needs to be is the fact that a wide variety of credit scores, ratings and metrics are used depending on country or jurisdiction.

The criteria that underlies credit rankings and metrics from nation to nation are usually based on factors specific to those regions. For this reason, credit scores in one country might not, and probably won't, apply at all in another jurisdiction, which, after all, differs culturally, governmentally and/or financially from other regions. This can make it extremely challenging to effectively judge the creditworthiness of a company that operates in an area whose rules, regulations and credit scoring systems differ from those which you are accustomed to working with.

Naturally, if you're unfamiliar with the way that information is reported in a certain country or area, it will make it that much harder for you to process and understand, much less accurately judge, the creditworthiness of a company based in that area. We addressed this issue in depth in a white paper called: Internationally standardised company information for credit risk.

Orbis's standardised data can help you make sense of different credit reporting standards 

Fortunately, the standardised and structured data offered by our Orbis database – which covers more than 220 million companies across all countries worldwide – can help you wade through and make sense of the different reporting standards that occur from nation to nation.

Using financial strength models – created by 6 providers who specialise in the business risk assessment space – Orbis's data is able to take into account and rationalise cultural, environmental and reporting differences and anomalies between countries. This allows you to analyse data in context, giving you a clearer and more certain picture of the credit risk associated with a single company or several companies in comparison.

The image below illustrates how Orbis's use of statistical models – based on sophisticated mathematical techniques like fuzzy logic – can clarify and smooth out differing regional standards and factors. This can offer you a more comprehensible, measurable and comparable set of variables by which to make your risk calculations.

Armed with this more intelligent data, you'll be able to make vital decisions based on "apples to apples" comparisons, rather than "apples to pears" guesswork. In this, and many other ways, Orbis's structured and standardised information can take much of the mystery and conjecture out of your risk assessment research.