For companies you've sold or lent to before, you might look at their payment history. Or if you haven't had any past dealings with these customers, some external databases offer aggregated payment history data, which might be of peripheral use.
But with little real idea of their probability of default, you'll inevitably have to offer shorter terms with lower credit limits or err on the side of caution.
But what if there were a better way? One that didn't mean you had to pass up some of the best opportunities among the many companies around the world that aren't required to file their financials.
Coverage approaching 99%The good news is that we've added a new qualitative score to our financial strength module. Reviewed weekly, these scores are available on Orbis, our global database of more than 200 million private companies, and in the catalysts that Orbis powers.
The addition of this new qualitative score increases the proportion of companies for which we provide financial strength information from somewhere below 15% up to nearly 99% of all companies.
How do qualitative scores work and how reliable are they?
We have a well-established relationship with Italy-based credit rating agency, modeFinance, whose standardising "MORE score" already appears on most of our company records that do have financial information; the new qualitative score is based on modeFinance's research on and use of non-financial information in our databases. These variables include:
- The size and strength of shareholding companies and subsidiaries
- The average MORE score for the sector in which it operates
- Its management and number of directors
- Its experience and structure, such as years in business, number of employees, and capital and legal form
The variables carry different "weights", which are fed into a sophisticated model. Group financial strength carries a very high weight, for example, while company structure variables, such as number of directors or capital, are relatively light. This model generates a qualitative score, which ranges from A (highest) to E (lowest) for five different classes. We offer explanatory information alongside some of the scores.
Given the considerable variation in how much of the above information is available for any given company, we also publish a confidence level.
These two new values allow users to make more reliable decisions.
Based on assessing data on a very large set of companies, modeFinance's research demonstrates this assertion. With their qualitative model (below, left), their aim has been to mimic their quantitative model (below, right). How close the middle curve in each case is to the top curve indicates how reliable the model is. The diagonal line shows an entirely random model.
We'll explain this modelling more fully in a white paper due later this year. In the meantime, if you have any questions about how this affects your existing or future subscriptions to our products, do please get in touch.