Driving International Growth with Global Financials

Doing Business Internationally Can Be a Challenge.

Understanding the financial performance of customers, prospects, suppliers or partners is key to assess risk and opportunity. But in today’s global business environment, your customers and partners are often located in other countries.

On the surface, this might not appear to be such a challenge. Business is increasingly being conducted without borders, after all. Problems arise, however, when we consider that each country has its own filing requirements, financial reporting standards and generally accepted accounting principles (GAAP).

In response, assessing financial performance in a uniform manner can pose a real problem. Plus, laws and filing regulations are subject to constant change, which makes it near impossible to maintain any standardised views you may have created.

Or, that was at least until the launch of Global Financials from the Worldwide Network by Dun & Bradstreet.

Featuring 150 million financial statements for 170 countries covering public and private listings, our global solution provides access to standardised, comparable business reports and analytics benchmarking for different financial reporting standards around the world.

Today, more and more progressive businesses are leveraging Global Financials, in order to drive robust decisions and reviews of organisations from different countries, with seamless comparability of everything from balance sheets and profit & loss accounts, to ratios.

But you don’t need me to relay the (many) benefits of Global Financials, our sales team can do that. Instead I wanted to explore the platform’s emerging possibilities and how we’re unlocking the potential of data to drive international growth for our customers.

Because at the end of the day, it’s not just about how much data you have, it’s what you do with it.

Unlocking the power of data with Global Financials

One way we’re doing more with data is automating and developing predictive credit scorecards. As any credit professional can tell you, initial credit reviews and decisions on new accounts can be a subjective process that takes a lot of time and manual effort, especially when factoring in the abovementioned GAAP.

For one customer, with plans to expand its operations into new territories, it needed to quickly identify companies who might pay late or pose serious credit risks. Owing to its extensive trading history, favourable/unfavourable business flags and capability to create unique financial derivations and ratios, we knew this was within the remit of Global Financials.

So, we took the client’s portfolio, identified the relevant SIC codes and leveraged these next to WorldBase, to get a get a view on the types of companies our customer was doing business with. Specifically in terms of legal form, employees (actual or modelled), and annual sales (USD, actual or modelled).

Next, we profiled their customers in the territory in question using these dimensions, to see how many companies with the relevant profile were available in Global Financials, with unfavourable out of business flags. Using this profile, we then sought to find similar types of companies in other countries, within Global Financials.

We started with countries possessing similar GDP levels to the territory in question, and then gradually added more nations until we satisfied two dimensions. One being in terms of GDP, where we tried to remain as close as possible to the territory. But of course, as we added more countries to increase the sample size, we began to move away from this.

Secondly, we could have a sufficiently large number of unfavourable out of business flags, to satisfy the statistics that work well on larger numbers. It’s also worth noting that we slightly oversampled the unfavourable flags.

By leveraging this new subset of data, we were ultimately able to report our findings back to the customer, complete with an industry-specific scoring system that is able to predict, in the lowest 20% of scored cases, over 60% of future bankruptcies in the customer’s territory. And this is over a horizon of a bankruptcy happening in 1 to 5 years.

But despite the obvious benefit this brought for the client, the biggest success story lies in maximising the potential of data and Global Financials. While the volume of bankruptcies we can identify and predict is substantial, it’s also driven from the same data. This shows it’s not a data source issue – it’s simply what you do with the data at your disposal.

Leading the way to a data-driven future

In the innovative spirit of Dun & Bradstreet and Global Financials, our endeavours to set ourselves apart from the competition and solve complex problems doesn’t stop there. One additional way we’re striving to deliver yet more added value for customers is with the marriage of data and emerging technologies, such as AI.

Or more specifically, AI Layered Scoring, which combines deep learning with industry-standard credit scoring and is taking credit scorecards to an entirely new level, as proved when we tested our AI Layered Scoring methodology on the same Global Financials files. Even if it was just a preliminary test, the findings show that this new system is capable of predicting some 90% of bankruptcies in the lowest 20% of scored cases.

It’s constant innovation like this that is helping our customers to navigate and thrive in a time when the business landscape is subject to unrelenting change. Ultimately, as we’ve demonstrated, the data and will to drive smarter decision making is there. Sometimes it just takes the right partner to help connect the dots and overcome existing problems with a fresh, data-driven approach.