Improving Credit Risk Management with Trade Payment Insights & Analysis
A leading sustainable building materials and construction solutions business responsible for many of the UK’s biggest construction projects. The client’s Head of Credit, who is ultimately responsible for the cashflow, risk performance and trade opportunities, has used data and analytics from Dun & Bradstreet’s Global Trade Exchange Programme.
- 60% reduction in departmental budget cost over a two-year period
- 75% reduction in bad debt
- 65% reduction in accounts on 'stop'
- Average debt per account halved
The Challenge
This client is a key supplier to the entire construction sector, with a wide customer base encompassing building and infrastructure contractors, local authorities, builders’ merchants and a range of industrial customers. Their supply contracts include ongoing commitments, so they need to consider wide and often longer-term implications when making credit decisions.
When a contract opportunity arises within the locality served by one of their facilities, the client needs to provide credit quickly and efficiently. Dun & Bradstreet’s data and analytics provide vital intelligence to support our client in making an insightful, yet swift lending decision, which benefits both the client and their customers. Relationships are important and a fast decision can support the successful closing of a deal. For our client, deals are often long-term commitments with a customer which is a primary objective, especially in a challenging economic environment.
The Solution
The organisation is part of Dun & Bradstreet’s Global Trade Exchange Program, and has been providing trade payment data to Dun & Bradstreet since 2017. In turn, they have received comparative analytics for use within their credit team. These analytics enable the client to benchmark against the market in terms of DSO (Days Sales Outstanding), help identify ways to reduce DSO and improve overall credit risk management. DSO is a measure of the average number of days that it takes a company to collect payment after a sale has been made – the lower the number the better as this supports healthy cash flow for the client.
Trade payment analytics are key to building a holistic view of payment performance.
The credit team combine their own internal data with Dun & Bradstreet trade payment data to derive further metrics such as:
- Weighted average terms (terms of trade weighted by the average invoice value).
- Weighted average days to pay (the days between when an invoice goes on and comes off the ledger).
These measures provide insight on how quickly an organisation pays, per value of sale. By ingesting external data, the credit team can benchmark performance against the market.
Quick payment analysis is used as an external benchmark indicator of how quickly the organisation is being paid against other businesses. The analytical breakdown shows what percentage are paid in the same time, or faster than others.
In constructing a risk tracker, the client has also been leveraging Dun & Bradstreet’s COVID-19 Impact Index which indexes businesses against a range of factors to indicate how they are faring through the COVID-19 pandemic. The index provides an additional lens for comparison on business health and enables a multi-dimensional perspective.
Some customers provide a solid and justifiable explanation of late payment and the client works with these accounts towards a mutually agreeable solution. However, the trade payment data enables the credit team to interrogate the information, in order to validate these explanations and take any relevant action to address late payments when appropriate.
Furthermore, the data provided is used not only for decision making but also management reporting and securing senior level support for the credit team. It also supports their efforts and work with the sales team to drive increased discipline when quoting for contracts, including asking sales to check the client’s credit before signing a deal.
The Benefits
The client focuses on five key areas when reviewing credit risk of a new customer:
- What revenue will this account bring?
- How strategically important is this account?
- How likely is this client to go bankrupt?
- How likely are they to pay on time?
- How difficult will it be to serve this client?
The trade payment analytics from Dun & Bradstreet play a key role in building a fuller picture and assessing the level of credit risk.
The resulting decisions and actions helped to reduce the number of accounts on ‘stop’ (those that the client halts supply for due to lack of payment) by around 65% and improved credit management. The client has also seen a reduction in average value owed from £20K per account, to below £10K, which has in turn improved their own cash flow and reduced bad debt.
Conclusion
This client has experienced many benefits from contributing trade payment data and gaining access to key analytics to benchmark incoming payments.
Participation in Dun & Bradstreet’s Global Trade Exchange Program is a powerful way to increase the predictiveness of the insight you use to make credit decisions and manage risk.
At no cost, your business can support the credit community by sharing customer payment experiences confidentially.
Find out more about the Dun & Bradstreet Global Trade Exchange Program.
We need a multi-dimensional view of trade credit to enhance the assessment of credit risk, especially in uncertain economic conditions. My team have achieved a ~75% reduction in bad debt over a two-year period by using additional analytics and data sources.