According to the Dun & Bradstreet 4th Quarter Analysis 2016, late payment times rose during the fourth quarter of 2016, marking a fitting end to a year which saw late payment times track a jagged path following two years of sustained falls.
The recent up-tick in late payments appears to reflect a slowing in the overall rate of economic growth and the general sluggishness of the business sector.
- Larger companies were slowest to pay invoices in Q4 2016. Larger firms consistently settle invoices later than the national average
- During the past five years, Tasmanian business has gone from making the slowest late payments to top of the class. ACT companies have distinguished themselves as being consistently tardy over the same period.
- Mining may have been the slowest paying sector for the quarter, but Communications stood out as the only industry to record a year-on-year decrease in payment times. The result represented a sharp turnaround from Q3 2016, during which Communications was the slowest paying sector.
- All industries, other than Communications, experienced an increase in late payment times over the past year, with the Mining, Utilities, Manufacturing and Retail sectors paying slowest. It is interesting that after that initial spike, the longer firms have operated, the lower the late payment times, until they reach more than 50 years.
To read the full story click on the attachment: DB Late Payments Q4 2016
About Late Payments
Late Payments analyses trade information from Dun & Bradstreet’s Commercial Bureau, the largest database of business-to-business payment information – capturing 778,000 entities – in Australia. Monthly trade transaction files are collated and advanced analytics is used to provide a summary of how late entities pay for goods and services after payment is due. Previously released as Trade Payments Analysis, Late Payments now provides a quarterly report with a breakdown according to sector, size, age and location of entities.
Business-to-business payment information reveals how an organisation is paying its existing obligations. It is a highly predictive data set and a critical element in credit risk scores and business failures forecasting. The predictive nature of trade data combined with its monthly availability enables businesses to properly assess credit risk with real time information.
Media interviews with Stephen Koukoulas, Economic Adviser to Dun & Bradstreet, can be arranged by contacting 0467 647 508 or firstname.lastname@example.org