Global AI-powered Order-to-Cash platform, Sidetrade has today revealed global payment trends from the Sidetrade Data Lake. Never-before-seen in the industry, the global payment trends - based on the payment behavior of 20.7 million buying companies worldwide - enable companies, governments, and analysts to make data-driven decisions in a time of uncertainty.
Developed by Sidetrade’s best-in-class engineers and leading data scientists since 2015, the Sidetrade Data Lake is the heart of Sidetrade’s innovative Order-to-Cash AI solutions to enhance cash optimization. It is used by data-driven companies (i.e. suppliers) to understand and predict buyer payment behaviors.
A unique tool within the Order-to-Cash market, it is a repository of data of past B2B payment transactions. It is comprised of more than 593 million payment experiences worth a total of $4.6 trillion processed over the last three years from 20.7 million buyers worldwide. Today’s launch provides users with a free and interactive map into aggregated and anonymized insights from the Sidetrade Data Lake.
A resource for companies, governments, and analysts
The publication of global payment trends from the Sidetrade Data Lake is an industry-first and comes as global uncertainties and increasing inflationary pressures place a greater emphasis on cash and credit management.
Updated on a quarterly basis, the global payment trends give users access to never-before-available insights into how buyers pay their suppliers depending on country and industry, enabling them to better monitor customers’ payment trends across the world, predict payment behavior and decrease collection time. This provides invaluable support for effective decision-making and payment negotiations, thereby cutting days sales outstanding (DSO).
Sidetrade CEO, Olivier Novasque, commented: “Protecting and accelerating cash flow has never been so critical as bad debt risk and inflation are dramatically increasing everywhere. This can best be achieved if companies harness enough customer behavior data and become more forward-looking. Data science and artificial intelligence are essential to fighting against late payment. Since each buyer’s payment behavior is different, a dedicated and automated collection strategy is needed to be efficient.
“We’re delighted today to offer a first look into the Sidetrade Data Lake and bring the power of true AI to companies at a time when they need it the most.”
Innovation and digital transformation to support businesses
The Sidetrade Data Lake harnesses the power of Sidetrade’s next-generation AI technology (aka Aimie) to predict the likelihood that a customer will pay late. Aimie then recommends customer-specific collection strategy based on buyer payments patterns, and other data insights.
Sidetrade Chief Product Officer, Rob Harvey, added: “In B2B companies, every CFO wants industry benchmarking data on their customer payments; they thrive on data. But how well do finance teams actually know their customers? Do they know who is likely to pay them late? Which industries wait the longest to get paid? Now, CFOs can finally understand their customer behaviors, better understand their competition, and make smarter decisions; much like Tesla uses driver data to make innovative changes, enhancing and optimizing the driver experience.
“With the Sidetrade Data Lake, we unlock enterprise data and simplify access to payment data management. At Sidetrade, we are committed to saving time for businesses, exploring smart efficient processes in the Order-to-Cash cycle, assisting in decision-making, and sharing information in real-time. Sidetrade is the Waze for business payments!”
The Sidetrade Data Lake is the result of years of hard work of collecting, cleaning up, matching, and enriching huge volumes of data. Transactions between Sidetrade’s customers (the suppliers) and their buyers within the Sidetrade Data Lake are aggregated, anonymized, and layered with algorithms to determine a predictive payment metric for each analyzed buyer company. This is the engine behind Sidetrade’s AI technology. It takes decision-making support to the next level, providing data-based recommendations on the most effective collection, dispute resolution and risk control actions.
Mark Sheldon, Chief Technology Officer of Sidetrade: “We are proud to offer a first look at our Data Lake today and showcase the depth of our data, technology and true AI capabilities.
“What is particularly exciting about the Sidetrade Data Lake technology, is the fact we’ve not only succeeded in getting large amounts of data cleansed, matched and into one place, but that we’ve also layered that with next-generation AI and predictive capabilities, and are able to measure its value. This latter part in particular is something that many companies often struggle with, and why we’re proud to be able to clearly demonstrate the value to our customers.”
Best and worst payment behaviors around the world revealed
Leveraging its Data Lake, Sidetrade reveals the best and worst markets and industries for late payments over the last three years.
A global snapshot
On average, companies around the world pay supplier invoices 21 days late – taking the length of time between an invoice being issued to getting paid, to a total of 53 days on average.
Scandinavian businesses tend to pay the quickest overall, in particular Sweden, with a delay of just 7 days, well below the global average.
Getting back to pre-pandemic unpaid invoice ratios
Over two years on from the start of the pandemic, the US, France, and Italy still haven’t fully reverted back to their pre-pandemic unpaid invoice rates according to the Sidetrade Unpaid Invoice Tracker. Conversely, Belgium, Spain, the UK, and the Netherlands now have better unpaid invoice ratios than before the start of the pandemic.
France holds the title for the worst amongst the seven countries tracked, with 25% of the value of all overdue invoices as of April 16, 2022.
27-day delays in the US
US companies rank tenth globally for longest payment delays, with a mean of 27 days. The industry with the shortest payment delays in the US is Manufacturing: 22 days. The worst industries are Financial Services & Insurance, and Leisure & Hospitality: 30 and 31 days, respectively.
Payment disparities in Europe
Across Europe, there are significant disparities in payment delays from country to country, ranging from 7 days (Sweden) to 26 days late (Ireland). On average, it takes companies in Europe 45 days to collect payment – a mean delay of 16 days.
UK & Ireland exceeding European average for payment terms and delays
Companies in the UK and Ireland are among the top four worst in Europe for payment delays, with means of 21 and 26, respectively. This is despite both countries having higher payment terms (34 days in the UK, 31 days in Ireland) than the European average of 29 days.
In the UK, the industries with the shortest payment delays are Utilities & Energy at 19 days, and Retail & CPG at 20 days. Industries in the UK with the longest payment delays are Financial Services & Insurance at 25 days, and Public Services, HR Services and Transportation & Logistics at 24 days.
Looking at the Sidetrade Unpaid Invoice Tracker, almost all UK industries appear to have recovered from the pandemic in terms of late payments, most showing pre-pandemic unpaid invoice rates. The exceptions are, Public Services, Other Services and the Food industry. The latter has risen from 14% at pre pandemic levels, to 21% of invoice values being deemed late (10+ days after their due date) as of 16 April 2022.
France is amongst the worst performing European countries for late payments. Their sectors with the shortest payment delays are Retail & CPG, and Manufacturing, both at 17 days. The worst industries in France for late payments are Leisure & Hospitality, and Public Services at 24 days. France still hasn’t recovered from the Covid-19 crisis when it comes to late payments. The rate of unpaid invoices across every industry in France is still above pre-pandemic level, at 22.7%.
Josie Dent, Managing Economist at Centre for Economics and Business Research (Cebr): “After the hit businesses took during the pandemic and lockdowns, which caused a significant rise in late payments, the global economy is now experiencing a new source of pressure. Across the world, inflation is accelerating, driven by energy prices and supply chain disruptions. While both of these factors were already at play at the start of the year, the conflict in Ukraine and sanctions on Russia, as well as recent lockdowns in key Chinese cities have further added to the inflationary environment and the outlook for price growth. These increasing costs for fuel, energy and raw materials add to businesses’ financial strain at a time when many are still recovering from the pandemic, making late payments more likely.
“Therefore, as businesses’ bills come due, often at higher prices than previously, many will find themselves having to prioritize which they can afford to pay immediately, and which will need to wait.
“In the US, consumer price inflation rose to 8.5% in March, up from just 2.6% a year earlier. In the meantime, the average share of unpaid invoices by value rose from 14.5% on 31 March 2021 to 17.5% on the same day in 2022. Businesses will also be affected by the Federal Reserve’s interest rate rises expected this year. In March, the Fed voted to increase interest rates for the first time since 2018, with projections pointing to a further six rate rises in 2022 alone, raising costs for those with debt.
“Businesses in other countries are also facing rising costs and interest rates. The share of late payments by value stands at 24.7% in France in the latest data (16th April), compared to 21.0% at the start of the year, while inflation picked up to 5.1% in March.”
The Sidetrade Data Lake Data Science analysis
20.7 million buyer companies 593 million+ invoices processed in the last three years $4.5 trillion worth of invoices
Daily analysis of the data hosted in the Sidetrade Cloud leveraging machine learning algorithms
1-Jan-2019 through 31-Dec-2021
How the Sidetrade Data Lake works
The Sidetrade Data Lake leverages data collected from multi-tenant SaaS Software. The data within the Sidetrade Data Lake has gone through a complex and layered process of matching, crawling, enriching and multi-step machine learning. Highly effective machine learning is made possible by the huge volume of supplier data within Sidetrade’s cloud-based Data Lake.
Sidetrade’s AI technology (AKA Aimie) utilizes a combination of machine learning and algorithms to offer recommendations on cutting DSO. Because the system and models are deployed in real-world scenarios, Sidetrade is uniquely able to accurately prove and monitor the Data Lake’s value, and performance.
This announcement comes shortly after Sidetrade’s recognition as a Leader in the first Gartner® Magic Quadrant™ for Integrated Invoice-to-Cash Applications.
Christelle Dhrif +33 6 10 46 72 00 [email protected]
Rebecca Parlby +44 7824 505 584 [email protected]
About Sidetrade (www.sidetrade.com)
Sidetrade (Euronext Growth: ALBFR.PA) provides a SaaS platform dedicated to securing and accelerating cash flow. Sidetrade’s next-generation AI, nicknamed Aimie, analyzes $4.6 trillion worth of B2B payment transactions daily in the Sidetrade Cloud to predict customer payment behavior and attrition risk of more than 21 million companies worldwide. Aimie recommends the best cash collection strategies, intelligently automates actions on the Order-to-Cash process, and dematerializes customer transactions to enhance productivity, performance and working capital management.
Sidetrade has a global reach, with 300 talented employees based in Paris, London, Birmingham, Dublin, Houston, and Calgary, serving global businesses in more than 85 countries. Amongst them: Tech Data, KPMG, Nespresso, Hearst, Expedia, Manpower, Securitas, Randstad, Engie, Veolia, Inmarsat, and Bidfood.
For further information, visit us at www.sidetrade.com and follow us on Twitter @Sidetrade.
In the event of any discrepancy between the French and English versions of this press release, only the English version is to be considered.