Late payments make up over a third of global pay cycles

Late payments now account for 37% of the global days-to-pay cycle, according to new analysis from Sidetrade's Data Lake, based on more than USD $8 trillion of invoice-level B2B transactions.

The findings point to a widening gap between contractual payment terms and when suppliers actually receive cash. The dataset covers payment behaviour from more than 42 million buying companies worldwide. It suggests that shortening commercial terms does not reliably translate into faster payment, increasing the importance of post-invoice execution and collections discipline in cash predictability.

Globally, businesses took an average of 51 days to get paid in 2025: 32 days of contractual terms plus 19 days of delay after the due date. Sidetrade described this post-due share as a structural shift that complicates cash-flow forecasting and working-capital management.

Country gaps

The analysis shows wide differences between countries. The Netherlands recorded an average 40 days-to-pay, including 12 days of delay. India averaged 77 days-to-pay, driven by 43 days of delay beyond agreed terms.

Sidetrade highlighted a 37-day gap between those two markets as a measure of cash exposure for multinationals operating across regions. It argued that payment discipline, more than regulation or negotiated terms, explains much of the variation.

US picture

In the United States, the average delay was 25 days, though results varied widely by sector. Financial Services, Insurance, and Real Estate averaged 57 days-to-pay, including 27 days of delay. Manufacturing and HR Services were faster, with 24 days of delay and days-to-pay of 54 and 49, respectively.

The analysis links these differences to industry-specific practices and internal processes such as approval chains and Order-to-Cash operations. It also suggests aligning credit policies and accounts receivable strategies with observed payment behaviour in each segment.

Europe comparison

Sidetrade's data puts Europe ahead of the United States on payment discipline, with 18 days of delay versus 29 days. It also shows substantial variation within Europe despite a shared EU regulatory backdrop.

The Netherlands was highlighted again, alongside Germany, Sweden, Finland, and the Czech Republic, at 12 to 15 days of delay. Spain and parts of Southern and Eastern Europe were described as lagging by weeks.

Germany averaged 15 days of delay, with ICT and Transport & Logistics underperforming the national baseline. France averaged 19 days, ranging from 17 days in Retail and Transport & Logistics to 24 days in HR Services. The UK averaged 21 days of delay, with Life Sciences and Manufacturing among the slowest, according to Sidetrade.

"Late payments are structural and consistently exceed statutory limits. For policymakers, they offer real-time insight into underlying economic pressures," said Mark Sheldon, CTO at Sidetrade.

Sheldon also outlined the operational impact for suppliers.

"For enterprises, payment delays undermine cash forecasting, inflate accounts receivable costs, and weaken balance-sheet confidence. Renegotiating commercial terms treats the symptom. Controlling the Order-to-Cash cycle addresses the cause," he said.

Data and AI

Sidetrade also described how it builds and uses its Data Lake and AI models. Customer payment behaviours often sit across multiple systems, including ERP and CRM platforms, spreadsheets, and manual processes. This fragmentation can make it harder to identify the drivers of delay.

"We began by building the data foundation to analyze the Revenue-to-Cash," said Sheldon.

The Data Lake has been used since 2016 to train Sidetrade's AI models. In 2025, it captured about 285 million invoices representing USD $1.7 trillion. Sidetrade said its AI system, Aimie, executed or recommended more than 5.1 million collection actions in 2025 and supported a 49% increase in cash collection efficiency.

"Quality data is the foundation of AI. Without it, there's no learning and no intelligent Order-to-Cash," said Sheldon.

Sidetrade said it aggregates more than USD $8 trillion in anonymised B2B transactions and processed more than 1 billion invoices over the past five years. It added that its industry segmentation is derived from about 33% of invoices with definitive vertical tagging, while the remaining volume informs global baselines.

"Autonomous decisioning in finance doesn't come from a model alone," said Sheldon. "It comes from the scale, structure, and governance of the data behind it. Aimie is trained on anonymized, real-world B2B payment behavior, using Order-to-Cash-specific models, deployed within a governed and private environment. That data foundation is what allows our autonomous agents to prioritize collections, surface disputes, flag emerging risk, and forecast cash with a level of accuracy and operational efficiency that generic AI agents cannot match."