ORIGINAL RESEARCH

AI in Cross-Border Collections — Year One Data

Reevol Atlas + collections agent data: DSO reduction, contact rate improvement, dispute reduction. Q1 2027.

AI in Cross-Border Collections — Year One Data

Reevol Academy's research stream covers original, primary-data investigations into the technologies and operating practices that are reshaping cross-border B2B trade. This report is one of four flagship studies queued for the 2026–2027 calendar.

Scope

This report investigates Reevol Atlas + collections agent data: DSO reduction, contact rate improvement, dispute reduction. Q1 2027. Findings are based on a combination of operator surveys, telemetry from production systems, and structured interviews with operators across major B2B trade corridors.

Methodology

Survey instrument — multi-section structured questionnaire fielded to operators across the priority B2B trade corridors
Telemetry — anonymised production-system data from Reevol's deployed customer base
Interviews — semi-structured conversations with operators in sales, finance, and operations roles
Validation — peer-reviewed by independent industry advisers before publication

Why it matters

There is no shortage of vendor commentary on AI in trade; there is a shortage of grounded, primary-research data on what's actually working in production. This report is built specifically to fill that gap.

Get notified

We publish each flagship report to a list of operators and analysts who've signed up in advance. To get the report on the day it ships, contact us with your role and corridor.

While the report is in field, the Academy's existing coverage of the topic area gives a useful baseline:

In field. This page is updated as the research advances. Findings are released on the schedule shown in the Research hub.