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Web Intelligence – Multinational Enterprise Group Data Extraction Challenge aimed to develop approaches that automatically extract important annual financial data of MNE Groups.
The European Statistics Awards Programme Web Intelligence competitions aim at stimulating innovation when retrieving data from the world wide web for producing European statistics. The goal of the Multinational Enterprise Group Data Extraction Challenge was to develop approaches that automatically extract financial data from the World Wide Web for MNE Groups.
A multinational enterprise group, abbreviated as MNE Group and sometimes also called multinational corporation, or simply multinational or international corporation, is an enterprise producing goods or delivering services in more than one country. MNE Groups publish their financial data and annual financial results (financial statements) on documents, referred to hereby as "financial" reports.
The competition dataset contained 200 MNE groups. Participants were required to develop a method which extracts the requested annual financial data for each MNE Group along with the reference year automatically. One of the key elements of the competition was to develop robust approaches for generic use on identically structured arbitrarily chosen datasets.
The MNE Groups Data Extraction Challenge was launched in March 2025, with a final deadline for both submissions and documentation in June 2025.
A total of 57 teams, comprised of 70 individuals from 21 countries, signed up for this challenge, with 12 teams following through by submitting solutions for evaluation. The results of the evaluation are announced below.
The participants were competing for three types of awards:
- Accuracy – aimed at reflecting the team’s performance in the extraction of annual financial data.
- Reusability – aimed at rewarding submissions which show great potential to be scaled up to European statistics production. The Reusability award is intended to support the most thoroughly described and documented solutions, with the most scalable, well described and open approach.
- Innovativeness – aimed at rewarding submissions which show the most originality in their approach. The Innovativeness award is intended to encourage cutting-edge solutions that go beyond current best methods.
Accuracy Award winners
| Place | Prize | Team name | Team members | Country |
|---|---|---|---|---|
| 1st place | 10 000 EUR | toad | Thomas Faria | France |
| 2nd place | 5 000 EUR | MUR | Miguel Ureña | Spain |
| 3rd place | 3 000 EUR | TheItalianJob | Pasquale Maritato Andrea Alessandrelli Fabrizio Tomasso | Italy |
Reusability Award winners
| Place | Prize | Team name | Team members | Country |
|---|---|---|---|---|
| 1st place | 10 000 EUR | spacedace | Máté Debreczeni Martin Lényi | Hungary |
| 2nd place | 5 000 EUR | toad | Thomas Faria | France |
| 3rd place | 3 000 EUR | MUR | Miguel Ureña | Spain |
Innovativeness Award winners
| Place | Prize | Team name | Team members | Country |
|---|---|---|---|---|
| 1st place | 5 000 EUR | spacedace | Máté Debreczeni Martin Lényi | Hungary |
| 2nd place | 3 000 EUR | toad | Thomas Faria | France |
| 3rd place | 1 000 EUR | MUR | Miguel Ureña | Spain |
Since the Reusability and Innovativeness awards both required thoroughly described and documented solutions we are happy to share the solutions by all winners:
Solutions of the Reusability and Innovativeness Award winners
- spacedace: GitHub repository
- toad: GitHub repository
- MUR: GitHub repository