English

Towards automating Numerical Consistency Checks in Financial Reports

Computation and Language 2022-11-14 v1 Artificial Intelligence Machine Learning

Abstract

We introduce KPI-Check, a novel system that automatically identifies and cross-checks semantically equivalent key performance indicators (KPIs), e.g. "revenue" or "total costs", in real-world German financial reports. It combines a financial named entity and relation extraction module with a BERT-based filtering and text pair classification component to extract KPIs from unstructured sentences before linking them to synonymous occurrences in the balance sheet and profit & loss statement. The tool achieves a high matching performance of 73.0073.00% micro F1_1 on a hold out test set and is currently being deployed for a globally operating major auditing firm to assist the auditing procedure of financial statements.

Keywords

Cite

@article{arxiv.2211.06112,
  title  = {Towards automating Numerical Consistency Checks in Financial Reports},
  author = {Lars Hillebrand and Tobias Deußer and Tim Dilmaghani and Bernd Kliem and Rüdiger Loitz and Christian Bauckhage and Rafet Sifa},
  journal= {arXiv preprint arXiv:2211.06112},
  year   = {2022}
}

Comments

Accepted at BigData 2022, 10 pages, 3 figure, 5 tables

R2 v1 2026-06-28T05:39:49.488Z