Towards automating Numerical Consistency Checks in Financial Reports

Autor:	Hillebrand, Lars, Deußer, Tobias, Dilmaghani, Tim, Kliem, Bernd, Loitz, Rüdiger, Bauckhage, Christian, Sifa, Rafet
Rok vydání:	2022
Předmět:	Computer Science - Computation and Language Computer Science - Artificial Intelligence Computer Science - Machine Learning
Druh dokumentu:	Working Paper
Popis:	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 $73.00$% micro F$_1$ 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. Comment: Accepted at BigData 2022, 10 pages, 3 figure, 5 tables
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2211.06112 Zobrazit plný text záznamu View this record from Arxiv