FOCA: A System for Classification, Digitalization and Information Retrieval of Trial Balance Documents

Gokce Aydugan Baydar, Seçil Arslan

2019

Abstract

Credit risk evaluation and sales target optimization are core businesses for financial institutions. Financial documents like t-balances, balance sheets, income statements are the most important inputs for both of these core businesses. T-balance is a semi-structured financial document which is constructed periodically by accountants and contains detailed accounting transactions. FOCA is an end to end system which first classifies financial documents in order to recognize t-balances, then digitalizes them into a tree-structured form and finally extracts valuable information such as bank names, human-company distinction, deposit type and liability term from free format text fields of t-balances. The information extracted is also enriched by matching human and company names who are in a relationship with existing customers of the bank from the customer database. Pattern recognition, natural language processing, and information retrieval techniques are utilized for these capabilities. FOCA supports both decision/operational processes of corporate/commercial/SME sales and financial analysis departments in order to empower new customer engagement, cross-sell and up-sell to the existing customers and ease financial analysis operations by digitalizing t-balances.

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Paper Citation


in Harvard Style

Aydugan Baydar G. and Arslan S. (2019). FOCA: A System for Classification, Digitalization and Information Retrieval of Trial Balance Documents.In Proceedings of the 8th International Conference on Data Science, Technology and Applications - Volume 1: DATA, ISBN 978-989-758-377-3, pages 174-181. DOI: 10.5220/0007843201740181


in Bibtex Style

@conference{data19,
author={Gokce Aydugan Baydar and Seçil Arslan},
title={FOCA: A System for Classification, Digitalization and Information Retrieval of Trial Balance Documents},
booktitle={Proceedings of the 8th International Conference on Data Science, Technology and Applications - Volume 1: DATA,},
year={2019},
pages={174-181},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007843201740181},
isbn={978-989-758-377-3},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 8th International Conference on Data Science, Technology and Applications - Volume 1: DATA,
TI - FOCA: A System for Classification, Digitalization and Information Retrieval of Trial Balance Documents
SN - 978-989-758-377-3
AU - Aydugan Baydar G.
AU - Arslan S.
PY - 2019
SP - 174
EP - 181
DO - 10.5220/0007843201740181