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Authors: Gokce Aydugan Baydar and Seçil Arslan

Affiliation: R&D and Special Projects Department of Yapí Kredi Teknoloji, Istanbul and Turkey

Keyword(s): Pattern Recognition, Document Digitalization, Information Retrieval, Classification, ElasticSearch.

Related Ontology Subjects/Areas/Topics: Applications ; Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Business Analytics ; Data Analytics ; Data Engineering ; Data Management and Quality ; Data Manipulation ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Information Retrieval ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Methodologies and Methods ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Ontologies and the Semantic Web ; Pattern Recognition ; Physiological Computing Systems ; Semi-Structured and Unstructured Data ; Sensor Networks ; Soft Computing ; Software Engineering ; Symbolic Systems ; Text Analytics

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. F OCA 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. (More)

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Paper citation in several formats:
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 - DATA; ISBN 978-989-758-377-3; ISSN 2184-285X, SciTePress, pages 174-181. DOI: 10.5220/0007843201740181

@conference{data19,
author={Gokce {Aydugan Baydar}. and Se\c{C}il 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 - DATA},
year={2019},
pages={174-181},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007843201740181},
isbn={978-989-758-377-3},
issn={2184-285X},
}

TY - CONF

JO - Proceedings of the 8th International Conference on Data Science, Technology and Applications - DATA
TI - FOCA: A System for Classification, Digitalization and Information Retrieval of Trial Balance Documents
SN - 978-989-758-377-3
IS - 2184-285X
AU - Aydugan Baydar, G.
AU - Arslan, S.
PY - 2019
SP - 174
EP - 181
DO - 10.5220/0007843201740181
PB - SciTePress