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Authors: María Del Carmen Zúñiga 1 ; Walter Fuertes 1 ; Hugo Vera Flores 2 and Theofilos Toulkeridis 1 ; 3

Affiliations: 1 Department of Computer Sciences, Universidad de las Fuerzas Armadas ESPE, Av. General Rumiñahui S/N, P.O. Box: 171 5 231 - B, Sangolquí, Ecuador ; 2 BI-Solutions, Av. de los Shyris N36-120, Allure Park Building, 170505, Quito, Ecuador ; 3 Universidad de Especialidades Turísticas UDET, Quito, Ecuador

Keyword(s): Business Intelligence, Data Mining, Financial Services, Financial Incident Management, FinTech, Management Support System.

Abstract: Financial technology corporations (FinTech) specialize in the electronic processing of business transactions and compensation of charges and payments. Such operations have a technological platform that connects multiple financial institutions with companies of the public and private sector. In its constant concern for the provision of efficient services, the company created a unit to guarantee the quality and availability of 24x7x365 of its services by granting their clients confidence regarding online-financial environments through high-security timely security standards management of incidents. However, poor management of incident resolution was detected as there are is a lack of tools to monitor transactional behavior or identify anomalies. Consequently, resolution time has been delayed and, therefore, continuity and regular operation of services. In this sense, economic losses are frequent, yet the real loss results in its confidence and reputation. In response to this problemati c issue, the current study proposes developing a support model of information management for the appropriate and timely resolution of incidents by analyzing historical information, which allows to detect of anomalies in transactional behavior and improve resolution time of events affecting financial services. The used methodology is ad-hoc and consists of various phases, such as identifying the present situation. Afterward, it builds the solution based on Ralph Kimball and Scrum methodologies and validates its result. With the implementation of the work, the business intelligence model improves incident management by providing indicators for the timely detection of anomalies in financial transactions. (More)

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Paper citation in several formats:
Zúñiga, M.; Fuertes, W.; Flores, H. and Toulkeridis, T. (2021). Management Support Systems Model for Incident Resolution in FinTech based on Business Intelligence. In Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-509-8; ISSN 2184-4992, SciTePress, pages 240-247. DOI: 10.5220/0010456402400247

@conference{iceis21,
author={María Del Carmen Zúñiga. and Walter Fuertes. and Hugo Vera Flores. and Theofilos Toulkeridis.},
title={Management Support Systems Model for Incident Resolution in FinTech based on Business Intelligence},
booktitle={Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2021},
pages={240-247},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010456402400247},
isbn={978-989-758-509-8},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - Management Support Systems Model for Incident Resolution in FinTech based on Business Intelligence
SN - 978-989-758-509-8
IS - 2184-4992
AU - Zúñiga, M.
AU - Fuertes, W.
AU - Flores, H.
AU - Toulkeridis, T.
PY - 2021
SP - 240
EP - 247
DO - 10.5220/0010456402400247
PB - SciTePress