Technological Solutions for Fraud Prevention and design of a Transactional Risk Prevention Model for the Payment Button
DOI:
https://doi.org/10.31908/19098367.1154Keywords:
Payment button, cybersecurity, cybercrime prevention, electronic payment, fraud prevention, financial servicesAbstract
Financial services sector faces challenges in the development of activities that require the use of information and communication technologies, because these are activities exposed to risks such as cybercrimes, which can affect trust in the company’s brand and the confidence in the service. In order to face these challenges, ACH Colombia developed a project in order to anticipate and prevent the risks related to computer crimes, using tools that facilitate the analysis of information for decision-making. It also designed and implemented a particular prevention model for the payment button, which is one of the services that the company provides to banks, legal and natural persons and public entities. This article aims to present some results of the project.
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References
Liébana-Cabanillas, F. et al. «Analysing user trust in electronic banking using data mining methods,» Expert Systems with Applications, pp. 5439-5447, 2013.
Ali, R., Barrdear, J., y Clews, R. «Innovations in payment technologies and the emergence of digital currencies,» Park Communications Limited, Londres, 2014.
Peha, J. M., y Khamitov, I. M. «PayCash: a secure efficient internet payment system,» Electronic Commerce Research and Applications, p. 381–388, 2004.
Cano, J. J. «Inseguridad Informática: Un Concepto Dual En Seguridad Informática,» de IV Jornada Nacional de Seguridad Informática - ACIS 2004., Bogotá, 2004.
PWC, «(Don’t) take it to the bank: What customers want in the digital age,» PwC, Nueva York, 2017.
Comité de Supervisión Bancaria de Basilea, «Buenas prácticas para la gestión y supervisión del riesgo operativo,» Banco de Pagos Internacionales, Basilea (Suiza), 2004.
Asociación de Supervisores Bancarios de las Américas, «Temas de Supervisión,» 2010. [En línea]. Available: http://www.ccsbso.org/sites/default/files/g6_es.pdf.
KPMG Advisory Services Ltda., «Encuesta de Fraude en Colombia 2013,» KPMG Advisory Services Ltda., Bogotá, 2013.
Gemalto, «Breach Level Index 2017,» gemalto, Nevada, 2017.
ASOBANCARIA, «Seguridad bancaria en canales no presenciales: una ruta hacia la inclusión financiera,» Semana Económica 2015, nº 1002, pp. 1-11, 2015.
Gomber, P., Koch, J. A., y Siering, M. «Digital Finance and FinTech: current research and future research directions,» Journal of Business Economics, vol. 87, nº 5, p. 537–580, 2017.
Perry, y Fontnouvelle, P. «Measuring Reputational Risk: The Market Reaction,» Federal Reserve Bank of Boston., Boston, 2005.
Langari, et al. «Introducing a model for suspicious behavior detection in electronic banking by using decision tree algorithms,» Journal of Information Processing and Management, pp. 681-700, 2014.
GARTNER, «Documentos Gartner Inc.,» 11 abril 2011. [En línea]. Available: https://www.gartner.com/doc/1646115/layers-fraud-prevention-using-beat.
SAS Institute Inc., «Recursos / White Paper,» 06 junio 2011. [En línea]. Available: http://www.sas.com/resources/whitepaper/wp_5819.pdf.
Valencia, E. «Aplicación de las Redes Neuronales a la Mineria de Datos,» UNAM, México D.F., 2006.
Patidar, R., y Sharma, L. «Credit Card Fraud Detection Using Neural Network,» International Journal of Soft Computing and Engineering, pp. 32-38, 2011.
Capgemini, «Top 10 Trends in Banking – 2017,» Capgemini, Paris, 2017.
Garg, G., Vudayagiri, G., Pillai, S. G., y Sharma, R. «Top 10 trends in payments,» Capgemini, Paris, 2018.
Hernandez, R., Fernandez, C., y Baptista, P. Metodología de la Investigación, México: McGraw-Hill, 2006.