Scholarly record
OPPORTUNITIES TO USE VIRTUAL TOOLS IN START-UP FINTECH COMPANIES
Abstract
The digitalization of financial services at its current stage is characterized by high dynamics in terms of information technology used, with the expansion and complication of the relationship with consumers, which requires constant improvement of the forms and methods of management of organizations offering financial services. The emergence of phenomena such as cryptocurrencies, blockchain transactions, fintech companies, and others modify the financial services market, which is traditionally dominated by banks and other large-scale financial organizations. To maintain their position in this highly dynamic environment, organizations offering financial services need to constantly adapt to modern information technologies and seek new approaches to connect with the end users through the digitalization of their activities. The list of tools offered by us does not claim to be exhaustive and rather indicates opportunities, coverage of tasks, possible diversity. The individual virtual tools are suitable for certain phases of the process of working in start-up fintech companies. It is a matter of the entrepreneur's discretion which of these and how convenient they are for a given product, idea, and business model. In terms of price, most tools have zero or low price - free versions, free for micro teams (up to 5-10 users) or the price is according to the number of users or volume of consumption. This is a convenience for a start-up company, as it implies low operating costs. A significant problem could be the large number and variety of tools to use. Many products have features that cover more than one activity and/or can be integrated with third-party tools for other activities, which makes it easier to build an integrated start-up environment.
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References14
Balabanova I., Georgiev G., Penchev P., Kostadinova S., Dimova, R. Classification of Teletraffic Service Devices by K-NN, ANFIS and ANN Classificators. IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom), 2016, pp.1-5.
Bulut F., Erol M.H. A Real-Time Dynamic Route Control Approach on Google Maps using Integer Programming Methods. International Journal of Next-Generation Computing.2018, 9(3), pp.189-202.
Dimitrov G.P., Panayotova G., Garvanov I., Os B., Petrov P., Angelov A. Performance analysis of the method for social search of information in university information systems. Third International Conference on Artificial Intelligence and Pattern Recognition (AIPR), 2016, pp.1-5, DOI: 10.1109/ICAIPR.2016.7585228.
Kuyumdzhiev I., Nacheva R. Choosing Storage Devices with Consideration of Backup and Restore Performance in MS SQL SERVER. Information and Communication Technologies in Business and Education: Proceedings of the International Conference Dedicated to the 50th Anniversary of the Department of Informatics, Varna: Science and Economic Publ. House. 2019, pp.166-176.
Pashev G., Rusenova L., Totkov G., Gaftandzhieva S. Business Process Modelling & Execution Application in Work Education Domain. TEM Journal, 2019, 8(3), pp.992-997.
Petrov P, Valov N. Digitalization of banking services and methodology for building and functioning of Fintech companies. Izvestia Journal of the Union of Scientists-Varna. Economic Sciences Series. 2019, 8(1), pp.110-117.
Petrova S., Sergeev A., Getova I., Kostadinova I. S. Online Public Access Catalogs in Bulgarian University Libraries an Empirical Study of Seven-Year Evolution. In 12th Annual International Conference of Education, Research and Innovation (ICERI). 2019, pp.230-236. DOI: 10.21125/iceri.2019.0091
Radev M. Using the TOPSIS Method to Evaluate Projects for Virtualization. Izvestia Journal of the Union of Scientists - Varna. Economic Sciences Series. 2017, issue 2, pp.234-241.
Rakhmatova A, Sergeev A, Buevich A, Shichkin A, Sergeeva M. Partition Procedure of the Initial Data for the Models Based on Artificial Neural Networks. In 2019 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT) IEEE. 2019, pp.241-243.
Stoev S. Integration of Risk Management Processes into the Business of IT Companies. Izvestia Journal of the Union of Scientists-Varna. Economic Sciences Series. 2017, issue 2, pp.225-233.
Stoev S. Product Risk Management in Information Systems Implementation. Izvestia Journal of the Union of Scientists-Varna. Economic Sciences Series. 2016, issue 2, pp.109-116.
Sulov V. Iteration vs Recursion in Introduction to Programming Classes: An Empirical Study. Cybernetics and Information Technologies. 2016, 16(4), pp.63-72.
Sydikhov A, Buevich A, Sergeev A, Shichkin A, Subbotina I, Baglaeva E. Method of selecting spatially distributed information for constructing training set of artificial neural networks. In AIP Conference Proceedings. 2019, Vol.2116 No.1, p.200020.
Turygina V.F., Vasilev J., Safrygin A.S., Nizov A.N., Panteleeva N.D. Comparison of statistical models for assessing the probability of bankruptcy of enterprises. International Multidisciplinary Scientific GeoConference: SGEM, 2019, 19(2.1), pp.175-180.
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