TY  - CHAP
AU  - Pisoni, Galena
AU  - Molnár, Bálint
ED  - Tsiatsos, Thrasyvoulos
ED  - Langmann, Reinhard
ED  - Auer, Michael E.
TI  - Data Management and Enterprise Architectures for Responsible AI Services
T2  - Open Science in Engineering
PB  - Springer Nature Switzerland AG
CY  - Cham
SN  - 9783031424670
T3  - Lecture Notes in Networks and Systems, ISSN 2367-3370 ; 763.
PY  - 2023
SP  - 879
EP  - 884
PG  - 6
DO  - 10.1007/978-3-031-42467-0_83
UR  - https://m2.mtmt.hu/api/publication/34472933
ID  - 34472933
AB  - Big data is becoming a reality. Complex and difficult-to-understand data may be found in a wide range of industries. Big data is a critical component of enterprise services and technology architectures. Data science techniques and methodologies can be applied in many aspects of the working of companies. In this paper, first, as a background, we provide an overview of knowledge management practices and data analysis strategies and techniques in the daily operations of companies working towards development of AI agents. Furthermore, we look at the need in particular companies to develop human centric AI solutions; then, we discuss the basics for cross-disciplinary research, in which we stress the need to rethink development processes of AI services and make them more responsible. Thereby, we define research questions to investigate the problem. As the research proposal discusses, companies and public institutions can create and develop new responsible, ethical, and transparent AI services.
LA  - English
DB  - MTMT
ER  - 

TY  - JOUR
AU  - Kherbouche, Meriem
AU  - Pisoni, Galena
AU  - Molnár, Bálint
TI  - Model to Program and Blockchain Approaches for Business Processes and Workflows in Finance
JF  - APPLIED SYSTEM INNOVATION
J2  - APPL SYST INNOV
VL  - 5
PY  - 2022
IS  - 1
PG  - 17
SN  - 2571-5577
DO  - 10.3390/asi5010010
UR  - https://m2.mtmt.hu/api/publication/32577546
ID  - 32577546
LA  - English
DB  - MTMT
ER  - 

TY  - CHAP
AU  - Verma, Suhasini
AU  - Sharma, Jeevesh
AU  - Kaushik, Keshav
AU  - Vyas, Vidhisha
ED  - Kaushik, Keshav
ED  - Vyas, Vidhisha
ED  - Verma, Suhasini
TI  - Mounting Cases of Cyber-Attacks and Digital Payment
T2  - Cybersecurity Issues, Challenges, and Solutions in the Business World
PB  - IGI Global
SN  - 9781668458297
T3  - Advances in Information Security, Privacy, and Ethics, ISSN 1948-9730
PY  - 2022
SP  - 59
EP  - 80
PG  - 22
DO  - 10.4018/978-1-6684-5827-3.ch005
UR  - https://m2.mtmt.hu/api/publication/33205939
ID  - 33205939
AB  - Digital transformation in financial transactions has changed the method of payment. We have witnessed a many-fold and rapid increase in the digital payment. As more individuals opt for digital payments, the potential of being exposed to cyber-attacks such as online fraud, theft of identity, and spyware or virus attacks is rising. Transaction on digital mode has led to an increase in internet-based crimes known by the term ‘cybercrime'. Cybercrime is an illegal act practiced by hackers on web applications, web browsers, and websites. Secured payment is critical for any company that deals with electronic payments and transactions. One of the most vital issues confronting players in the digital payment ecosystem is cyber security. The growth of such cyber-attacks can be attributed to various reasons, including a lack of knowledge and a poor digital payment infrastructure. To safeguard against threats of cybercrime, there are various cyber security techniques. This chapter deals in understanding the causes, threats, and solutions to cyber-attacks in digital payment methods.
LA  - English
DB  - MTMT
ER  - 

TY  - CHAP
AU  - Farooq, Akeel
AU  - Chawla, Privanka
TI  - Review of Data Science and AI in Finance
T2  - 2021 International Conference on Computing Sciences (ICCS)
PB  - IEEE
SN  - 9781665494458
PY  - 2021
SP  - 216
EP  - 222
PG  - 7
DO  - 10.1109/ICCS54944.2021.00050
UR  - https://m2.mtmt.hu/api/publication/32923185
ID  - 32923185
LA  - English
DB  - MTMT
ER  - 

TY  - JOUR
AU  - Pisoni, Galena
AU  - Molnár, Bálint
AU  - Tarcsi, Ádám
TI  - Data Science for Finance. Best-Suited Methods and Enterprise Architectures
TS  - Best-Suited Methods and Enterprise Architectures
JF  - APPLIED SYSTEM INNOVATION
J2  - APPL SYST INNOV
VL  - 4
PY  - 2021
IS  - 3
PG  - 20
SN  - 2571-5577
DO  - 10.3390/asi4030069
UR  - https://m2.mtmt.hu/api/publication/32239388
ID  - 32239388
LA  - English
DB  - MTMT
ER  -