@Article{crph1335,
AUTHOR = {Burugulla, Jai Kiran Reddy},
TITLE = {Enhancing Regulatory Compliance in Finance through Big Data Analytics and AI Automation},
JOURNAL = {Current Research in Public Health},
VOLUME = {1},
YEAR = {2021},
NUMBER = {1},
PAGES = {1-20},
URL = {https://www.scipublications.com/journal/index.php/UJFE/article/view/1335},
ISSN = {2831-5162},
DOI = {10.31586/ujfe.2020.1335},
ABSTRACT = {This paper shows how Big Data Analytics (BDA) and Artificial Intelligence (AI) automation facilitate regulatory compliance in Finance. Regulatory compliance is essential in helping institutions to mitigate reputational, litigation, and financial risk. Existing literature reveals several preconditions for compliance. However, much of the literature has adopted an internal view of compliance without considering external regulatory frameworks. This research draws on the cognitive model of regulation that looks at regulatory compliance as a social construct. It uses a triangulation research method comprising literature review, interview of trade compliance experts, and questionnaire survey of compliance practitioners to understand how regulation affects compliance and what role ICTs play in implementing compliance. The findings of this study present a regulatory compliance framework comprising four cognitive stages and a conceptual regulatory compliance system that presents how BDA and AI automation are applied to mitigate regulatory complexity and enhance regulatory compliance. The conceptual regulatory compliance system shows how BDA and AI enable institutions to dynamically assess regulatory risk, automatically monitor compliance, and intelligently predict risk violations mitigating regulatory complexity and preventing producing unnecessary documents. It provides theoretical contributions to understanding regulatory evolution and compliance and practical implications for understanding how regulation evolves to be more complicated and elements of a regulatory compliance system mitigate proliferating regulations. Additionally, it provides avenues for future research into the relationship between competing regulatory mandates and how institutions cope with that. Regulations are important for ensuring compliance and governance in finance and to curb systemic risk. Complying with regulations is difficult due to their growing volume, complexity, and fragmentation. Institutions use large-scale Information and Communication Technologies (ICTs), such as Big Data Analytics (BDA) and Artificial Intelligence (AI) automation, to monitor compliance and mitigate regulatory complexity. However, less is known about how firms comply with regulation. Most literature does not thoroughly investigate regulatory elements nor explicitly relate them to compliance.},
}

%0 Journal Article
%A Burugulla, Jai Kiran Reddy
%D 2021
%J Current Research in Public Health

%@ 2831-5162
%V 1
%N 1
%P 1-20

%T Enhancing Regulatory Compliance in Finance through Big Data Analytics and AI Automation
%M doi:10.31586/ujfe.2020.1335
%U https://www.scipublications.com/journal/index.php/UJFE/article/view/1335

TY  - JOUR
AU  - Burugulla, Jai Kiran Reddy
TI  - Enhancing Regulatory Compliance in Finance through Big Data Analytics and AI Automation
T2  - Current Research in Public Health
PY  - 2021
VL  - 1
IS  - 1
SN  - 2831-5162
SP  - 1
EP  - 20
UR  - https://www.scipublications.com/journal/index.php/UJFE/article/view/1335
AB  - This paper shows how Big Data Analytics (BDA) and Artificial Intelligence (AI) automation facilitate regulatory compliance in Finance. Regulatory compliance is essential in helping institutions to mitigate reputational, litigation, and financial risk. Existing literature reveals several preconditions for compliance. However, much of the literature has adopted an internal view of compliance without considering external regulatory frameworks. This research draws on the cognitive model of regulation that looks at regulatory compliance as a social construct. It uses a triangulation research method comprising literature review, interview of trade compliance experts, and questionnaire survey of compliance practitioners to understand how regulation affects compliance and what role ICTs play in implementing compliance. The findings of this study present a regulatory compliance framework comprising four cognitive stages and a conceptual regulatory compliance system that presents how BDA and AI automation are applied to mitigate regulatory complexity and enhance regulatory compliance. The conceptual regulatory compliance system shows how BDA and AI enable institutions to dynamically assess regulatory risk, automatically monitor compliance, and intelligently predict risk violations mitigating regulatory complexity and preventing producing unnecessary documents. It provides theoretical contributions to understanding regulatory evolution and compliance and practical implications for understanding how regulation evolves to be more complicated and elements of a regulatory compliance system mitigate proliferating regulations. Additionally, it provides avenues for future research into the relationship between competing regulatory mandates and how institutions cope with that. Regulations are important for ensuring compliance and governance in finance and to curb systemic risk. Complying with regulations is difficult due to their growing volume, complexity, and fragmentation. Institutions use large-scale Information and Communication Technologies (ICTs), such as Big Data Analytics (BDA) and Artificial Intelligence (AI) automation, to monitor compliance and mitigate regulatory complexity. However, less is known about how firms comply with regulation. Most literature does not thoroughly investigate regulatory elements nor explicitly relate them to compliance.
DO  - Enhancing Regulatory Compliance in Finance through Big Data Analytics and AI Automation
TI  - 10.31586/ujfe.2020.1335
ER  -