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Artificial Intelligence: The Strategy of Financial Risk Management

https://doi.org/10.26794/2587-5671-2024-28-3-174-182

Abstract

This research examines the use of artificial intelligence (AI) as a financial risk management tool. The concept is motivated by the revolutionary effects that financial technology has on business operations. Traditional methods of financial risk management are no longer effective and require revision. The purpose of the study is to assess the role of artificial intelligence in the management of financial risks and offer recommendations for its further use in the financial sector of the economy. Methodological analysis of relevant scientific literature showed that AI, in particular machine learning, can help in managing financial risks. It has been concluded that AI improves the management of market and credit risks in model verification, risk modelling, stress testing and data preparation. AI helps to monitor the quality of information received, detect fraud and search for the right information on the Internet. In the future, financial technology will continue to influence the financial sector as operating companies modify their operations. Thus, financial risk management tools will include AI. The study examines the possibilities of AI use in financial (market and credit), risk management and operational sectors (business continuity and emergency recovery). The paper presents the most promising AI technologies and techniques such as RPA, Data Management, Blockchain, MRL, MRC, CRU, Deep Learning, OML, Modelling and Stress Testing, Machine Learning and Algorithms, Neural Networks, Decision Trees, CPM, CRA, Black Box, etc. to improve “Financial Risk Management (FRM)”.

About the Authors

A. Kumar
Indian Institute of Technology (Indian School of Mines); Bank of India, Government of India (U/T)
India

Abhijeet Kumar — MBA, Research Scholar, Department of Humanities and Social Sciences; Specialist Officer (S.O)

Dhanbad; Mumbai, Maharashtra, (Goa Zone)


Competing Interests:

The authors have no conflicts of interest to declare.



A Kumar
Indian Institute of Management; Indian Institute of Management; P K Roy Memorial College; Guru Nanak College; Binod Bihari Mahto Koyalanchal University; University of Religions and Denominations
India

Avinash Kumar — Fellow; SRF, Faculty of Humanities and Social Sciences; Asst. Prof. (G.F) / Asst. Prof. (G.F); Research Fellow

Ahmedabad, Bangalor; Dhanbad; Qom, Iran


Competing Interests:

The authors have no conflicts of interest to declare.



S. Kumari
Indian Institute of Technology
Russian Federation

Swati Kumari— SRF, Department of Electrical Engineering and Computer Science (EECS)

Bhilai


Competing Interests:

The authors have no conflicts of interest to declare.



S. Kumar
Bank of India, Government of India (U/T)
India

Sneha Kumari — MBA in Finance, Assistant Manager

Mumbai, Maharashtra, (Dhanbad Zone)


Competing Interests:

The authors have no conflicts of interest to declare.



N. Kumari
Indian Institute of Technology (Indian School of Mines)
India

Neha Kumari — Research Scholar, Department of Humanities and Social Sciences

Dhanbad


Competing Interests:

The authors have no conflicts of interest to declare.



A. K. Behura
Indian Institute of Technology (Indian School of Mines)
India

Ajit K. Behura — PhD, Prof., Department of Humanities and Social Sciences

Dhanbad


Competing Interests:

The authors have no conflicts of interest to declare.



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Review

For citations:


Kumar A., Kumar A., Kumari S., Kumar S., Kumari N., Behura A.K. Artificial Intelligence: The Strategy of Financial Risk Management. Finance: Theory and Practice. 2024;28(3):174-182. https://doi.org/10.26794/2587-5671-2024-28-3-174-182

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