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Artificial Intelligence for Risk Mitigation in the Financial Industry

      Author: creativelivenew1   |   30 November 2024   |   comments: 0

Artificial Intelligence for Risk Mitigation in the Financial Industry
Free Download Artificial Intelligence for Risk Mitigation in the Financial Industry by Ambrish Kumar Mishra, Shweta Anand, Narayan C. Debnath
English | June 11, 2024 | ISBN: 1394174713 | 378 pages | MOBI | 14 Mb
Artificial Intelligence for Risk Mitigation in the Financial Industry


This book extensively explores the implementation of AI in the risk mitigation process and provides information for auditing, banking, and financial sectors on how to reduce risk and enhance effective reliability.
The applications of the financial industry incorporate vast volumes of structured and unstructured data to gain insight into the financial and non-financial performance of companies. As a result of exponentially increasing data, auditors and management professionals need to enhance processing capabilities while maintaining the effectiveness and reliability of the risk mitigation process. The risk mitigation and audit procedures are processes involving the progression of activities to "transform inputs into output." As AI systems continue to grow mainstream, it is difficult to imagine an aspect of risk mitigation in the financial industry that will not require AI-related assurance or AI-assisted advisory services. AI can be used as a strong tool in many ways, like the prevention of fraud, money laundering, and cybercrime, detection of risks and probability of NPAs at early stages, sound lending, etc.
Audience
This is an introductory book that provides insights into the advantages of risk mitigation by the adoption of AI in the financial industry. The subject is not only restricted to individuals like researchers, auditors, and management professionals, but also includes decision-making authorities like the government. This book is a valuable guide to the utilization of AI for risk mitigation and will serve as an important standalone reference for years to come.


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