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Artificial Intelligence for Risk Mitigation in the Financial Industry
book

Artificial Intelligence for Risk Mitigation in the Financial Industry

by Ambrish Kumar Mishra, Shweta Anand, Narayan C. Debnath, Purvi Pokhariyal, Archana Patel
July 2024
Intermediate to advanced
384 pages
10h 37m
English
Wiley-Scrivener
Content preview from Artificial Intelligence for Risk Mitigation in the Financial Industry

Index

  • AePS, 140
  • AI and financial risk mitigation procedures,
    • continuously improving the risk mitigation process, 70
    • developing risk mitigation policies, 68
    • identification and assessment of risks, 67
    • implementation of risk control policies, 69
    • monitor and evaluate risk mitigation procedures, 69
    • risk prioritization, 67
    • testing and validation, 70
  • AIC criteria, 245
  • AICPA (American Institute of Certified Public Accountants), 230
  • Algorithmic trading, 111
  • Altman’s Z-score models, 209, 212, 214, 215, 218–219
  • Amalgamating, 289
  • Angel Broking, 143
  • Anti-money laundering (AML), 136
  • Artificial intelligence (AI), 82, 85, 134–153, 212, 214, 261, 262, 264, 269
  • Artificial intelligence (AI) in finance, 116
  • Artificial intelligence, financial sector, and risk mitigation,
  • AI and financial risk detection processes, 58, 59
  • AI and financial risk recognition techniques,
    • chatbots and customer service, 62
    • cybersecurity and data privacy, 62
    • fraud detection and anticipation, 60
    • loan underwriting and processing, 63
    • portfolio optimization and asset allocation, 61
    • regulatory compliance, 61
    • risk assessment and prediction, 59
    • risk modeling and stress testing, 60
  • Artificial manipulation, 160–161
  • Artificial neural networks (ANNs),
  • Asset impairment, 161, 168, 179
  • Asset management, 144
  • Asset reconstruction companies (ARCs), financial distress in,
    • brief review of literature, 212–213
    • data analysis and ...
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Publisher Resources

ISBN: 9781394174713Purchase Link