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The Evolution of Model Risk Management:for Managers and World Leaders

The Evolution of Model Risk Management:for Managers and World Leadersvon Morteza Kohansal Sie sparen 19% des UVP sparen 19%
Über The Evolution of Model Risk Management:for Managers and World Leaders

An increasing reliance on models, regulatory challenges, and talentscarcity is driving banks toward a model risk management organizationthat is both more effective and value-centric.The number of models is rising dramatically¿10 to 25 percent annually at largeinstitutions¿as banks utilize models for an ever-widening scope of decision making.More complex models are being created with advanced-analytics techniques, such asmachine learning, to achieve higher performance standards. A typical large bank can nowexpect the number of models included within its model risk management (MRM) frameworkto continue to increase substantially.Among the model types that are proliferating are those designed to meet regulatoryrequirements, such as capital provisioning and stress testing. But importantly, many of thenew models are designed to achieve business needs, including pricing, strategic planning,and asset-liquidity management. Big data and advanced analytics are opening new areas formore sophisticated models¿such as customer relationship management or anti-moneylaundering and fraud detection.

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  • Sprache:
  • Englisch
  • ISBN:
  • 9786200467522
  • Einband:
  • Taschenbuch
  • Seitenzahl:
  • 308
  • Veröffentlicht:
  • 21. November 2019
  • Abmessungen:
  • 150x19x220 mm.
  • Gewicht:
  • 477 g.
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Beschreibung von The Evolution of Model Risk Management:for Managers and World Leaders

An increasing reliance on models, regulatory challenges, and talentscarcity is driving banks toward a model risk management organizationthat is both more effective and value-centric.The number of models is rising dramatically¿10 to 25 percent annually at largeinstitutions¿as banks utilize models for an ever-widening scope of decision making.More complex models are being created with advanced-analytics techniques, such asmachine learning, to achieve higher performance standards. A typical large bank can nowexpect the number of models included within its model risk management (MRM) frameworkto continue to increase substantially.Among the model types that are proliferating are those designed to meet regulatoryrequirements, such as capital provisioning and stress testing. But importantly, many of thenew models are designed to achieve business needs, including pricing, strategic planning,and asset-liquidity management. Big data and advanced analytics are opening new areas formore sophisticated models¿such as customer relationship management or anti-moneylaundering and fraud detection.

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