Harnessing artificial intelligence by embedding advanced analytics and modelling techniques into risk management processes

Abstract This study examines the integration of analytics and modeling—complementary domains of artificial intelligence—into risk management to transform traditional frameworks into predictive systems. By embedding these AI‐driven methodologies, the research aims to enhance real‐time risk assessment and response capabilities, fostering a proactive rather than reactive approach. A key contribution lies in exploring advanced foresight tools and leveraging AI techniques to construct a cohesive predictive risk management framework. This framework is designed to assist risk practitioners in identifying emerging risks early and formulating mitigation strategies that strengthen emergency preparedness within organizational contexts.

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Publication Details

Journal
Risk Management and Insurance Review
Published
2025-05-05
DOI
https://doi.org/10.1111/rmir.70006
Citations
1
Primary Topic
Anomaly Detection Techniques and Applications
Type
article
Field-Weighted Citation Impact
2.48
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article

Harnessing artificial intelligence by embedding advanced analytics and modelling techniques into risk management processes

Pontsho B. Mokoena
1 citations
Risk Management and Insurance Review
Anomaly Detection Techniques and Applications
2.48
article

Harnessing artificial intelligence by embedding advanced analytics and modelling techniques into risk management processes

Pontsho B. Mokoena
article en
1 citations

Abstract

Abstract This study examines the integration of analytics and modeling—complementary domains of artificial intelligence—into risk management to transform traditional frameworks into predictive systems. By embedding these AI‐driven methodologies, the research aims to enhance real‐time risk assessment and response capabilities, fostering a proactive rather than reactive approach. A key contribution lies in exploring advanced foresight tools and leveraging AI techniques to construct a cohesive predictive risk management framework. This framework is designed to assist risk practitioners in identifying emerging risks early and formulating mitigation strategies that strengthen emergency preparedness within organizational contexts.

Risk Management and Insurance ReviewVol. 28(2)
Paris School of Business (FR)
Openalex Percentile: Top 11%
Anomaly Detection Techniques and Applications
2.48
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