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

Pontsho B. Mokoena

Risk Management and Insurance Review2025https://doi.org/10.1111/rmir.70006article
ABDC C
Weight
0.37

What the paper says

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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https://doi.org/https://doi.org/10.1111/rmir.70006

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@article{pontsho2025,
  title        = {{Harnessing artificial intelligence by embedding advanced analytics and modelling techniques into risk management processes}},
  author       = {Pontsho B. Mokoena},
  journal      = {Risk Management and Insurance Review},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1111/rmir.70006},
}

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

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.