2024: Crisis Management Days Book of Abstracts
Communication and Technology (Crisis Communication, Application of New Technologies and Artificial Intelligence in Crisis Management)

The efficiency of artificial intelligence in reducing financial losses caused by disasters

Samir Ščetić
Visoka škola "CEPS - Centar za poslovne studije" Kiseljak
Lejla Tatarević - Ščetić
Sveučilište "Vitez" Travnik
Hadžib Salkić
Visoka škola "CEPS - Centar za poslovne studije" Kiseljak

Published 2024-05-20


  • AI,
  • disasters,
  • risk management,
  • data analysis,
  • technological revolution


Artificial intelligence (hereinafter AI) is increasingly becoming a key tool in reducing financial losses caused by disasters. Through the application of advanced machine learning algorithms, AI enables rapid recognition and analysis of disaster-related data, facilitating the prediction of their financial consequences. AI systems can analyze vast amounts of data such as meteorological, seismic, and social information to create precise risk models. This empowers decision-makers in the financial sector to respond promptly to threats and minimize losses. Additionally, AI can automatically generate recommendations for optimizing resource allocation for post-disaster recovery and aid. Integration of AI into insurance systems enables personalized insurance policies that better match the specific risks of individuals or organizations. AI also enhances claims processes, expediting damage assessment and claims handling. However, challenges such as data access, privacy, and ethical considerations also need to be carefully addressed to ensure the effective and responsible application of AI in reducing financial losses caused by disasters. Ultimately, the integration of AI into risk management opens the path to a more efficient and resilient financial sector in facing the challenges of disasters.


  1. Bellovin, S. M., & Berson, T. A. (2019). AI for Disaster Response and Recovery. O'Reilly Media.
  2. O'Sullivan, F., & Sanderson, D. (2020). Artificial Intelligence in Finance: Machine Learning and Natural Language Processing. Springer.
  3. Reddy, K. N., & Kumar, M. (2020). Applications of Artificial Intelligence Techniques in Disaster Management. In Handbook of Research on Applications and Implementations of Machine Learning Techniques (pp. 106-124). IGI Global.
  4. Mehmood, A., Abbas, Q., Kim, B. S., & Zhang, L. (2020). A survey of artificial intelligence and machine learning based disaster management. Future Generation Computer Systems
  5. Yang, W., & Hu, X. (2020). Artificial Intelligence in Disaster Management: Recent Progresses and Future Prospects. IEEE Access, 8, 113903-113916.
  6. Colombo, G., Villa, A., & Villa, S. (2021). Artificial Intelligence in Natural Disaster Risk Reduction and Management: A Review. ISPRS International Journal of Geo-Information