Climate Risk Insurance: Dealing with Opportunities and Challenges in a World Changing
Keywords:
Climate risk, insurance, climate change, financial resilience, risk managementAbstract
A key topic of current discussions on the control of growing climate change risks is climate risk insurance. Natural disasters include floods, hurricanes, and wildfires—which are becoming more frequent and severe—cause increased financial risks for individuals and businesses. These events disrupt people's livelihoods and way of life, hence maybe causing significant financial losses especially in vulnerable regions. The requirement of thorough insurance solutions to reduce these risks has become increasingly important as climate-related disasters worsen. Still, climate risk insurance offers some challenges. Conventional insurance models often cannot fit the unpredictability and intensity of natural disasters. The uncertainty about climate change calls for help in properly assessing risks and pricing insurance in line with this. Climate risk insurance might become a necessary element of the worldwide strategy to improve resistance to climate change in these evolving surroundings. Developing more inclusive and sustainable insurance models able to withstand future challenges depends on the cooperation among the private sector, governments, and international organizations; hence, individuals and companies can better negotiate the uncertainty presented by a changing climate.
References
1. Linnerooth-Bayer, J., Warner, K., Bals, C., Höppe, P., Burton, I., Loster, T., & Haas, A. (2009). Insurance, developing countries and climate change. The Geneva Papers on Risk and Insurance-Issues and Practice, 34, 381-400.
2. Knight, J. (2008). Higher education in turmoil: The changing world of internationalization (Vol. 13). Brill.
3. Walker, B., & Salt, D. (2012). Resilience thinking: sustaining ecosystems and people in a changing world. Island press.
4. Darling-Hammond, L., & Bransford, J. (Eds.). (2007). Preparing teachers for a changing world: What teachers should learn and be able to do. John Wiley & Sons.
5. Beck, U. (2009). World at risk. Polity.
6. Armitage, D. R., Plummer, R., Berkes, F., Arthur, R. I., Charles, A. T., Davidson-Hunt, I. J., ... & Wollenberg, E. K. (2009). Adaptive co‐management for social–ecological complexity. Frontiers in Ecology and the Environment, 7(2), 95-102.
7. Helfat, C. E., & Winter, S. G. (2011). Untangling dynamic and operational capabilities: Strategy for the (N) ever‐changing world. Strategic management journal, 32(11), 1243-1250.
8. Ostrom, E. (2017). Polycentric systems for coping with collective action and global environmental change. In Global justice (pp. 423-430). Routledge.
9. Vermeulen, S. J., Campbell, B. M., & Ingram, J. S. (2012). Climate change and food systems. Annual review of environment and resources, 37(1), 195-222.
10. Gupta, J. (2007). The multi-level governance challenge of climate change.
11. Smith, P. B., Bond, M. H. H., Vignoles, V. L., & Fischer, R. (2013). Understanding social psychology across cultures: Engaging with others in a changing world.
12. Armaroli, N., & Balzani, V. (2007). The future of energy supply: challenges and opportunities. Angewandte Chemie International Edition, 46(1‐2), 52-66.
13. Gifford, R. (2011). The dragons of inaction: psychological barriers that limit climate change mitigation and adaptation. American psychologist, 66(4), 290.
14. Sekaran, U., Lai, L., Ussiri, D. A., Kumar, S., & Clay, S. (2021). Role of integrated crop-livestock systems in improving agriculture production and addressing food security–A review. Journal of Agriculture and Food Research, 5, 100190.
15. Smit, B., & Wandel, J. (2006). Adaptation, adaptive capacity and vulnerability. Global environmental change, 16(3), 282-292.
16. Katari, A., Muthsyala, A., & Allam, H. HYBRID CLOUD ARCHITECTURES FOR FINANCIAL DATA LAKES: DESIGN PATTERNS AND USE CASES.
17. Katari, A. Conflict Resolution Strategies in Financial Data Replication Systems.
18. Katari, A., & Rallabhandi, R. S. DELTA LAKE IN FINTECH: ENHANCING DATA LAKE RELIABILITY WITH ACID TRANSACTIONS.
19. Katari, A. (2019). Real-Time Data Replication in Fintech: Technologies and Best Practices. Innovative Computer Sciences Journal, 5(1).
20. Katari, A. (2019). ETL for Real-Time Financial Analytics: Architectures and Challenges. Innovative Computer Sciences Journal, 5(1).
21. Babulal Shaik. Automating Compliance in Amazon EKS Clusters With Custom Policies . Journal of Artificial Intelligence Research and Applications, vol. 1, no. 1, Jan. 2021, pp. 587-10
22. Babulal Shaik. Developing Predictive Autoscaling Algorithms for Variable Traffic Patterns . Journal of Bioinformatics and Artificial Intelligence, vol. 1, no. 2, July 2021, pp. 71-90
23. Babulal Shaik, et al. Automating Zero-Downtime Deployments in Kubernetes on Amazon EKS . Journal of AI-Assisted Scientific Discovery, vol. 1, no. 2, Oct. 2021, pp. 355-77
24. Nookala, G., Gade, K. R., Dulam, N., & Thumburu, S. K. R. (2021). Unified Data Architectures: Blending Data Lake, Data Warehouse, and Data Mart Architectures. MZ Computing Journal, 2(2).
25. Nookala, G. (2021). Automated Data Warehouse Optimization Using Machine Learning Algorithms. Journal of Computational Innovation, 1(1).
26. Nookala, G., Gade, K. R., Dulam, N., & Thumburu, S. K. R. (2020). Automating ETL Processes in Modern Cloud Data Warehouses Using AI. MZ Computing Journal, 1(2).
27. , G., Gade, K. R., Dulam, N., & Thumburu, S. K. R. (2020). Data Virtualization as an Alternative to Traditional Data Warehousing: Use Cases and Challenges. Innovative Computer Sciences Journal, 6(1).
28. Nookala, G., Gade, K. R., Dulam, N., & Thumburu, S. K. R. (2019). End-to-End Encryption in Enterprise Data Systems: Trends and Implementation Challenges. Innovative Computer Sciences Journal, 5(1).
29. Boda, V. V. R., & Immaneni, J. (2021). Healthcare in the Fast Lane: How Kubernetes and Microservices Are Making It Happen. Innovative Computer Sciences Journal, 7(1).
30. Immaneni, J. (2021). Using Swarm Intelligence and Graph Databases for Real-Time Fraud Detection. Journal of Computational Innovation, 1(1).
31. Immaneni, J. (2020). Cloud Migration for Fintech: How Kubernetes Enables Multi-Cloud Success. Innovative Computer Sciences Journal, 6(1).
32. Boda, V. V. R., & Immaneni, J. (2019). Streamlining FinTech Operations: The Power of SysOps and Smart Automation. Innovative Computer Sciences Journal, 5(1).
33. Gade, K. R. (2021). Cost Optimization Strategies for Cloud Migrations. MZ Computing Journal, 2(2).
34. Gade, K. R. (2021). Cloud Migration: Challenges and Best Practices for Migrating Legacy Systems to the Cloud. Innovative Engineering Sciences Journal, 1(1).
35. Gade, K. R. (2021). Data Analytics: Data Democratization and Self-Service Analytics Platforms Empowering Everyone with Data. MZ Computing Journal, 2(1).
36. Gade, K. R. (2021). Data-Driven Decision Making in a Complex World. Journal of Computational Innovation, 1(1).
37. Gade, K. R. (2021). Migrations: Cloud Migration Strategies, Data Migration Challenges, and Legacy System Modernization. Journal of Computing and Information Technology, 1(1).
38. Muneer Ahmed Salamkar. Batch Vs. Stream Processing: In-Depth Comparison of Technologies, With Insights on Selecting the Right Approach for Specific Use Cases. Distributed Learning and Broad Applications in Scientific Research, vol. 6, Feb. 2020
39. Muneer Ahmed Salamkar, and Karthik Allam. Data Integration Techniques: Exploring Tools and Methodologies for Harmonizing Data across Diverse Systems and Sources. Distributed Learning and Broad Applications in Scientific Research, vol. 6, June 2020
40. Muneer Ahmed Salamkar, et al. The Big Data Ecosystem: An Overview of Critical Technologies Like Hadoop, Spark, and Their Roles in Data Processing Landscapes. Journal of AI-Assisted Scientific Discovery, vol. 1, no. 2, Sept. 2021, pp. 355-77
41. Muneer Ahmed Salamkar. Scalable Data Architectures: Key Principles for Building Systems That Efficiently Manage Growing Data Volumes and Complexity. Journal of AI-Assisted Scientific Discovery, vol. 1, no. 1, Jan. 2021, pp. 251-70
42. Muneer Ahmed Salamkar, and Jayaram Immaneni. Automated Data Pipeline Creation: Leveraging ML Algorithms to Design and Optimize Data Pipelines. Journal of AI-Assisted Scientific Discovery, vol. 1, no. 1, June 2021, pp. 230-5
43. Naresh Dulam, et al. “Snowflake’s Public Offering: What It Means for the Data Industry ”. Journal of AI-Assisted Scientific Discovery, vol. 1, no. 2, Dec. 2021, pp. 260-81
44. Naresh Dulam, et al. “Data Lakehouse Architecture: Merging Data Lakes and Data Warehouses”. Journal of AI-Assisted Scientific Discovery, vol. 1, no. 2, Oct. 2021, pp. 282-03
45. Naresh Dulam, et al. “The AI Cloud Race: How AWS, Google, and Azure Are Competing for AI Dominance ”. Journal of AI-Assisted Scientific Discovery, vol. 1, no. 2, Dec. 2021, pp. 304-28
46. Naresh Dulam, et al. “Kubernetes Operators for AI ML: Simplifying Machine Learning Workflows”. African Journal of Artificial Intelligence and Sustainable Development, vol. 1, no. 1, June 2021, pp. 265-8
47. Naresh Dulam, et al. “Data Mesh in Action: Case Studies from Leading Enterprises”. Journal of Artificial Intelligence Research and Applications, vol. 1, no. 2, Dec. 2021, pp. 488-09
48. Thumburu, S. K. R. (2021). A Framework for EDI Data Governance in Supply Chain Organizations. Innovative Computer Sciences Journal, 7(1).
49. Thumburu, S. K. R. (2021). EDI Migration and Legacy System Modernization: A Roadmap. Innovative Engineering Sciences Journal, 1(1).
50. Thumburu, S. K. R. (2021). Data Analysis Best Practices for EDI Migration Success. MZ Computing Journal, 2(1).
51. Thumburu, S. K. R. (2021). The Future of EDI Standards in an API-Driven World. MZ Computing Journal, 2(2).
52. Thumburu, S. K. R. (2021). Optimizing Data Transformation in EDI Workflows. Innovative Computer Sciences Journal, 7(1).
53. Sarbaree Mishra. “The Age of Explainable AI: Improving Trust and Transparency in AI Models”. Journal of AI-Assisted Scientific Discovery, vol. 1, no. 2, Oct. 2021, pp. 212-35
54. Sarbaree Mishra, et al. “A New Pattern for Managing Massive Datasets in the Enterprise through Data Fabric and Data Mesh”. Journal of AI-Assisted Scientific Discovery, vol. 1, no. 2, Dec. 2021, pp. 236-59
55. Sarbaree Mishra. “Leveraging Cloud Object Storage Mechanisms for Analyzing Massive Datasets”. African Journal of Artificial Intelligence and Sustainable Development, vol. 1, no. 1, Jan. 2021, pp. 286-0
56. Sarbaree Mishra, et al. “A Domain Driven Data Architecture For Improving Data Quality In Distributed Datasets”. Journal of Artificial Intelligence Research and Applications, vol. 1, no. 2, Aug. 2021, pp. 510-31
57. Sarbaree Mishra. “Improving the Data Warehousing Toolkit through Low-Code No-Code”. Journal of Bioinformatics and Artificial Intelligence, vol. 1, no. 2, Oct. 2021, pp. 115-37
58. Komandla, V. Strategic Feature Prioritization: Maximizing Value through User-Centric Roadmaps.
59. Komandla, V. Enhancing Security and Fraud Prevention in Fintech: Comprehensive Strategies for Secure Online Account Opening.
60. Komandla, Vineela. "Effective Onboarding and Engagement of New Customers: Personalized Strategies for Success." Available at SSRN 4983100 (2019).
61. Komandla, V. Transforming Financial Interactions: Best Practices for Mobile Banking App Design and Functionality to Boost User Engagement and Satisfaction.
62. Komandla, Vineela. "Transforming Financial Interactions: Best Practices for Mobile Banking App Design and Functionality to Boost User Engagement and Satisfaction." Available at SSRN 4983012 (2018).