Managing Financial Climate Risk in Banking Services: A Review of Current Practices and the Challenges Ahead
The document discusses the financial climate risk in the context of the banking industry, emphasizing the need for a comprehensive understanding of climate change across different spatial and temporal scales. It highlights the challenges in estimating physical and transition risks, specifically extreme events and limitations of current climate models. The document also reviews current gaps in assessing physical and transition risks, including the development, improvement of modeling frameworks, highlighting the need for detailed databases of exposed physical assets and climatic hazard modeling. It also emphasizes the importance of integrating financial climate risks into financial risk management practices, particularly in smaller banks and lending organizations.
Code (0)
등록된 구현이 없습니다.
Tasks
ManagementSimilar Papers 제목 키워드 기반
From Persistent Homology to Reinforcement Learning with Applications for Retail Banking
The retail banking services are one of the pillars of the modern economic growth. However, the evolution of the client's habits in modern societies and the recent European regulations promoting more competition mean the …
Managementreinforcement-learningReinforcement LearningReinforcement Learning (RL)Exploring Causes, Effects, and Solutions to Financial Illiteracy and Exclusion among Minority Demographic Groups
Americans across demographic groups tend to have low financial literacy, with low-income people and minorities at highest risk. This opens the door to the exploitation of unbanked low-income families through high-interes…
Risk-Adjusted Harm Scoring for Automated Red Teaming for LLMs in Financial Services
The rapid adoption of large language models (LLMs) in financial services introduces new operational, regulatory, and security risks. Yet most red-teaming benchmarks remain domain-agnostic and fail to capture failure mode…
Red TeamingRedefining Finance: The Influence of Artificial Intelligence (AI) and Machine Learning (ML)
With rapid transformation of technologies, the fusion of Artificial Intelligence (AI) and Machine Learning (ML) in finance is disrupting the entire ecosystem and operations which were followed for decades. The current la…
Fraud DetectionManagementDynamic Evolutionary Game Analysis of How Fintech in Banking Mitigates Risks in Agricultural Supply Chain Finance
This paper explores the impact of banking fintech on reducing financial risks in the agricultural supply chain, focusing on the secondary allocation of commercial credit. The study constructs a three-player evolutionary …