by Ajay Katara
Climate risk is assuming a critical role for banks and financial institutions due to the mounting environmental challenges. As the frequency and severity of climate-related events increase, banks face heightened risks associated with their investments, loans, and overall financial stability. It’s no surprise that climate risk management features in the topmost agenda for CRO’s (Chief Risk Officers) globally as effectively managing these risks is imperative to safeguard assets, ensure regulatory compliance, and promote long-term sustainability in the context of a changing climate.
Generative AI or Gen AI, a subset of artificial intelligence, holds transformative potential in addressing climate risks. The tech stack comes with advanced algorithms and models which can be leveraged in various use cases in the climate risk management lifecycle, aiding in risk assessment and mitigation planning.
Some key use cases or problem statements that can benefit from Gen AI interventions in climate risk management are:
- Climate Modelling and Prediction: Gen AI plays a crucial role in improving climate models by analysing vast datasets and identifying complex patterns. This enables more accurate predictions of climate changes, including shifts in temperature, precipitation patterns, and sea level rise. Banks can typically leverage existing models or build new models that enable them to ascertain climate impact arising due to physical risk and transition risk and translate them in to impacts affecting existing credit risk exposures, collateral management, asset valuations and more.
- Prospecting and Origination – Banks are trying to assess physical and transition risks on clients’ credit at the start of new relationships, aligning prospecting and origination with their business strategy. While ESG metrics are available for large companies, others may require climate risk analysis based on sector concentrations and regional exposure. Due diligence procedures also vary based on client characteristics and Gen AI helps in carrying out this initial customer assessment in line with Banks Climate strategy by parsing through available data sets and providing meaningful insights.
- Credit Underwriting – Banks are progressing to incorporate climate risks into the rating and underwriting process by developing standalone borrower-specific climate risk scores or integrating assessments into standard credit rating procedures. Gen AI interventions play a pivotal role in advancing climate risk underwriting, providing innovative solutions for financial institutions. Gen AI technology allows for the creation of borrower-specific climate risk scores, considering factors like physical and transition risks, resilience to climate change, and mitigation strategies. Additionally, these applications leverage big data analytics to map out companies based on carbon clusters, enhancing the assessment of their climate risk profiles. The use of Gen AI in climate risk underwriting enables more accurate evaluations which help in contributing to more informed and sustainable decision-making.
- Climate related disclosure management – Gen AI can automate data collection, validation, and analysis, significantly reducing the time and resources required for regulatory and internal reporting. It can handle vast datasets and complex regulatory requirements, ensuring accuracy and consistency in reporting for e.g. the compiling of the required information for TCFD (Task force on climate related financial disclosures) disclosures. Furthermore, Gen AI’s adaptive nature allows it to stay abreast of evolving regulatory frameworks, automatically updating reporting protocols to align with the latest compliance standards. This ensures that financial institutions can stay abreast of the ongoing and upcoming regulatory changes.
The integration of Generative AI in climate risk management fastracks banks in addressing the complexities of environmental challenges. The application of advanced algorithms and machine learning empowers banks to develop precise and dynamic climate risk assessments. This not only enhances their ability to evaluate the impact of climate-related factors on clients but also enables the creation of bespoke risk scores tailored to individual borrowers. As financial institutions strive to navigate the evolving landscape of climate risks, Generative AI emerges as a pivotal tool, aiding in informed decision-making, regulatory compliance, and sustainable practices. The technology’s capacity to automate processes, analyse extensive datasets, and adapt to emerging environmental trends positions it as a crucial asset in fortifying banks against climate-related uncertainties and fostering a more resilient and environmentally responsible financial sector.
The author, Ajay Katara, serves as a consulting partner and leads the Reg Tech portfolio within the banking risk management domain at Tata Consultancy Services. With over 19 years of expertise in business consulting transformation and solution design, he navigates regulatory compliances in the areas of Regulatory Capital Management, Credit Risk, Climate Risk, Stress testing and Anti Money Laundering. Operating across diverse geographies, Ajay has collaborated with numerous financial institutions and enterprises. His substantial contributions to conceptualising strategic offerings in risk management and his impactful role in driving successful consulting engagements underscore his influence. He has also been awarded the Risk Management Professional of the Year award by CIRM Magazine UK in 2023.
