CLIMATE RISK

Module 1: Introduction to climate change and financial risk management

​

• Summary of climate change risk

• How does climate change translate into financial risk?

• Exposure to weather-related risks

  • physical risks

    • Climate change as a physical and meteorological phenomenon and its impacts on natural and artificial systems

    • Basic science of climate change

    • the latest scientific knowledge compiled by the Intergovernmental Panel on Climate Change (IPCC).

  • transition risks

    • The economic transition with low carbon emissions, its risks and impacts

    • The social response to climate change as a political, economic and technological response

    • the international climate change regime, and current debates and challenges, such as the "Tragedy on the horizon"

    • main policy responses to climate change at the national level (for example, emissions trading

    • introduction to the risks and opportunities that climate change implies for the financial sector (mitigation and adaptation)

    • introduction to transition risks and opportunities in the context of the new Task Force on Climate Related Financial Disclosure (TCFD)

• Risks of climate change risk

• Understand the performance of carbon as an asset class.

​

Module 2: Emerging regulatory expectations

​

• Background to regulatory initiatives: Paris Agreement and other frameworks

• Overview of current regulatory standards (for example, PRA, ECB, HKMA, MAS, etc.)

• Role of NGFS and standard setters

• Risk Management Expectations

• Challenges and opportunities Disclosure, reporting and governance frameworks

• Growing pressure for financial disclosure

• Strong ownership and oversight of climate change risk management practices

• Task Force on Climate-related Financial Disclosures TCFD

  • Understand the guiding principles of TCFD

  • Develop a comprehensive TCFD program

  • implement recommendations

• Basel

  • The role of climate-related financial risks in the regulatory and supervisory framework

  • Research related to the measurement of climate-related financial risks

  • Measures to raise stakeholder awareness of climate-related financial risks

  • Bank approaches to managing and disclosing weather-related financial risks

  • The supervisory treatment of weather-related financial risks

  • Other initiatives that are underway among the respondents.

• IFRS

  • ​Making materiality judgments

  • Apply Materiality Judgments to Weather-Related and Other Emerging Risks

  • Financial reporting considerations

  • Disclosure of weather-related risks and other emerging risks

  • Management comment: provides context to the financial statements

  • Abstract: Materiality judgments must satisfy the information needs of investors.

​

Module 3: ESG and climate change risk

​​

• Environmental, social and corporate governance (ESG) refers to the three central factors in measuring the sustainability and social impact of an investment in a company or business.

• Current trends in the ESG market

• Analysis of ESG ratings

• Adapt investment strategies to the effects of climate change

  • Build a portfolio that reflects the transition to a low carbon economy

  • Integrating the carbon transition and physical climate risk

• Distinguish the risks, challenges and opportunities associated with ESG

​

Module 4: Climate Risk Management

​

• Scenario Analysis and Stress Testing

• What is the difference between "normal" stress tests and climate change risk stress tests?

  • Bank of England stress test

• Summary of scenario analysis in the context of climate change risk

• Data management to assess the risks of climate change.

• Benefits and Issues of performing scenario analysis

• Climate change risk methodologies

• How to model the risk of climate change?

• Using and evaluating data

• Understand modeling methodologies

  • temperature alignment

  • Decarbonization Pact Methodology

  • Climate change applied to credit risk

• Challenges in climate change risk modeling

• Incorporation of climate change risk strategies

• Integrate climate change risk management into financial risk management frameworks

• Adoption of KPI, KRI to monitor climate risks.

• Use of self-assessments

• Improvement and management of business commitment

• How to successfully integrate climate risk strategies into the business.

​

Module 5: Credit risk transition risk

​​

• Scenario analysis to assess the transition risk component of a portfolio's credit risk

• Introduction: preparing banks for the low carbon transition

  • A growing need for climate scenario analysis

  • The challenge for banks

  • Take advantage of and integrate the resources available to banks

• An integrated approach to transition risk assessment Transition scenarios

  • Understand transition scenarios and their sources

  • Using scenarios for transition risk assessment

  • Closing the gap between climate scenarios and financial risk assessment

• Borrower Level Calibration

• Portfolio Impact Assessment

  • Link expected loss to transition impacts on portfolios

  • Assessment of probability of default (PD)

  • Loss Given Default (LGD) Assessment

• Putting the Approach to Work: Lessons Learned from Banking Pilots

• Piloting the transition risk methodology

• Definition of sectors and segments

• Evaluate the relative sensitivities of the segments

• Determination of calibration points at the borrower level Case studies and results

• The pilot transition scenario

• pilot results

• Transition Opportunities: Exploring an Institutional Strategy

• evaluating the market

• Grounding Opportunity Assessments in Scenario Analysis

• Assessing the market attractiveness of the segment

• Identification of banking capabilities

• Discovering the opportunities with the greatest potential

• Future Directions: Developing the Next Generation of Transition Risk Analysis

​

Module 6: Physical risks and opportunities

​​

• An Integrated Approach to Physical Risk Assessment

• Borrower Characteristics

• Insurance as a risk mitigator due to extreme climatic and meteorological events

• climate change scenarios

• Impacts of climate change on the probability of default PD

  • Evaluation of changes in the productivity of the sector

  • Adjustment of income statement metrics

  • Determination of changes in the probability of default

• Real Estate: Climate Change Impacts on LTV Loan-to-Value

  • Estimation of the impacts of extreme events on the value of properties.

  • Determining Changes in LTV Loan-to-Value Ratio

• Physical Opportunities: Exploring an Institutional Strategy

• Taxonomy of opportunities and data sources

• evaluating the market

• Evaluation of the financing demand of the sector

• Sector evaluation

• Assess the institutional capacity and market positioning of a bank

• evaluate opportunities

• Future Directions: Towards the Next Generation of Physical Risk and Opportunity Analysis

• Develop internal analytics and capabilities within banks

• Strengthening the research base

• Develop analytical platforms and tools to support physical assessments of risks and opportunities.

• Improve information flows on physical risk and adaptation between banks and borrowers

• Improve dialogue with governments and insurers

Module 7: Decarbonization and disruption

​

• The oil and gas sector

  • market trends

  • The potential impacts of a disruptive transition

  • Ensure an orderly transition

  • Analysis of climatic scenarios of the messy transition

• Utilities and Power Generation Sector

  • market trends

  • The potential impacts of a disruptive transition

  • Ensure an orderly transition

  • Analysis of climatic scenarios of the messy transition

• Metals and mining sector (industrial)

  • market trends

  • The potential impacts of a disruptive transition

  • Ensure an orderly transition

  • Analysis of climatic scenarios of the messy transition

• Agricultural sector

  • market trends

  • The potential impacts of a disruptive transition

  • Ensure an orderly transition

  • Analysis of climatic scenarios of the messy transition

​

Module 8: Climate transition scenarios

​

• Analysis of climate scenarios in the financial sector

  • Analysis of scenarios before and after the global financial crisis

  • Climate scenario analysis

• Climate scenarios

  • Introduction to Integrated Assessment Models (IAM)

  • Where do AMIs come from?

  • Advantages and Limitations of IAMs

• Key assumptions

  • What do the IAM scenarios show?

  • What socioeconomic and policy assumptions do IAMs make?

  • What technological assumptions do IAMs make?

  • Elimination and overshoot of carbon dioxide

  • Many routes up to 15 ° C

• Sectoral perspectives of climate scenarios

  • Regional, sectoral and technological coverage in IAM

  • Future energy mix at IAM

  • Understand sector-specific impacts

• Bank assessments of climate scenarios (case studies)

  • Summary of UNEP FI transition risk approach used for bank case studies

  • Case studies and perspectives of the Bank on climate scenarios

CLIMATE CHANGE and CREDIT RATING

​Module 9: Climate Impact on Credit Rating

​

• Analysis of Business Models of Corporate Credit Rating:

  • Moody's

  • Z-score

  • S&P

• Main Financial Ratios

• Data treatment

• Univariate Analysis

  • Beta transformation

• Selection of Variable Blocks

  • Principal component analysis

• Qualitative Variables

• Default definition

• Temporal horizon

• Multivariate models

  • Logistic regression

  • Multinomial Regression

• Weight of qualitative and quantitative factors

• Consistency Tests

• PD Estimation and Calibration

• Definition and creation of Master Scale

• PD Mapping to Master Scale

• Impact of climate risk

• Methodology to integrate climate risk

• Climate Risk Factors

• Exercise 1: Univariate Analysis with Financial Ratios in Excel

• Exercise 2: Analysis of Principal Components in SAS

• Exercise 3: Multivariate Model in SAS

• Exercise 4: Consistency Test in Excel

• Exercise 5: Qualitative and Quantitative Factors of the Rating

• Exercise 6: PD estimation and mapping to Master Scale

• Exercise 7: Credit rating and climate risk

​

Module 10: Climate Change in the Sovereign Rating

​

• Sovereign Risk

• transfer risk

• Country Rating Modeling

• Sovereign Rating Model emerging countries

• Sovereign Rating Model developed countries

• Univariate Analysis

• Shadow AR

• Advanced Multivariate Model for Sovereign Rating

• Climate risk impact

• Exercise 8: Impact due to climate risk Sovereign Rating

​

CLIMATE CHANGE and PD

​

Module 11: IRB PD Estimation

​

• Impact of COVID-19 on PD

• Basel III and EBA regarding the default before COVID-19

• Default definition

• Public or private moratorium

• PD PIT and PD TTC

• Detection of borrowers in default due to the Pandemic

• Adjustments for transition risks of climate change in the PD

• Adjustments for physical risks of climate change in the PD

• Credit scoring models

  • Explanatory variables of the impact of COVID-19

• Productive Behavior Score models of COVID-19

  • explanatory variables

• Credit Rating models for companies

  • Explanatory variables of COVID-19

• PD estimation

• Treatment of Panel data

• Econometric models to estimate PD

  • PD Logistic Regression

  • PD Probit Regression

  • PD COX regression of survival

  • PD Log-log Complementary

  • PD Regression Data Panel

• PD Calibration

• Calibration of econometric models

• Anchor Point Estimate

• Calibration of PD by vintages or vintages

• vintage analysis

  • PS Marginal

  • PS Forward

  • Cumulative PD

• Exercise 9: Building Advanced Credit Scoring in Python and R

• Exercise 10: Calibration of PD with COX regression in R

• Exercise 11: Calibration of PD with regression of R panel data

• Exercise 12: PD calibration with logistic LASSO model in R

• Exercise 14: Calibration of the PD with Bayesian regression probit in R

• Exercise 15: Calibration of PD with Bayesian COX regression in R

• Exercise 16: PD Calibration by Climate Adjustment

​

Module 12: Structural Models of PD

​

• ​Merton's model

• Physical Probability of Default

• Black-Scholes-Merton model

• Black–Cox model

• Vasicek–Kealhofer model

• CDS Pricing

• Curves in liquidity and non-liquidity conditions

• CDS Implied EDF

• CDS Spreads

• Fair Value Spread

• CDS Spread in Sovereigns

• DD Default Distance

• Impact of climate change

• Coal Price Sensitivity

• Exercise 17: Estimation of CDS Spread and PD

• Exercise 18: Estimate of EDF and DD adjusted for climate change

​

​Module 14: Lifetime PD Models

​​​

• Adjustments for transition risks of climate change in the PD

• Adjustments for physical risks of climate change in the PD

• PD Lifetime consumer portfolio

• PD Lifetime mortgage portfolio

• PD Lifetime Wallet Credit Card

• PD Lifetime portfolio SMEs

• vintage model

  • Exogenous Maturity Vintage EMV Model

  • decomposition analysis

  • COVID-19 Pandemic Application

  • Advantages and disadvantages

• Basel ASRF model

  • Matrix ASRF model

  • Leveraging IRB in IFRS 9

  • Advantages and disadvantages

• Regression Models

  • Logistic Multinomial Regression

  • Ordinal Probit Regression

• Survival Models

  • Kaplan–Meier

  • Cox regression

  • Advantages and disadvantages

• Markov models

  • ​​Multi-State Markov Model

  • Advantages and disadvantages

• Machine Learning Model​

  • Support Vector Machine

• Deep Learning Models

• Neural network architecture

• PD Lifetime Extrapolation Models

• Lifetime PD Calibration

• Exercise 19: PD Lifetime using vintage EMV Decomposition model using pandemic data

• Exercise 20: PD Lifetime using multinomial regression in R

• Exercise 21: PD Lifetime using Markov model

• Exercise 22: PD Lifetime using matrix ASRF model

• Exercise 23: PD Lifetime using extrapolation approach

• Exercise 24: PD Lifetime using SVM in Python

• Exercise 25: PD Lifetime using Deep Learning in Python and PD calibration

​

CLIMATE CHANGE and LGD

​

Module 15: LGD in Mortgages and IRB companies

​

• Impact of COVID-19 on LGD

  • definition of default

  • moratoriums

  • Renovations and restructuring

  • Default Cycle

  • Real Default Cycles

• Adjustments for climate change transition risks in LTV and LGD

• Adjustments for physical risks of climate change in LTV and LGD

• Expected Loss and Unexpected Loss in the LGD

• LGD in Default

• Default Weighted Average LGD or Exposure-weighted average LGD

• LGD for performing and non-performing exposures

• Treatment of collaterals in the IRB

• Workout Focus

  • Techniques to determine the discount rate

  • Treatment of recoveries, expenses and recovery costs

  • Default Cycles

  • recovery expenses

• Downturn LGD in consumer portfolios

• Downturn LGD in Mortgages

• LGD in Mortgages adjusted for climate change

• LGD in companies adjusted to climate change

• Exercises 26: Estimation and analysis of LGD and Exp. Weighted Ave. LGD

​

Module 16: LGD Econometric Models

​

• Advantages and disadvantages of LGD Predictive Models

• Forward Looking models incorporating Macroeconomic variables

• Parametric and non-parametric models and transformation regressions

• Typology of LGD Multivariate Models

  • Linear regression and Beta transformation

  • Linear Regression and Logit Transformation

  • Linear regression and Box Cox transformation

  • Logistic and Linear Regression

  • Logistic and nonlinear regression

  • Censored Regression

  • Generalized Additive Model

  • neural networks

  • Beta regression

  • Inflated beta regression

  • Fractional Response Regression

• Exercise 27: Logistic and linear regression LGD in SAS

• Exercise 28: LGD Neural Networks

• Exercise 29: Beta Regression Model LGD in R and SAS

• Exercise 30: Comparison of the performance of the models using Calibration and precision tests.

​

​