SPEAKERS

SAMPLE OF KEYNOTE SPEAKERS AND THEIR CASE STUDIES

Roberta RANALDI

Director – Head of Methodologies and Tools for Validation and Controls

CASE STUDY / DAY 1

Development of a Scoring Model Supporting Ex Post Controls on Credits with Machine Learning: Practical Applications in an Ordinary Context and During COVID-19 Crisis

Internal Validation and Controls Dept. is experiencing an evolution programme in terms of methodologies and tools supporting validation and second level controls on credit, in order to boost efficiency and accuracy of activities. The development of a scoring model with machine learning techniques is part of the aforementioned programme and it has been already applied to support second level controls and validation activities during IVQ 2020, during the COVID-19 crisis.

  • Overview of the scope of the model and of the methodology applied for its development
  • Fine tuning and back testing of the model in COVID-19 crisis
  • Example of application of the model and next steps
CASE STUDY / DAY 1

COVID-19 – From Internal Steering to Regulatory Perspective

The presentation focuses on the retrospective analysis performed on the main dimensions from the banking sector’s perspective, in order to identify the preferred way to move forward in times of crisis uncertainties.

  • Bank’s response to the COVID-19 pandemic, immediate focus and steps performed
  • Internal steering perspectives, from data gathering to active management, including provisioning while fulfilling IFRS 9 principals
  • Regulators’ reactions and main focus reflected in guidelines and ad-hoc requests
  • Converging point of all dimensions, from steering perspective to regulators
  • Way forward in times of crisis uncertainties

Mihaela ATOMEI

Deputy Head of Group Risk Reporting, Planning and Risk Cost Management

SUMMIT WILL HOST SPEAKERS FROM THE WORLD’S LEADING COMPANIES

Angel RODRIGUEZ-ROZAS

Associate Director, Quantitative Analyst – Model Validation

CASE STUDY DAY 2

A Novel Hybrid Monte Carlo-FEM Approach to Solving Credit Risk Valuation Problems

The speaker proposes a novel hybrid numerical method for credit risk valuation problems based on the celebrated Feynman-Kac formula. For every pricing estimation, it combines two types of numerical approximations:
• The stochastic solution to approximate the conditional expectation via (Quasi) Monte-Carlo
• The numerical solution to the corresponding Partial Differential Equation(s) (PDE), using the Finite Element Method (FEM)

This method is applicable to a wide range of credit risk models and practical examples are given. When applicable, it outperforms traditional numerical methods. Moreover, it is robust, proves to be naturally fault-tolerant, and is also suitable for solving large-scale problems on High-Performance Computing (HPC) facilities. Theoretical bounds for the numerical errors and for estimating the computational time are given.
• Theoretical context
• Foundations of the new hybrid numerical technique
• Practical cases applied to credit risk models
• Conclusions

Karlis DANEVICS

Member of the Management Board, Head of KYC/AML, Baltics

CASE STUDY DAY 2

KYC/AML Aspects of Credit Risk Management

KYC/AML has emerged as one of the key issues for reputation as well as a key risk management topic in banking and finance. Historically it has been seen as compliance and operational risk topic, while now it emerged into forefront of active risk management with some similarities with credit risk management. What are those similarities? What are the differences? How important this risk is for credit risk governance as well as risk culture in a bank? Those would be questions that the speaker tries to address in this presentation.

• Situation in Northern Europe concerning AML/KYC
• Good credit culture as the main cornerstone for KYC
• Main principles of KYC in lending and in AML
• Main principles for good AML programme – The same as in managing credit risk
• Differences between credit risk (more static risk) and AML risk (more dynamic risk)

Mihaela ATOMEI

Deputy Head of Group Risk Reporting, Planning and Risk Cost Management

CASE STUDY DAY 1

COVID-19 – From Internal Steering to Regulatory Perspective

The presentation focuses on the retrospective analysis performed on the main dimensions from the banking sector’s perspective, in order to identify the preferred way to move forward in times of crisis uncertainties.

• Bank’s response to the COVID-19 pandemic, immediate focus and steps performed
• Internal steering perspectives, from data gathering to active management, including provisioning while fulfilling IFRS 9 principals
• Regulators' reactions and main focus reflected in guidelines and ad-hoc requests
• Converging point of all dimensions, from steering perspective to regulators
• Way forward in times of crisis uncertainties

Roberta RANALDI

Director – Head of Methodologies and Tools for Validation and Controls

CASE STUDY DAY 1

Development of a Scoring Model Supporting Ex Post Controls on Credits with Machine Learning: Practical Applications in an Ordinary Context and During COVID-19 Crisis

Internal Validation and Controls Dept. is experiencing an evolution programme in terms of methodologies and tools supporting validation and second level controls on credit, in order to boost efficiency and accuracy of activities. The development of a scoring model with machine learning techniques is part of the aforementioned programme and it has been already applied to support second level controls and validation activities during IVQ 2020, during the COVID-19 crisis.

• Overview of the scope of the model and of the methodology applied for its development
• Fine tuning and back testing of the model in COVID-19 crisis
• Example of application of the model and next steps

Gilles ARTAUD

Head of Model Risk Audit

CASE STUDY DAY 1

Machine Learning in Credit Risk

Machine learning models are like any other models, but different. So easy to set in place, with abundant data and ready-to-use libraries. But is it really so easy?

• Pros and cons of applying ML in finance: AI is not new, ML used in finance, with risks and rewards
• Strategies for ML in finance – Four key issues to address tactically
• Importance of making

Angel RODRIGUEZ-ROZAS

Associate Director, Quantitative Analyst – Model Validation

CASE STUDY / DAY 2

A Novel Hybrid Monte Carlo-FEM Approach to Solving Credit Risk Valuation Problems

The speaker proposes a novel hybrid numerical method for credit risk valuation problems based on the celebrated Feynman-Kac formula. For every pricing estimation, it combines two types of numerical approximations:

  • The stochastic solution to approximate the conditional expectation via (Quasi) Monte-Carlo
  • The numerical solution to the corresponding Partial Differential Equation(s) (PDE), using the Finite Element Method (FEM)

This method is applicable to a wide range of credit risk models and practical examples are given. When applicable, it outperforms traditional numerical methods. Moreover, it is robust, proves to be naturally fault-tolerant, and is also suitable for solving large-scale problems on High-Performance Computing (HPC) facilities. Theoretical bounds for the numerical errors and for estimating the computational time are given.

  • Theoretical context
  • Foundations of the new hybrid numerical technique
  • Practical cases applied to credit risk models
  • Conclusions
CASE STUDY / DAY 2

KYC/AML Aspects of Credit Risk Management

KYC/AML has emerged as one of the key issues for reputation as well as a key risk management topic in banking and finance. Historically it has been seen as compliance and operational risk topic, while now it emerged into forefront of active risk management with some similarities with credit risk management. What are those similarities? What are the differences? How important this risk is for credit risk governance as well as risk culture in a bank? Those would be questions that the speaker tries to address in this presentation.

  • Situation in Northern Europe concerning AML/KYC
  • Good credit culture as the main cornerstone for KYC
  • Main principles of KYC in lending and in AML
  • Main principles for good AML programme – The same as in managing credit risk
  • Differences between credit risk (more static risk) and AML risk (more dynamic risk)

Karlis DANEVICS

Member of the Management Board, Head of KYC/AML, Baltics

Very good organisation and the quality of the presentations was excellent. Thank you!

Head of Internal Model Market and Counterparty Risk at Intesa Sanpaolo

Event programme

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