Credit Risk Management and Modelling, Frankfurt

Understand how to manage credit risk within your organisation; with a focus on modelling methods, stress testing and machine learning.

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Credit Risk Management and Modelling

November 13–14, 2019

Frankfurt

View course guide Apply now

  

This course is designed for anyone with credit risk responsibilities within financial services. Key sessions will cover the impacts of Basel IV and TRIM, approaches to credit risk modelling, stress testing credit risk portfolios and applications of AI and machine learning.

What will you learn?
  • Best practice approaches to managing credit risk post IFRS 9 

  • How Basel IV, IRB and TRIM interact and can be managed together

  • A new or improved understanding of credit risk modelling

  • Methods for assessing non-modelled credit risks

  • How to manage stress testing your credit risk portfolios

  • Applications for machine learning and AI

View course guide

Who should attend?

Relevant departments may include but are not limited to: 

  • Credit risk

  • Risk steering

  • Accounting

  • Hedge accounting

  • Regulation 

  • Risk modelling

  • Internal audit

  • Stress testing

  • Model risk

View pricing options

Course highlights
  • Credit risk management post IFRS 9

  • Basel IV, IRB and TRIM 

  • Structural credit risk models

  • Best practice credit risk modelling

  • Non-modelled credit risks

  • Model validation and assurance

  • Stress testing credit risk portfolios

  • Machine learning and AI in credit risk modelling

View course agenda

Course speakers

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Radka Margitova

Senior Manager | Financial Services Risk Consulting

PwC

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Dr. Zhilin Yao

Head of Risk Controlling

Agricultural Bank of China, Frankfurt

Dr. Zhilin Yao is Head of Risk Controlling at Agricultural Bank of China Frankfurt since 2013, who has over 10 years of risk experiences on different organization levels. Following his Doctor’s degree in quantitative skills and financial economics, he worked in Credit Risk Methodology/Risk Steering team at Dresdner Bank/Commerzbank (2008 -2011). He continued his career in ICAAP and Group Strategic and Capital Planning at Deutsche Bank (2011 -2013). Next to his risk job he gathers knowledge about legal as a candidate in LL.M. Finance.

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Jörg Lemm

Privatdozent

Institute of Theoretical Physics at WWU Münster

 

2001 – today: Privatdozent, Institute of Theoretical Physics at WWU Münster 

2018 – today:  DZ HYP (part time job in credit risk after retirement, since Sept. 2018)

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Stefano Bonini PhD, CStat, PStat®

Executive, finance and risk

Accenture

Stefano is a Management Consulting Director of Accenture Finance & Risk and since 2011 has led the development of Accenture Credit Risk Modeling & Validation and Model Risk offering in Italy. He built strong relationships with key clients as Banks and Rating Agencies, being in charge of numerous Risk Modeling, Validation & Model Risk projects mainly within regulatory framework of Basel II/III/IV, IFRS9, and TRIM. He also acted as advisor risk culture formation for board members of Banks under SSM. He also lead the Italian Risk Management Association Study Group on Machine Learning.

Stefano is adjunct professor of Banking and Risk Management at top tier Italian Universities like University of Bologna & MIP Business School, holds a PhD in Banking & Finance and is currently the only person with triple Certified Chartered Statistician: from USA, UK & Italian Statistical Association.

He is regular speaker to industry events & international conferences on Risk Management, is author of publications on books and international journals (Journal of Credit risk, European Journal of Finance) and collaborated with CONSOB within the "Financial Education Month”.

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Dominik Zabel

Expert in ML and development of cloud microservices services

Deloitte

Dominik Zabel studied International Economics as well as Finance with main focus on quantitative methods before joining Deloitte in 2018.

His field of work at Deloitte is related to credit risk modeling, in particular, the development and practical implementation of advanced credit risk models using standard and machine learning approaches.

On his previous projects, he implemented different machine learning algorithms for bond risk and provided the modeling services as micro services in a cloud based infrastructure using Docker container.

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Marcel Jäger

Manager credit risk & lead of ML lab

Deloitte

Marcel Jäger has more than seven years of experience regarding PD, LGD, IFRS 9 and machine learning modeling and implementation. He is the leading expert at Deloitte for the application of machine learning in the credit risk environment and leads a lab which builds machine learning prototypes for financial institutions. Since august 2017, Marcel is external lecturer for the modeling of quantitative credit risk at bFi Vienna

In his last project, he was the head of data science of a fintech and responsible to hire a team, build a cloud based infrastructure and implement credit risk models for bond risk using machine learning models and >3 terabyte of data.

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Luca Ciavoliello

Principal supervisor, supervisory policy division

European Central Bank

Luca Ciavoliello joined the Supervisory Policy Division of the European Central Bank on 1 December 2018. He is an accounting expert, in charge of leading the ECB horizontal supervisory activities on IFRS 9 for the largest banks of the euro area.

Mr Ciavoliello started his career at Deloitte in 2006 in the Financial Sector Industry, where he took part in audits and financial due diligences on banks and financial institutions. He joined Banca d’Italia in 2012 as policy expert in the Regulation and Macroprudential analysis Directorate; he represented Banca d’Italia in various technical working groups on accounting at the European Banking Authority and in the Basel Committe.

Luca holds master degrees in Banking and Finance and in Economics and Business Administration, and he is author of publications on NPLs and complex financial instruments.

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Kaan H. Aksel

Director, regulatory management - quant team

PwC Germany

Key expert in the PwC global network in developing and introducing rating models and analytical framework for assessing credit risk in accordance with Basel III and Basel IV for more than 20 years. Kaan is  one of the  leading PwC's European experts in the area of Risk Modelling & RWA optimization, being engaged in several international PwC’s projects related to risk management and measurement at various financial institutions. The Quant Team with more than eighteen expert from PwC Frankfurt, he is leading, specialized in the Regulatory questions of model development in the context of the new requirements imposed by the EBA and ECB.
Kaan has vast experience in delivering projects related to implementing Basel requirements, such as:

•Leading several TRIM and IRB Repair programmes in more then nine ECB regulated territories
•Leading Model validation engagement at several banks including proposed IRB repair adjustments
•Building comprehensive risk management systems including PD, LGD and CCF Models according to the new EBA GLs
•Developing credit rating models for Corporates, SMEs, Specialised Lending, Sovereign and Financial Institutions
•Developing application and behavioural models for retail portfolios
•Validating rating/scoring and LGD models
•Introducing Economic Capital Measurement Models for Universal  Banks
•Building risk-adjusted pricing models and limit management tools based on rating models
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Andreas Koutras

Independent Consultant

Specialities: Professional: Risk appetite, Interest Rates, Risk Management, IFRS9 implementation, Fixed Income Structured Products and Derivatives Marketing in CEEMEA European Debt, Greek Debt, stress testing, scenario analysis.
Academic: General Theory of Relativity, Time, Exact solutions of EFE, Cosmology, Complexity, Evolution, Foundation of QM

CPD / CPE Accreditation

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CPD Accreditation

This course is CPD (Continued Professional Development) accredited and will allow you to earn up to 12 credits. One credit is awarded for every hour of learning at the event.

CPE Member

CPE Accreditation

This course is CPE (Continuing Professional Education) accredited and will allow you to earn up to 12 credits. One credit is awarded for every hour of learning at the event in accordance with the standards of the National Registry of CPE Sponsors.

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