- COVID-19 is taking a toll on banking systems: Increasing vigilance of governments
- Impact of intensifying inflationary pressures on credit risk management
- How is changing customers behaviour pressuring banks to rethink the cost, efficiency and sustainability of their risk-management models and processes?
- How does the rise of digital payments impact credit risk management?
- Upgrading Basel III to Basel IV: Will it force banks to rethink their capital allocation strategies?
- How to eliminate potential cyber and ethical risks of AI and Machine Learning models?
- Importance of understanding counterparty credit risk and real-time risk monitoring solutions
- Vulnerability of banks to climate-related credit risk
- Future challenges for credit risk management
16th Annual Banking Credit Risk Management Summit
1 – 2 February 2023 | Hilton Vienna Danube Waterfront
PAST SPEAKERS
SEE THE PREVIOUS SPEAKERS & CASE STUDIES
Enno Veerman
Deputy Head IFRS9 Modelling
Idrissa Coulibaly
Chief Risk Officer
Roko Uglesic
Managing Director
for Group Models and Data
Florian Stryeck
Chief Risk Officer
Erics Plato
Senior Credit Officer
CONFERENCE TOPICS 2023
LOOK AT THE TOPICS THAT WERE DISCUSSED
Designed for
Members of board, C-level, Senior/Global Vice Presidents, Directors, Heads of departments, from the banking industry involved in:
- Credit Risk
- Trading Credit Risk
- Credit Risk Control
- Credit Risk Models
- Credit Risk Analytics
- Credit Risk Systems
- Credit Risk Review
- Credit Risk Validation
- Credit Risk Monitoring
- Credit Risk Management
- Counterparty Credit Risk Methodology
- Risk Appetite Framework and Model
- Capital Management
- Stress Testing
- Portfolio Models
- Regulatory Strategy
- IFRS 9 Regulation
- AIRB Modelling
CASE STUDY
IFRS9 Models in a Rapidly Changing Macroeconomic Environment
An important requirement of IFRS9 is the inclusion of forward-looking information, both for expected credit losses and risk stage determination. The IFRS9 models are calibrated on historical data which do not necessarily reflect the currently relevant dynamics (such as observed in the COVID-19 pandemic and the recent energy crisis). This poses challenges to the use and design of the models. In this presentation we will discuss several challenges and potential solutions, using examples from practice.
Some examples that are covered:
- Government support measures during COVID-19 pandemic distort the impact of macroeconomic variables on credit risk
- Extreme GDP shocks during the pandemic exceed values for which models are calibrated
- Currently important drivers such as inflation and energy prices for credit risk are less relevant in the period covered by historical data
Enno Veerman
Deputy Head IFRS9 Modelling
ABN Amro Bank N.V.
Roko Uglesic
Managing Director for Group Models and Data
Addiko Bank AG
CASE STUDY
Challenges of IFRS 9 Modelling in Current Turbulent Macroeconomic Environment
- Senior management is interested in the effects of inflation on IFRS 9 models. What to communicate?
- How to deal with data disruptions caused by COVID-19 measures
- How to adapt IFRS 9 models to properly take into account significant macroeconomic volatility in recent times
CASE STUDY
The Digitalisation of the Banking Credit Risk: How Does the Rise of Digital Payments Impact Credit Risk Management?
In this regard, we will share the experience of The National Bank of Investment of Ivory Coast (BNI Côte d’Ivoire) in building and implementing an efficient credit risk management framework in response to the fast-growing digitalisation of banking activities and services.
- An overview of the Banking sectors and the regulation of the credit risk in the West African Economic and Monetary Union
- The Case study of the National Bank of Investment of Ivory Coast:
- The new products and services in line with the digital payments
- The impact of digital payments on credit risk management governance, procedures and tools
Idrissa Coulibaly
Chief Risk Officer
National Bank of Investment
Erics Plato
Senior Credit Risk Expert
Nordea
CASE STUDY
Seemless Integration of Credit and Rating Processes
The regulations require”each obligor shall be assigned to an obligor grade as part of the credit approval process”. However, the rating process is based on a number of statistical models that consider information differently from human beings conducting credit assessments. This requires a concerted effort to harmonize both processes as one.
- What are the inter-relationships between the credit and rating processes?
- How to derive ratings from the credit process in a manner that reflects traditional credit assessments?
- How can you apply human judgement to the models with information from the credit assessment that is not captured by the models?
- How to integrate ESG into the credit and rating processes?
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