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Hottest information about 13th Annual Banking Credit Risk Management Summit

20 January 2020

18 January 2020

Whitepapers - Management Solutions

16 December 2019

ULF  HOLMBERG

Stress Test and Regulatory Affairs Specialist
Swedbank

3 Questions For Ulf Holmberg

What are the main challenges of stress testing for your organisation?

Stress tests tend to be resource intense and cumbersome activities, particularly since we always want to integrate model outputs with qualitative, judgement-based assessments. Going forward, I believe that through the cycle elements in risk management, together with various Basel IV modifications are problematic since they make REA and other risk metrics less sensitive to macroeconomic risk. Figuring out how to retain macroeconomically induced stress and how to conceptualise macroeconomic risk within this new regulatory environment is a challenge that needs to be dealt with.

What to look out for in stress testing for the future?

Look out for the growing importance of climate change risk and stress testing as most banks will seek to implement the Financial Stability Board’s Task Force on Climate-related Financial Disclosures recommendations. As the recommendations suggest, financial institutions should seek to understand their climate change risk exposure using scenario analysis, a modification of banks current scenario-based stress testing practices is an obvious candidate in the pursuit of compliance. However, as the “usual” climate change scenarios stretches far into the future, the challenge becomes how to integrate this viewpoint into banks’ regular scenario modelling practices which in general have shorter scenario horizons.

What are the newest technology trends in banking industry and how do they affect credit risk management?

The biggest single technological advancement is probably the increasing reliance on artificial intelligence (AI) and AI driven methodologies, models and assessments. All this as AI technology opens up for “data mining of statistical techniques” which will improve risk management and stress testing practices. But as the technology advances many analysts are likely to move from modelling to inference which could change risk management practices within the industry.

Ulf Holmberg is a Stress Test & Regulatory Affairs Specialist with PhD in Economics. He has experience of central banking and from work done within various international working groups such as the ESRBs ATC Task Force on Stress Testing and the IBRN. Ulf specialises in scenario design and probability calculations and seeks ways to merge regulatory changes with current risk management practices. As a strong believer in the power of econometrics, Ulf seeks methods to merge statistical techniques with expert judgement in a transparent and tractable way.

5 December 2019

RALF  ZEITLBERGER

Head of Holding / EGI Corporate & RE Workout
Erste Group

3 Questions For Ralf Zeitlberger

Which areas of regulations are banks finding most challenging?

First of all, capitalisation and all related topics such as equity definition (Tier 1, Tier 2) and RWA-calculation are keys. European banks need equity to finance business growth and have to offer a profitable business outlook to attract investors.
But of course, other regulatory requirements are demanding and challenging as well.

What is the impact of regulations on your organisation?

When you say “NPL Management”, the biggest impact is the establishment of the “prudential backstop”. It means that banks have to restrict their time to solve NPL portfolios or to invest their own equity. This might change the business model for banks: Instead of handling NPLs, sell them to investors. It will have a negative impact on risk costs and the “lessons learned part”. I doubt that our business will be more secure.
Additionally, non-bank investors in NPL portfolios have little regulatory burden and limited reputational risk.

What trends can we expect in credit risk management in 2020 and after?

In risk management digitalisation, automatisation and use of data will be more and more important. Nowadays, an SME client demands a working capital facility for his enterprise and negotiates the terms and conditions with his relationship manager of the bank.
In the future, the machine will calculate all possible business opportunities on the basis of automatically transferred and stored data and will answer without human interference. Quality, time and costs of decisions will be optimised, depended on available data.

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