After a decade of negative or zero interest rates, European economies entered a rising rate cycle in 2022. Now, as markets anticipate the beginning of an easing cycle, deposit betas are expected to catch up. The question is, are banks prepared to compete for deposits in this environment, which is unfamiliar to a whole generation of bankers?

In 2024, a systematic approach to deposit management is not only a critical value driver but also a necessary defensive tool. By leveraging smart deposit management techniques, anchored on advanced analytics and operational capabilities, banks can optimise their deposit costs significantly.

What actions have you taken? Where can the community help you?

I personally worked with one of the large German banks on a "Basel IV" impact study back in 2016 and early 2017...now, after various delays things are getting real. Most banks are technically prepared by now but is the bank steering as well?

From our point of view, the following elements are required to successfully manage the finalization of Basel III:

1. Be aware of international differences: Basel III endgame with differing implementation horizons and capital impact (US > UK > EU). Especially global banks need to be aware and steer accordingly

2. Get your calculation toolkit ready: Transparency on Basel IV impact on a loan / trade level as well as tool to assess impact on an aggregated level is the basis for steering and risk management decisions

3. Adapt steering and pricing: Strategy and overarching principles needed now to avoid surprises down the road. Or are we actually already down the road and a bit too late to the game?

4. FTP adjustments: Change FTP in line with the above mentioned strategy and implement changes in systems. It might be a good opportunity for a more general FTP review

5. Refine capital planning: While most banks have included Basel IV impacts on an overarching level, a detailed analysis linked to the granular business plans and the pricing strategy is often missing

6. Regulatory reporting: New data attributes to be integrated into regulatory reporting to allow Basel IV RWA calculation. There are RWA optimization opportunities via data enhancements

Which challenges do you see? Where are you in the journey? How can the community help you?

Credit Spread Risk in the Banking Book (CSRBB) is one of the hot topics for Treasury (Risk) departments at the moment. Regulators have high expectations, and banks feel significant uncertainty on how they will be assessed.

To help navigate this complex landscape, my colleagues Emiliano Carchen and Matteo Baraldi have performed a comprehensive industry survey, revealing a variety of practices and interpretations of the regulatory requirements. Their findings shed light on the challenges and opportunities that banks face in managing CSRBB.

To effectively manage CSRBB and navigate the evolving regulatory landscape, we recommend the following steps:
Clarify objectives and Roles & Responsibilities
Establish a robust narrative on how you are interpreting the rules
Create a holistic framework of risk metric and reporting
Assess evolving your modelling capabilities

Which challenges do you currently see in this space?

Feel free to also reach out if we can help with more insights from our survey!

Best,
Marcel

Hi community,

I would be very interested to hear what are your lessons learned on the back of the CS situation and if you made any changes to your liquidity risk management practices (stress testing, risk appetite / limits, controls, mitigation actions, etc.)?

Looking forward to your answers.

Best,
Marcel

Hello RiskbOWl community,

Talking to CFOs and Treasurers these days, we hear the following seven top priorities:

1. Protect NII against the downturn of interest rates (interest rate strategy / modelling / positioning + deposit modelling and pricing)
2. Optimise financial resources via more strategic steering, economic profit measures and improved FTP
3. Resources-driven strategic planning making sure planning, resource allocation, forecasting, stress testing are aligned
4. Regulatory agenda with Basel III finalization, IRRBB inspections, CSRBB discovery mode
5. Cost management and investment prioritization
6. Demystify AI and translate initial pilots into real impact
7. Embedding ESG within the organisation and financial processes

What are your current priorities? Where do you see current challenges? Which topics do you want to discuss?

Best,
Marcel

As AI models are used by more and more banks for more and more use cases, the validation of such models naturally also becomes a new focus for MRM teams.

Opening up this thread to discuss issues / concerns / tips around the validation of AI models.

What worked well for you? What can be improved?

Hello RiskbOWl community,

talking to various MRM teams around the globe, the regulatory focus on non-models seems to be getting larger, either triggered via new formal regulation (such as PRA SS1/23 in the UK) or via supervisory comments by Fed / PRA / ECB / etc.

The formal criteria on how to define non-models are fairly clear, however, one discussion point which comes up over and over again, how are different banks identifying the inventory of non-models in an efficient way without boiling the ocean. For example, going through the full list of usually over 10,000 EUCs and checking which ones should be included as non-models within the MRM scope seems a very time consuming task. On the other side, trying to define the non-models in a top-down way risks that not all material non-models are identified.

Hence, my question, how are you identifying non-models which are in scope of MRM? Any pragmatic ways to help the community on this rather new topic?

Thanks,
Marcel

Hello RiskbOWl community,
Oliver Wyman recently conducted a Model Risk Management Survey with 10+ GSIBs participating (thank you to the onces who participated). One of the questions we asked in this survey was "what are your current priorities for MRM?". The top answers were:

1. 100% said: Expand the scope of MRM (i.e. adding new model types such as AI but also more and more non-models entering MRM)
2. 92% said: Increase resource productivity via simplification, streamlining, etc.
3. 92% said: Increase usage of AI tools to support validators
4. 66% said: Increase validation quality
5. less frequent answers: reduce validation frequency, change to event-based validation, increase offshoring or outsourcing

What are your current strategic priorities? Where do you see current challenges?