Course Agenda
Agenda
Course Agenda
14:00 – 15:00
Regulatory overview, governance and key considerations
14:00 - 15:00
- Deposit modelling - where are we now and where are we going?
- Increased focus on model validation
- Interaction of risk management and cost/benefit allocation
- Key challenges
- Influx of deposits due to quantitative easing
- Excess liquidity due to COVID -19
- Difficulty predicting customer behaviours
15:00 – 15:15
Break
15:15 - 16:15
15:15 – 16:15
Non-maturing deposits modelling
15:15 - 16:15
- What characterises a good model?
- Quantification of data
- The model risk in your NMD’s and how to capture that
- Behaviour of NMD’s
14:00 – 15:00
Liquidity risk modelling
14:00 - 15:00
- Purposes of liquidity modelling
- Liquidity dynamics
- The effects of too much liquidity
- Pricing of liquidity – own funding costs
15:00 – 15:15
Break
15:15 - 16:15
15:15 – 16:15
Negative interest rate environment – interest rate risk modelling
15:15 - 16:15
- Crossing the 0% rate floor
- How are institutions dealing with negative rates?
- Can current modelling systems still be used?
- Behaviour modelling implications
14:00 – 15:00
Addressing the associated challenges of a recent accumulation of deposits
14:00 - 15:00
- Liquidity and interest risk
- How can the maturity of these deposits be estimated?
- Are current models appropriate for this scenario?
- Operational balances approach
15:00 – 15:15
Break
15:15 - 16:15
15:15 – 16:15
Electronic bank innovations – the effect on deposit modelling
15:15 - 16:15
- Developments of online banks
- Are the current models factoring in these developments?
- Transferring of deposits
- Looking forward how will this affect the deposit market?
14:00 – 15:00
Data challenges
14:00 - 15:00
- Lack of historical data – how to address this
- Calibration of models when historic data is unfavourable
- Data management and residency
- Back testing
15:00 – 15:15
Break
15:15 - 16:15
15:15 – 16:15
The infrastructure and the governance of data-aggregation and risk modelling processes
15:15 - 16:15
- An idealised data flow in rate risk and liquidity risk reporting
- Where things can go wrong: challenges to risk reporting quality
- Infrastructure-related considerations in risk reporting
- The governance of data-aggregation and modelling processes
Dr. Csaba Burger, CFA, is an experienced financial professional with a demonstrated history of modelling the interest rate risk of the banking book (IRRBB), as well as other risk and data science-related topics in the financial services industry. He obtained his Doctor of Philosophy (Ph.D.) from University of Oxford with a focus on occupational pensions. Prior to his PhD, he worked for the Global Banking Profit Pools of McKinsey & Company. After graduation, he was active pursuing various risk and data science-related projects, and re-joined University of Oxford as a Visiting Research Associate for a period of time. Today, he is the ALM Treasury data scientist at BNP Paribas Germany.