1. Modelling Trends and Model Risk Management
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Modelling Trends and Model Risk Management
S. van Westerop, May 2016

2. Modelling Trends
In de late eighties credit scores where used to assist in accept/reject decisions on retail loans, in the end of the 90s artificial intelligence gets applied, scorecards sometimes replace by neural networks
Scorecards

3. Modelling Trends
Around 2008 banks started to qualify for the internal rating based approach (IRB)
Being able to qualify for IRB lowered the capital requirement on loans
IRB PD
IRB CCF
IMM/PFE
IRB LGD
Scorecards

4. Modelling Trends
Banks start using modified IRB parameters for Raroc/Pricing
Post-crises banks are asked to perform stress tests, with given stress scenario's
PD, LGD etc. dependent on stress scenario
PD, LGD etc to estimate losses in adverse, base case
EAD, LGD forecast for
Calculating Risk / Return / Priding
IRB PD
IRB CCF
IMM/PFE
IRB LGD
Scorecards

5. Modelling Trends IFRS9 PIT PD ECL, stage 2 ‘lifetime loss’ (B)CVA
As of many banks need to comply with IFRS9, a revised provision framework.
Banks are calculation BCVA for derivative positions using similar building blocks as used for counterparty credit risk (as used in IMM)
IFRS9
PIT PD ECL, stage 2
‘lifetime loss’
(B)CVA
PD, LGD etc. dependent on stress scenario
PD, LGD etc to estimate losses in adverse, base case
EAD, LGD forecast for
Calculating Risk / Return / Priding
IRB PD
IRB CCF
IMM/PFE
IRB LGD
Scorecards

6. Modelling Trends - Conclusion
The developments in the last 30 years led to:
A large increase of risk management models in the area of credit risk
These models are used in an increasing scope, initially for underwriting, but evolving into pricing/risk return, stress testing, provisioning
The application of components of the counterparty credit risk models (credit risk on derivatives) is broadening to the field of Credit Valuation Adjustments (CVA)
The models show large similarities, can/should not be the same for compliance reasons and their deviating purposes
This all becomes difficult to maintain: the huge model portfolio needs to be managed!

7. Model Risk Management Regulation Model Risk
Model Risk Management Framework
Framework elements
Policy elements
Formal Definition
Benefits

8. Model Risk Management – Regulation
Detailed US regulation (SR 11-7) is being enforced
The standard is raised by introducing new European requirements (CRD4) and consultative papers (CP 36) US EU SR
CRD IV / SREP
Requirements :
MRMF
Effective Challenge
Model risk governance is provided at the highest level by the board of directors and senior management when they establish a bank-wide approach to model risk management.
Requirements
Assess underestimation of own funds. “E.g. IRB model deficiency is considered as part of the credit risk assessment”
Assess losses relating to the development, implementation or improper use of any other models

9. Model Risk Management – Model examples
Scorecard for accept/reject decisions in retail finance
Value at Risk model for market risk limits
Loss given default model for capital on performing loans
Residual value model for leasing contracts
Propensity to buy model for marketing
Return on Risk Adjusted Capital for deal selection
Valuation of an interest rate swap

10. Model Risk Management Framework
Governance documents
Model Committees
Group-level systems
Model Inventory
Model Library
Model Portfolio reporting
Model Chain KPI’s
All entities and departments involved (such as senior management, modelling, validation, users)

11. MRMF Elements Definitions Policy Requirements Roles & Responsibilities
Model
Model Risk
Model Purpose & Model Application
Model Types
Policy Requirements
Roles & Responsibilities
Committee framework
Definition of roles & responsibilities

12. MRMF elements - Model Definition
Basic Model Definition (SR 11-7)
A model is a quantitative method, system, or approach that applies statistical, economic, financial, or mathematical theories, techniques, and assumptions to process input data into quantitative estimates. [..]
Key: In case a collection of models is built and used for a single and unambiguous purpose, then such a collection should be managed as a single model
Exclusion: Simple computations; End User Computing

13. MRMF - Elements Model Risk Assessment Risk = Impact x Uncertainty
Impact = Magnitude of loss if model outcome is wrong
Uncertainty = How (un)likely does a mistake occur
Impact is correlated with size of modelled portfolio or expected new business valume
Uncertainty is correlated with complexity of the model of its embedding or implementation

14. MRMF - Benefits Benefits of an MRMF
The model risk assessment could steer the intensity of controls such as model validation processes, allocating resources commensurate with model risk.
The model inventory makes transparent which models are around and what model risk they induce. It can be used to report to senior management as part of the risk appetite statement.
This model inventory date can be used by an architect to steer the evolution of the models and increase their coherence.

15. Questions?