A Guide to Behavioural Modelling
First published:
ISBN: 978-1-78272-404-9
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Integrating Credit Risk within the ALM Framework
Alina Preger and Sophie He
Introduction
Insights on Banks’ Recourse to Behavioural Models from a Focused IRRBB Stress Test
Implementing Regulatory Guidance on IRRBB Behavioural Models: Challenges and Opportunities
The Stakeholders of Interest Rate Risk Behavioural Models
Governance of Behavioural Models
The Nature of IRRBB and Typical Metrics Employed
A Framework for Developing NMD Behavioural Models
The Literature on NMD Behavioural Models
Interest Rate Risk of Non-maturity Bank Accounts: From Marketing to Hedging Strategy
NMDs and IRRBB: A Methodological Proposal for a Behavioural Model
NMD Modelling: A Financial Wealth Allocation Approach
A Benchmark Framework for NMDs: An Application
NMD Behavioural Models Used in Marketing
The Validation of NMD Behavioural Models
The Choice of Maturity Profile in NMD Behavioural Models
Acknowledging the Elephant in the Room: The Mismatch Centre
Prepayment Risk Modelling for ALM, Finance and FTP: A Survival Model
Modelling of Prepayment on Fixed Rate Residential Mortgages: A Logistic Regression Approach
A Simple Approach to Modelling Prepayment Events
Integrating Credit Risk within the ALM Framework
Modelling Committed Credit Lines
Accounting of the Sight Deposit and Hedging
Traditionally, banks used to monitor and manage their credit risk and interest rate risk in the banking book (IRRBB) separately. On the one hand, the credit risk management team would calculate capital requirements, impairments and provisions without considering the impact of interest rate scenarios and ALM cashflow modelling. On the other hand, the IRRBB management team would project repricing cashflows and hedge net interest income (NII) and economic value (EV) sensitivities based on a contractual or behaviourally adjusted representation (prepayment, attrition, stickiness, etc), without considering the impact of default flows and credit losses, and often with simplified non-performing loan (NPL) modelling.
The introduction of new IFRS 9 accounting principles stressed the need for a stronger integration between credit risk and ALM, both in terms of cashflow modelling and of impact of interest rates scenarios on credit risk parameters. In fact, the IFRS 9 regulation, in force since January 1, 2018, moved away from the previous IAS 39’s incurred loss model based on the occurrence of specific events, and introduced a new expected (lifetime) credit loss model to anticipate the
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