A Guide to Behavioural Modelling
First published:
ISBN: 978-1-78272-404-9
If you are a Risk.net subscriber you are entitled to 20% off your Risk books purchases. Please email enquiries@riskbooks.com for more information.
As part of your Risk.net subscription you are entitled to 20% off all of your Risk Books purchases. If you would like to place an order please email enquiries@riskbooks.com
NMD Behavioural Models Used in Marketing
Bogusz Stankiewicz
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
A data-driven strategy is used in business activities involving the collection and use of data for a comprehensive 3600 view of the consumer. One of the techniques in this strategy constitutes using data to analyse human behaviour, which many companies utilise to improve their offer management (such as online retailers) and products (eg, Apple).11 For instance, the online community Kaggle provided their own data and held a contest for the best model. All this means that properly used and interpreted knowledge obtained from data is increasingly desirable in the business world and is a great help for any company.
In the financial sector, one could find multiple examples where data are used to support management in various areas (eg, risk management). It is in everyone’s interest to gain knowledge through analysing “what the client does and why”. This chapter will describe a tool that can significantly contribute to an increase in business value. By using this tool, a company can improve their management, business process control and reporting as a result of understanding how bank decisions influence client behaviour in terms of non-maturity deposits (NMDs).
The chapter will
Copyright Infopro Digital Limited. All rights reserved.
As outlined in our terms and conditions, https://www.infopro-digital.com/terms-and-conditions/subscriptions/ (point 2.4), printing is limited to a single copy.
If you would like to purchase additional rights please email info@risk.net
Copyright Infopro Digital Limited. All rights reserved.
You may share this content using our article tools. As outlined in our terms and conditions, https://www.infopro-digital.com/terms-and-conditions/subscriptions/ (clause 2.4), an Authorised User may only make one copy of the materials for their own personal use. You must also comply with the restrictions in clause 2.5.
If you would like to purchase additional rights please email info@risk.net
