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A Guide to Behavioural Modelling



A Guide to Behavioural Modelling

Matteo Formenti and Umberto Crespi





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Dedicated to our families (Mums and Dads, Giulia and Paola, and our sons),

and to all colleagues and friends with whom we spent hours talking about

client’s behaviour



Contents

About the Editors

About the Authors

Introduction

PART I: INTRODUCTION TO IRRBB

1 Insights on Banks’ Recourse to Behavioural Models from a Focused

IRRBB Stress Test

Federico Pierobon

European Central Bank

2 Implementing Regulatory Guidance on IRRBB Behavioural Models:

Challenges and Opportunities

Enrique Benito

Deloitte

3 The Stakeholders of Interest Rate Risk Behavioural Models

Roberto Virreira

State Street

4 Governance of Behavioural Models

Daniel Almehed

BearingPoint

5 The Nature of IRRBB and Typical Metrics Employed

Jacek Rzeźnik

mBank



PART II: NMD BEHAVIOURAL MODELS

6 A Framework for Developing NMD Behavioural Models


UniCredit Group

7 The Literature on NMD Behavioural Models

Serena Di Rienzo

UniCredit Group

8 Interest Rate Risk of Non-maturity Bank Accounts: From Marketing

to Hedging Strategy

Andreas Blöchlinger

Swisscanto Invest by Zürcher Kantonalbank

9 NMDs and IRRBB: A Methodological Proposal for a Behavioural

Model

Rosa Cocozza, Domenico Curcio; Igor Gianfrancesco

University of Naples Federico II; Extrabanca

10 NMD Modelling: A Financial Wealth Allocation Approach

Francesco Frascarelli and Vanessa Pagliaccia

UniCredit Group

11 A Benchmark Framework for NMDs: An Application

Antonio Castagna; Antonio Scaravaggi; Bernardo Rapagnetta

Iason Ltd

12 NMD Behavioural Models Used in Marketing

Bogusz Stankiewicz

mBank

13 The Validation of NMD Behavioural Models

Marco Palumbo

UniCredit Group

14 The Choice of Maturity Profile in NMD Behavioural Models



Matteo Formenti

UniCredit Group

15 Acknowledging the Elephant in the Room: The Mismatch Centre

David Green

David Green Advisors, LLC

PART III: PREPAYMENT BEHAVIOURAL MODELS

16 Prepayment Risk Modelling for ALM, Finance and FTP: A Survival

Model

Pierluigi Coriazzi and Lisa Signani

Prometeia

17 Modelling of Prepayment on Fixed Rate Residential Mortgages: A

Logistic Regression Approach

Roberto Baccaglini

UniCredit Group

18 A Simple Approach to Modelling Prepayment Events

Matteo Formenti and Mattia Rossi

UniCredit Group and Santander UK

PART IV: BEHAVIOURAL MODELS FOR NON-PERFORMING

EXPOSURE AND COMMITTED LINES

19 Integrating Credit Risk within the ALM Framework

Alina Preger and Sophie He

Prometeia

20 Modelling Committed Credit Lines

Antonio Castagna

Iason Ltd

PART V: ACCOUNTING AND HEDGING

21 Accounting of the Sight Deposit and Hedging



Luca Ingargiola

Deloitte

Data Used in the Book

Bibliography



About the Editors

Umberto Crespi has over 20 years of experience in the banking sector. He

started his career in 1999 on the financial engineering desk of Fineco Bank

SpA, and after eight years became the Head of Treasury & ALM. In 2007,

Umberto moved to the Group Finance Department of UniCredit Group to

cover different activities, and in 2010 was appointed Head of the Model and

Interest Rate Strategy team within Group ALM & Financial Planning, with

responsibility for behavioural models and banking book interest rate risk

strategy. Currently, he is the Head of the Operational ALM team within

Group Finance Department. Umberto is a member of the European Banking

Federation ALM IRRBB Working Group and the ASSIOM FOREX ALM

Commission. He has a degree in monetary and financial economics from

Bocconi University in Milan.

Matteo Formenti works at UniCredit Group, where he was initially in the

group’s internal validation team on the internal models for Pillar 1 and Pillar

2 of the Basel Accords, with a focus on the validation of behavioural models

for ALM purposes (interest rate and liquidity risk). He then joined Group

Finance Department with a specific focus on ALM topics such as the

development of behavioral models across the Central Eastern Europe and

banking book interest rate strategy. Matteo currently manages the team in

charge of executing and setting the fund transfer pricing within the Group. He

is visiting professor of market risk at MIP (Milan Politecnique) and full

professor of asset management at LIUC (University of Castellanza), and

holds an MSc in economics and a PhD in finance with a theoretical and

empirical thesis on asset pricing theory.



About the Authors

Daniel Almehed is a senior expert in the risk management team within the

banking and capital markets practice of BearingPoint, with more than 10

years’ experience in a variety of roles in risk management projects for

international acting banking groups. He has a specific focus on banking book

risk controlling and management, covering interest rate risk in the banking

book (IRRBB) and liquidity risk. Daniel’s project experience covers

governance and process aspects, and development of methodology, as well as

ALM and risk software specifications and implementation. He is a regular

speaker at IRRBB events, and holds a PhD in theoretical physics.

Roberto Baccaglini has been working at UniCredit Group since 2012, after

obtaining a master’s degree in physics. After a few years as a maintainer of

models for market risk measures calculation in the chief risk officer area, he

worked in Group Finance Department, where his activity was mainly focused

on the development of behavioural models for pricing purposes and, in

general, the monitoring of IRRBB. Roberto has been continuing the

development of behavioural models in the chief risk officer area, especially

on data and statistical analysis, since 2018.

Enrique Benito works at Deloitte in London, where he provides advice on

ALM and liquidity risk management to global financial institutions. His past

experience includes roles with GE Capital Bank, where he contributed to the

set-up of its treasury function and was responsible for the bank’s liquidity

and funding management. Prior to that, Enrique was with the Financial

Services Authority, now part of the Bank of England, where he contributed to

the development of the first post-crisis liquidity risk regime and represented

the UK in negotiations of the Capital Requirements Regulation. He started

his career at the Central Bank of Spain.

Andreas Blöchlinger is an adjunct professor (senior lecturer with



habilitation) for banking and finance in the Department of Economics at the

University of Zurich and chief risk officer of Swisscanto Invest by Zürcher

Kantonalbank (ZKB). At ZKB, he is responsible for the risk management

function by identifying, modelling, measuring, monitoring and mitigating

market, liquidity, credit, counterparty and operational risk. Until 2016,

Andreas was head of ALM at ZKB, responsible for the interest rate risk

management of the banking book and the management of financial assets.

Before joining ZKB in 2006, he worked at Credit Suisse Group, latterly as

head of credit risk analytics, where he was responsible for the development of

credit portfolio and credit scoring models. Andreas completed his studies at

the University of Zurich with a licentiate in economics and a doctorate in

finance, and his academic papers have been published in a range of

prominent journals.

Antonio Castagna is partner and co-founder of the consulting company

Iason Ltd, providing support to financial institutions in designing models to

price complex derivatives and measure risks. He was previously at Banca

IMI in Milan from the 1999 to 2006, where he was a market maker of

caps/floors and swaptions, before setting up the FX options desk and running

the book of plain vanilla and exotic options on major currencies, as well as

being responsible for FX volatility trading. Antonio started his career in

investment banking in 1997 at IMI Bank in Luxembourg as a financial

analyst. He has written papers on issues such as credit risk, derivative pricing,

collateral management, managing of exotic options risks and volatility

smiles, and is the author of books on FX options and smile risk, and liquidity

risk. Antonio graduated in finance from LUISS University in Rome.

Rosa Cocozza is Full Professor of Banking and Finance at the University of

Naples Federico II. She is also chair of the board of directors of the pension

fund of the University of Naples Federico II, and former director of the PhD

programme in mathematics for finance at the university, where she holds the

chair of Financial Risk Management and the chair of Financial Engineering.

Rosa served as scientific director of the insurance section of the LUISS

Business School in Rome, and is the author of an insurance management

textbook and an extensive number of research papers in scientific journals, as

well as presenting at international conferences. She holds a PhD in business

administration from the University of Naples Federico II and an MA in



banking and finance from the UCNW in the UK.

Pierluigi Coriazzi is senior specialist at Prometeia, which he joined in 1998.

During his career, he has worked on credit risk (both exposure at default and

loss given default) and asset management (portfolio optimisation), and now

coordinates R&D activities for statistical application to behavioural models in

ALM and liquidity. Pierluigi is a lecturer in the application of statistical

models to risk management on university courses, and graduated with

honours in economics from the University of Pavia.

Domenico Curcio is associate professor of Banking and Finance at the

University of Naples Federico II. He is also adjunct professor of Economics

and Management of Financial Intermediaries (advanced course) at LUISS

University, where he gained a PhD in finance. Domenico was visiting scholar

at the Department of Finance, New York University Stern School of Business

and at the International Center for Financial Research of the Lally School of

Management and Technology of the Rensselaer Polytechnic Institute. His

research spans the areas of banking, risk management and financial

regulation, his studies have been presented at international conferences, and

he has been published in a number of international scientific journals.

Serena Di Rienzo works in the financial risk methodologies team at

UniCredit Group, which she joined after working in the Group Finance

Department of UniCredit Group, and before that in valuation and risk factor

analysis at Generali Investment Europe. Her main focus is on behavioural

models within the framework of liquidity and interest rate risks of the

banking book, increasingly complementing her quantitative skills with a

functional background and personal interest in international monetary

politics. Serena earned a summa cum laude master’s degree in economics and

finance from Bocconi University in Milan, with a final dissertation on the

modelling of non-maturing deposits.

Francesco Frascarelli is an expert in ALM with seven years of experience at

UniCredit Group ALM & Financial Planning working as a developer of

behavioural models for liquidity, interest rate risk, FTP and strategic balancesheet

management. He currently works in the Group Finance Department.

Francesco gained an MSc in mathematical finance from the University of

Perugia.



Igor Gianfrancesco is head of the Risk Management Department at Arepo

BP, the holding company of the Banca Profilo Banking Group, and at

Extrabanca. He previously worked in the risk management department at

Banco di Desio e della Brianza and Banca Popolare di Spoleto, and in the

research department at Capitalia Banking Group. Igor was visiting scholar at

New York University Stern School of Business and at the International

Center for Financial Research of the Lally School of Management and

Technology, Rensselaer Polytechnic Institute, and also carries out

autonomous research on banking risk management. He has presented at

international conferences, and been published in international scientific

journals. Igor has a National Scientific Qualification as an associate professor

in banking and finance within the Italian University system and also obtained

full professorship, and has a PhD in finance from LUISS University, where

he teaches undergraduate courses.

David Green is an expert in risk and profitability management based on

more than 20 years in banking, bank regulation, consulting and software

development. Before that, he was treasurer at BankUnited, where he was

responsible for ALM, FTP, the investment portfolio, funding and derivatives,

and was also A/L manager at SunTrust Bank, where he built and managed

static and stochastic interest rate risk models and worked to align a number of

business functions. David was chairman of the Georgia Bankers

Association’s A/L Management Committee, served as a bank examiner at the

Federal Reserve Bank of Atlanta, and was also chairman of

SunGard/Bancware’s US Client Advisory Council. He is a frequent

conference speaker, and delivers workshops on ALM, FTP, behavioural

modelling and stress testing. David holds a PhD in economics from Georgia

State University, a BS in applied mathematics from Georgia Tech and is a

CFA charterholder.

Sophie He is a manager at Prometeia within the enterprise risk management

practice. She is part of the ALM and liquidity, and the risk integration

competence lines, and is involved in pioneering projects across the EMEA

banking industry. Sophie has gained extensive experience in ALM, including

IRRBB, liquidity risk, FTP and performance management, regulatory and

cross-risk stress testing, and integrated balance-sheet management in diverse

markets and countries. Before joining Prometeia, she worked in the group



ALM department at Société Générale banking group. Sophie is also a regular

speaker at financial risk events, trainings and workshops in marketplaces

such as London and Istanbul.

Luca Ingargiola holds a senior management role with Deloitte in Milan, and

has over 10 years of experience in financial services, with in-depth

knowledge of auditing the financial statements of banks and investment firms

with a strong focus on risks identification practices and the application of

International Financial Reporting Standards (IFRS). He is part of Deloitte’s

national audit support team providing technical support countrywide on the

main application issues regarding IAS 32, IAS 39, IFRS 9, IFRS 13 and IFRS

7, with specific expertise in the valuation and accounting treatment of

derivative financial instruments and hedge accounting. Luca is also part of

the Office of the Professional Practice Director, with the role of financial

instruments specialist/advisor.

Vanessa Pagliaccia works in operational ALM team within the Group

Finance Department of the UniCredit Group. She started her career in 2010 in

UniCredit Group’s ALM & Financial Planning, and as developer of

behavioural models for liquidity, interest rate risk, FTP and strategic balancesheet

management. Vanessa was previously a consultant with Deloitte,

serving the main Italian banks on risk and financial projects. She holds an

MSc in mathematical finance from the University of Perugia.

Marco Palumbo is head of behavioural models, liquidity and IRRBB

validation at UniCredit Group, where he mainly focuses on models’

benchmarking, statistical results interpretation and backtesting procedures,

highlighting the impact of each modelling choice on IRRBB and liquidity

risk measures. He has over 18 years of experience in ALM and risk

management, having worked at Capitalia SpA as a strategic ALM analyst and

in Intesa SanPaolo’s risk management unit. Marco’s interests mainly lie in

statistical methods and macroeconomics, and he is currently involved in a

project on the application of machine learning techniques to model validation

topics. He completed its MSc in economics and finance, and his

undergraduate studies in quantitative methods for economics, at the

University of Naples Federico II.

Federico Pierobon is an adviser at the European Central Bank Banking



Supervision, where he works in the SSM Risk Analysis Division, the unit

responsible for risk analyses and the stress testing of banks under direct ECB

supervision. He previously held a similar position at Banca d’Italia. During

his career as a supervisor, Federico has focused on IRRBB, liquidity risk and

stress testing, and has acted as a project lead for the ECB’s sensitivity

analysis of IRRBB – stress test 2017, and in the ECB’s sensitivity analysis of

liquidity risk – stress test 2019. He is a regular speaker at conferences and

seminars on these subjects.

Alina Preger is a partner at Prometeia, which she joined in 1999. She is head

of the ALM and liquidity competence line within Prometeia’s enterprise risk

management area, coordinating R&D activities for ALM and innovative pilot

projects. Alina leverages her experience in ALM projects, covering interest

rate risk, liquidity risk, funds transfer pricing and planning, in both the risk

management and finance departments for a number of major Italian and

international banking groups. She is also lecturer on training courses for bank

professionals and university masters on financial risk management, and a

speaker at events and industry workshops. Alina graduated with honours in

economics from the University of Bologna.

Bernardo Rapagnetta joined Iason in 2018 as a quant analyst to support a

pan-European bank in the implementation of credit risk EBA and the ICAAP

stress test. He has a pivotal role in developing SAS codes aimed at executing

data analysis and managing each part of the process, from data quality to the

processes of IFRS 9 staging simulation and consequent ECL calculation.

Bernardo gained work experience at Crif SpA in Italy, where he developed

both quantitative and functional analyses, aimed at the realisation of abstract

and complex processes within the credit risk environment. He has a degree in

physics and an MSc in quantitative finance, as well as second-level masters

in quantitative risk management, specialising in credit risk modelling and

estimation techniques.

Mattia Rossi is a market and structural risk analyst at Santander UK. He

previously worked for a major international bank in the market risk team,

where he worked on their mortgage prepayment model, and later as part of

the behavioural models ALM team at UniCredit Group, with responsibility

for the Italian prepayment model enhancement. Mattia then joined a major



consulting company with a specific focus on the interest rate and liquidity

risk. He graduated in banking and finance from the University of Brescia, and

completed his studies in quantitative finance at University of Bologna, and

later at the Polytechnic University of Milan.

Jacek Rzeznik ´ is a vice director at mBank, which he joined in 2014. His

responsibilities include measuring, reporting, analysing and setting

governance framework for market risk, IRRBB and liquidity risk. Jacek has

over 13 years of risk management experience, especially in risk governance,

stress testing, contingency planning, ALM, FTP and regulatory topics, and is

a member of the risk committee, ALCO and the ALM committee. Prior to

joining mBank, he worked at JP Morgan Chase in global credit risk

management in London, and latterly as a vice president with credit authority.

In 2018 he was nominated as a Future Leader in Finance by the Institute of

International Finance. Jacek regularly runs training courses and presents at

conferences, and holds an MSc in management and regulation of risk from

London School of Economics and a BSc in international business

administration from RSM Erasmus University.

Antonio Scaravaggi has been head of the models development and stress test

framework for Iason’s Research Department since 2017. He started as quant

analyst with Iason, developing an understanding of statistical and predictive

modelling, and being involved in the company’s strategic projects. From

2016, Antonio led a Iason team to provide methodological and governance

services to a pan-European bank during the implementation and performance

of periodic credit risk and liquidity risk EBA stress-test exercises. As team

leader, he also works on new product developments in the forecasting models

for credit and liquidity risks and NPL pricing models with machine learning

algorithms. Antonio gained an MSc in mathematical engineering from the

Politecnico di Milano, with specialisation in quantitative finance.

Lisa Signani is a specialist at Prometeia, where she has gained nearly 15

years of experience, working on behavioural modelling for interest rate risk,

liquidity risk and fund transfer pricing analysis. She is a member of the

behavioural modelling team, driving improvement in prepayment, nonmaturity

deposits and other major behavioural models for the banking book.

Lisa has extensive experience in analysing massive datasets gained from



directly building models for several banking groups, and is a speaker on

training courses for bank professionals and university masters on financial

risk management behavioural modelling. She holds an MS and a BS in

finance and economics from the University of Bologna.

Bogusz Stankiewicz holds an expert role in the field of statistic and analysis

in retail banking at mBank, and has over 10 years’ experience in data. His

career has focused on data and its management, and he has developed data

warehouses that help to prepare more advanced models in fields such as

credit scoring, propensity to buy, client segmentation and offer management.

He has a focus on statistical knowledge and experience to deal with problems

around business strategy and creation of customer value (hypothesis testing

and inference).

Roberto Virreira works as Risk Director for State Street in London. He

previously redesigned the IRRBB framework at Standard Chartered Group,

and was also in charge of Group HSBC IRRBB reporting and IRRBB stresstest

methodologies. Before that, Roberto was head of ALM and BSM with

Bank of America, and worked in consulting projects and senior roles in

treasury and finance for several other global and regional banking

organisations. He participated in the review, discussion and feedback of

BCBS 368 with several banking associations, and has published journal

articles on IRRBB and in the second edition of The Handbook of ALM by

Risk Books. Roberto has chaired a number of IRRBB conferences and been a

speaker at seminars around the world. He is an industrial engineer, and holds

a masters degree in economics and an MBA from Warwick Business School.



Introduction


UniCredit Group

Client behaviour deeply impacts a bank’s liquidity, funding, interest rate

position and, consequently, the management of its asset/liability mismatch

and related profitability. Since the 2008 global financial crisis, an increasing

interest from external stakeholders (regulators, shareholders, institutional

investors) in understanding how client behaviour impacts banks’ profitability

has been observed, as well as how banks manage their liquidity, funding and

interest rate risk in light of it.

The output of behavioural models is also relevant for many of the internal

processes and stakeholders of a bank. For example, models are used: in the

treasury processes in setting the optimal interest rate hedging strategy in view

of a customer’s prepayment option; in the planning processes to assess the

contribution of maturity transformation on a bank’s net interest margin; in the

internal interest transfer system to identify the value-creating and destroying

businesses (eg, shorter duration of loans due to prepayment implies a lower

cost of funding that is allocated to that business); in the marketing strategy to

define the clients that are more important in providing a stable funding

source; and in internal control activity to verify the assumptions and

soundness of behavioural models and the related output.

Due to these factors, this book will aim to explain in a simple and effective

way how it is possible to model client behaviour for the proper management

of banks’ balance sheet, and to expand the knowledge of drivers of

behavioural models and to clear up some of the doubts of the different

stakeholders related to a bank’s ability to properly manage their clients

behaviour. The withdrawal option of non-maturity deposits (NMDs) and a

loan’s prepayment option are the main focus, although we do not ignore other

behavioural phenomena such as the integration of credit risk within the



behavioural modelling for asset/liability management (ALM) or the treatment

of the uncommitted lines.

The activities of raising deposits from, and providing credit to, clients are

crucial for a commercial bank. 1 Both show a behavioural vein: the first

because clients can withdraw their deposits without notice, the second

because clients may prepay their loans before maturity. An understanding of

client behaviour is essential in commercial banks where NMDs are one of the

main sources of funding. The relevance becomes straightforward considering

that maturity transformation is a key function of banks. Commercial banks

have to transfer funds from clients in surplus demanding short-term deposits

to clients with long-term financing needs. A significant percentage of NMDs

are normally used by banks for funding medium long-term assets.

Furthermore, the maturity/duration transformation activity is an important

driver of the net interest margin as banks invest in long-term assets to hedge

their deposit franchise, which is due to banks’ market power in sight deposit

markets that allows them to keep deposit rates low even as the short rate

rises. By hedging their deposit franchise, banks earn a spread between the

long-term rates on loans and short-term rates on deposits.

NMD behavioural models are a crucial driver of the maturity

transformation activity and bank’s profitability since their goal is to estimate

the stable source of funding, the volume that can be used for medium longterm

lending and the volume that represents a stable/low cost fixed rate

liability to be hedge. On the other hand, the prepayment option, by reducing

the contractual weighted average life on a commercial loan portfolio, has an

impact on the actual maturity/duration transformation. The prepayment

behavioural models are important to assess the actual weighted average life

of medium long-term assets because their goal is to estimate how the

contractual profile of the loans will be reduced because of clients’

prepayment option. The shortening of the maturity profile has an impact on

bank’s liquidity position by increasing short-term liquidity inflows and

reducing medium long-term funding needs. Moreover, the shortening of the

assets’ duration affects the interest rate risk position and related hedging

strategy.

A stronger integration between credit risk models and the standard ALM

framework allows a better modelling of expected cashflows. The increase in

delinquency and default rates alters the amount and timing of contractual

cashflows and impacts bank’s liquidity and interest rate position. As by their



nature behavioural models are very heterogeneous and their use within banks

so widespread, we split this book into five parts to introduce the reader to the

topic, to take a deep-dive into each specific category of modelling (NMDs,

prepayment, other optionalities), and lastly to have a general overview of the

relationship between accounting treatment and the behavioural assumptions.

The five chapters in Part I will help the reader achieve an understanding of

the relevance of these models from different perspectives. Chapter 1, by

Federico Pierobon, deals with the analysis performed by the European

Central Bank (ECB) within interest rate risk in the banking book (IRRBB)

stress tests on banks’ recourse to behavioural models in their ALM, with a

specific focus on NMDs, prepayment and non-performing exposure. In

Chapter 2, Enrique Benito then reviews the main aspects of the standards

issued by Basel Committee on Banking Supervision (BCBS) and European

Bank Authority (EBA) relating to behavioural models together with key

implementation challenges.

In Chapter 3, Roberto Virreira describes the role of behavioural modelling

in organisational and strategic processes, addressing the organisational

arrangements, roles and challenges for the stakeholders of these models, as

well as showing how technological advances and regulatory trends demand a

review of current paradigms. This is followed by Chapter 4 by Daniel

Almehed, which explains how to set up governance rules on behavioural

models to ensure that the bank has in place the organisational structures,

procedures and responsibilities to identify, develop, operate and monitor the

behavioural models considering specific challenges. Furthermore, it

exemplifies how these can be addressed.

Chapter 5 closes this section with Jacek Rzeznik ´ introducing some of the

metrics employed by banks to measure the interest rate risk arising from nontrading

book activities (IRRBB) and the role played by behavioural models.

It shows how the measurement of IRRBB is heavily dependent on the

modelling behaviour of products/clients.

Part II on NMDs behavioural models will help the reader to comprehend

the details of existing modelling and also some new approaches. In Chapter

6, the Editors describe a framework that can be useful for developing any

NMD behavioural models, one that is composed of six principles to help

different stakeholders (treasurer, ALM manager, risk manager, auditor

business manager) to better understand the pros and cons of the modelling

approach and related outcomes. Moreover, it will assist the developer to



make the necessary checks for a proper definition, development and

implementation of the model when it is used for liquidity risk, interest rate

risk and business purposes.

Chapter 7, by Serena Di Rienzo, then reviews the literature on the two

main approaches – the economic value and the replicating portfolio

framework – which differ in both methodology and objective. The key

difference is their perspective, since the first aims to determine the economic

value of NMDs to allow a proper valuation of the risk and hedging of the

position, while the second is focused on the creation of a risk-balanced and

profitable investment strategy using NMDs.

In Chapter 8, Andreas Blöchlinger describes one of the first econometric

models that is useful from marketing to the hedging strategy. It develops a

coherent framework for NMDs, including the evolution of interest rates,

bank’s pricing behaviour, and customers’ withdrawal and prepayment

behaviour to derive a hedging strategy that generates a stable net interest

income. Chapter 9, by Rosa Cocozza, Domenico Curcio and Igor

Gianfrancesco, then describes a simple econometric model for the purpose of

managing interest rate risk. It shows how the NMDs volume can be easily

modelled into the regulatory time bands used in the maturity ladder, and the

pass-through of the bank can be estimated using a well-known econometric

technique.

Francesco Frascarelli and Vanessa Pagliaccia illustrate in Chapter 10 an

advanced econometric model that considers the customer’s demand for

money, composed by NMDs and other types of financial wealth whose

allocation depends on the financial markets. The model integrates customers’

asset allocation with the dynamics of the financial markets with the purpose

of forecasting both the liquidity and interest rate risk position. Chapter 11, by

Antonio Castagna, Antonio Scaravaggi and Bernardo Rapagnetta, then

presents an application of a stochastic risk factor model that integrates the

liquidity, profitability and interest rate risk. The model was calibrated to

artificial data to show that the heterogeneity of the NMDs dynamics and

customer’s behaviour can be modelled using this unique framework.

In Chapter 12, Bogusz Stankiewicz describes an empirical application of

how an NMD behavioural model can be used by banks’ marketing

departments. In particular, the model provides an understanding of how

modelling can contribute to an increase in business value. Following that,

Chapter 13 by Marco Palumbo presents a step-by-step approach for



validating NMDs behavioural models, an activity that is required by EBA

regulation to ensure that economic assumptions are correctly modelled,

backtested and benchmarked with alternative models. Chapter 14, by Matteo

Formenti, then examines the choice of setting the maturity profile of any

NMD behavioural model. This choice is more of a strategic view, and is

usually the responsibility of the asset/liability committee. The simple

approach presented allows the maturity to be coherent with the banks’ risk

appetite and to manage the interest rate risk position in a dynamic interest

rate environment.

This part closes with Chapter 15, by David Green, which assesses the use

of NMDs in the internal funds transfer pricing (FTP) framework. In

particular, it explains how interest rate risk and liquidity risk, which are

innate to every levered financial institution, create a profitability management

problem that can only be solved by a comprehensive and well-functioning

FTP and behavioural model.

Part III, on prepayment behavioural models, provides a detailed overview

of the most common modelling assumptions. It starts with a chapter by

Pierluigi Coriazzi and Lisa Signani that shows how prepayment risk affects

both fixed and floating rate loans and especially retail loans, and that market

efficiency theory can be of limited use in the assessment of prepayment

phenomena. In this context, a prepayment model was developed beginning

from the dependence of prepayment speed from the seasoning of the loan

within the survival analysis framework. The chapter illustrates the main

features of the prepayment model, the leading characteristics of survival data,

the variables used to represent refinance incentives and the estimation

methods. Moreover, it illustrates an empirical application of the model to a

sample of data, and how the model can be used in the ALM and finance

context and to evaluate the option-adjusted spread.

Chapter 17, by Roberto Baccaglini, illustrates a prepayment modelling

particularly suited for the retail loans segment where the borrower is not fully

rational and prepayment phenomenon is not influenced by concentration

effects that may affect the corporate loans segment. The approach belongs to

the framework of generalised linear models in which a linear predictor is

assumed to be equal, on average, to the probability of prepayment by means

of an appropriate link function. It is also relatively simple from a

methodological point of view and efficient from a computational perspective.

In Chapter 18, Matteo Formenti and Mattia Rossi present a prepayment


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