Mortgage Arrears, Strategic Default and Repossessions

Mortgage Arrears,
Strategic Default and
Repossessions
Notes on the mortgage arrears, negative equity,
causes of strategic defaults and the rate of
repossession of properties whose mortgages are in
arrears
Alan McSweeney
http://ie.linkedin.com/in/alanmcsweeney

Mortgage Arrears, Default and Repossessions
Page 2
Contents
Introduction.......................................................................................................................................... 2
What is Strategic Mortgage Default? ..................................................................................................... 4
Sources of Mortgages and Their Defaults ............................................................................................... 4
Irish Mortgage Data Sources.................................................................................................................. 5
Strategic Default Analysis Material ....................................................................................................... 6
Predictors of Mortgage Arrears and Strategic Default ............................................................................ 6
House Price Data Notes....................................................................................................................... 11
Legislative and Other Interventions in the Mortgage Market ............................................................... 13
Central Bank of Ireland Restructured Mortgages and Mortgages in Arrears Not Restructured ............. 16
Repossessions ...................................................................................................................................... 21
Local Authority Mortgage Defaults ..................................................................................................... 23
Mortgage Arrears Cohort Analysis ....................................................................................................... 30
IFRS 9, Non-Performing Loans and Repossessions .............................................................................. 33
Summary............................................................................................................................................. 34
Summary
Arrears in mortgages appear to be closely correlated with the amount of negative
equity.
In the last 10 years, there have been many legal and regulatory interventions that
have affected the way in which properties whose mortgages are in arrears can be
repossessed. The repossession route is still long, slow and expensive. Two thirds of
mortgages in arrears have not been subject to any form of restructuring.
The rate of and thus the risk of repossessions is extremely low. The correlation
between the number of arrears and the number of repossessions is very low.
IFRS 9 will cause banks to sell non-performing loans in bulk rather than
attempting the time-consuming and expensive process of trying to engage with a
core of non-engagers that have been in arrears for some time.
A very high proportion of Local Authority mortgages are in arrears. Many of these
arrears are more than 20 years old.

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Introduction
These notes are a macro-level analysis of the issues of mortgage default and repossessions.
In February 2018, the Central Bank of Ireland published a paper 1RT18 The Impact of Repossession
Risk on Mortgage Default (https://www.centralbank.ie/docs/default-source/publications/research-
technical-papers/1rt18-the-impact-of-repossession-risk-on-mortgage-default-(o%27malley).pdf).
The objectives of this Central Bank of Ireland paper were:
This paper evaluates the claim that reducing repossession risk for homeowners leads to an
increase in mortgage default. Economic theory predicts that borrowers will be more likely to
default on their mortgages if their homes cannot be repossessed. After the financial crisis,
commentators frequently cited the lack of repercussions as one of the contributing reasons
for high mortgage arrears in Ireland.
I evaluate this claim by examining how mortgage arrears evolved during the recent "Dunne
judgment" period in Ireland. The legal judgment effectively removed the ability of banks to
repossess homes in the event of mortgage default. The terms of the judicial decision meant
that nearly every mortgaged household in the country could no longer lawfully have their
homes repossessed from mid-2011 to 2013. Crucially for the analysis in this paper, a group of
mortgaged households experienced no change in their repossession risk: they were exempt
from the ruling of Justice Dunne. This aspect of the ruling allows to me to conduct a quasi-
experimental evaluation of the impact of removing repossession risk on mortgage default:
default rates for borrowers who had their repossession risk removed are compared to similar
borrowers who experienced no change in the repossession regime in the event of default.
Though not the ultimate cause of the arrears crisis, I find that the removal of repossession
risk led to an immediate increase in mortgage default for affected borrowers. Borrowers
experiencing very low or negative levels of home equity are the most likely to default in
response to the removal of repossession risk. However, this notion of purely strategic default
is moderated by evidence that these "strategic defaulters" were also more likely to be in
financial difficulty before the ruling. They were more likely to have missed a payment before
the Dunne judgment, have lower incomes and also face higher interest rates on their
mortgages.
Policy implications are straightforward. Impediments to home repossession by banks reduce
a borrower’s incentive to fulfil the terms of their mortgage. While a policy aiming to reduce
repossession risk may benefit borrowers, it would also increase the mortgage default rate.
When considering changes to repossession law, policy-makers must trade off the benefits
from lower home repossessions with the moral hazard cost I have identified in this work.
These notes contain some comments on this paper. They examine mortgage data from a wider range of
sources that did the Central Bank to assess what are the determinants of strategic mortgage default.
They also look at the wider range of legal and regulatory interventions that may have affected the issue
of repossessions than were considered by the Central Bank.
These notes are just a very minor contribution to the wide range of analyses on this subject

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What is Strategic Mortgage Default?
Strategic default is a very emotive topic. It is difficult to have a rational conversation about it. Media
coverage tends to vary considerably and inconsistently.
Strategic default also has different meanings and results in different outcomes in different jurisdictions.
So an Irish definition should be agreed initially. In my view, strategic default happens when a borrower
decides to stop making repayments on a loan even though the borrower has the financial ability and
resources to make the payments (won’t pay rather than can’t pay). This can be temporary or
permanent. It can be in pursuit of a short-term gain or a part of a longer-term strategy to have some or
all of the loan or accumulated arrears or both written off.
For a borrower to stop repaying a mortgage deliberately there would have to be a set of circumstances
where the probability of the borrower suffering negative consequences from their actions would be low.
This can happen in circumstances where some or all of the following apply:
 Where the lender has no recourse on the mortgage loan other than the property
 Where if the lender takes charge of the collateral they amount they recover is substantially less than
the loan amount
 Where the process for the lender to recover the arrears or enforce a penalty or recover the underlying
collateral is slow, complex, expensive or difficult
 Where the lender feels that the value of the property will increase over time so waiting will increase
the amount recovered
 Where the lender will suffer a disadvantage by repossessing and selling the property and having to
crystallise the loss on their balance sheet
Sources of Mortgages and Their Defaults
There are three sources of residential mortgage lending in Ireland:
1 Regulated financial institutions such as retail banks and mortgage lenders
2 Local authorities
3 Credit unions
The breakdown in outstanding mortgage balances across these sectors is:

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The values for regulated financial institutions include PDH (Primary Dwelling House) and BTL (Buy-
To-Let). The balance amounts are in millions.
These numbers exclude commercial residential property lending.
Different types of strategic default may occur for each of these three lender types, depending on factors
such as the assertiveness stance of the lender in relation to pursuing arrears.
The Central Bank paper looked at the effect of repossessions on the PDH area.
Irish Mortgage Data Sources
Public mortgage arrears, house price and related data are available from multiple sources such as:
 Department of the Environment - http://www.housing.gov.ie/search/sub-topic/house-prices-loans-
and-profile-borrowers
 CSO -
http://www.cso.ie/px/pxeirestat/Database/eirestat/House%20Prices/House%20Prices_statbank.asp
 Central Bank - https://www.centralbank.ie/statistics/data-and-analysis/credit-and-banking-
statistics/mortgage-arrears
 BPFI - https://www.bpfi.ie/publications/bpfi-mortgage-drawdowns/
The problems with this publically available data are:
 It is at a high level and not very detailed or granular
 The start and end dates of the time series are not consistent
 The data intervals are not consistent across the time series with some series containing monthly data
and others quarterly
 The level of detail is inconsistent – national, regional, property type, property age
So combining the data requires that it be done at the highest common denominator which tends to be
national data for all property types for new and second hand properties quarterly.

Page 6
Detailed mortgage data is available privately to financial regulators and to individual financial
institutions that can perform detailed analyses. This data is not available publically.
Strategic Default Analysis Material
There is much excellent material available on the subject of strategic default, both in Ireland and
elsewhere, of which the following is a very small subset:
Irish Mortgage Default Optionality, Economics, Finance and Accounting Department Working
Paper Series n243-13.pdf, Department of Economics, Finance and Accounting, National
University of Ireland – Maynooth - http://repec.maynoothuniversity.ie/mayecw-files/N243-13.pdf
Moral and Social Constraints to Strategic Default on Mortgages -
http://www.financialtrustindex.org/images/Guiso_Sapienza_Zingales_StrategicDefault.pdf
Recourse and Residential Mortgage. Default: Theory and Evidence from. U.S. States. WP 09-10R
-
https://www.richmondfed.org/~/media/richmondfedorg/publications/research/working_papers/200
9/pdf/wp09-10r.pdf
Mortgage Modification and Strategic Behavior: Evidence from a Legal Settlement with
Countrywide -
https://chicagounbound.uchicago.edu/cgi/viewcontent.cgi?referer=https://www.google.ie/&httpsre
dir=1&article=1003&context=housing_law_and_policy
Can't Pay or Won't Pay? Unemployment, Negative Equity, and Strategic Default Can't Pay or
Won't Pay? Unemployment, Negative Equity, and Strategic Default -
https://www.bostonfed.org/publications/research-department-working-paper/2015/cant-pay-or-
wont-pay-unemployment-negative-equity-and-strategic-default.aspx
Mortgage Modifications after the Great Recession New Evidence and Implications for Policy -
https://www.jpmorganchase.com/corporate/institute/document/institute-mortgage-debt-
reduction.pdf
The Effect of Debt on Default and Consumption: Evidence from Housing Policy in the Great
Recession - https://scholar.harvard.edu/files/noel/files/ganong_noel_housing_2017-12-16.pdf
Resolving a Non-Performing Loan crisis: The ongoing case of the Irish mortgage market -
https://www.centralbank.ie/docs/default-source/publications/research-technical-papers/10rt17---
resolving-a-non-performing-loan-crisis-the-ongoing-case-of-the-irish-mortgage-market.pdf
Some defaults are deeper than others Understanding long-term mortgage arrears -
https://www.centralbank.ie/docs/default-source/publications/research-technical-papers/research-
technical-paper-05rt15.pdf
Predictors of Mortgage Arrears and Strategic Default
It is possible to do some very simple analysis with the limited set of publically available information to
determine the likely predictors of strategic default.

Page 7
This table below combines data from:
Department of the Environment
Quarterly Average Second Hand Property Price by
Area http://www.housing.gov.ie/sites/default/files/publications/files/form_41d-price-sh-property-
area-by-qtr_1.csv
National New House Prices by agency - by quarter
http://www.housing.gov.ie/sites/default/files/publications/files/form_42f-agency-new-house-price-
by-qtr_1.csv
CSO
HPM06 Residential Property Price Index by Month, Type of Residential Property and
Statistic http://www.cso.ie/px/pxeirestat/Statire/SelectVarVal/Define.asp?maintable=HPM06&P
Language=0
Central Bank
Residential Mortgage Arrears and Repossession Statistics: Data
https://www.centralbank.ie/docs/default-source/statistics/data-and-analysis/credit-and-banking-
statistics/mortgage-arrears/mortgage-arrears-data/moa-data.xlsx
This data applies to residential data for Primary Dwelling House (PDH) mortgages rather than Buy To
Let mortgages.
The last interval for which all data is available is 2016Q1. I converted monthly data to quarters by a
simple average rather than a more complex interpolation.
The Estimated Positive/ Negative Equity is derived by the difference between the CSO House Price
Index for the quarter relative to 2016Q1 multiplied by the average property price for that quarter taken
from the original property price,
So a property bought in 2005Q1 for €298,986 has a notional value of 0.8236 times its original price in
2016Q1 (CSO index at 2016Q1 82.97 / divided by CSO index at 2005Q1 100.73) or €246,245. This
represents an estimated negative equity of €52,741.
This is a rather artificial value.
The calculations of this are:
Interval Average New and
Second Hand Home
Price Nationally
CSO House Price
Index
CSO House Price
Index Relative to
2016Q1
Estimated Positive/
Negative Equity
Central Bank PDH
Arrears Number
2005Q1 €298,986 100.73 0.8236 -€50,206
2005Q2 €323,921 102.87 0.8065 -€58,766
2005Q3 €320,316 106.87 0.7764 -€67,504
2005Q4 €342,193 111.57 0.7437 -€81,860
2006Q1 €340,765 113.60 0.7303 -€86,719
2006Q2 €368,758 118.10 0.7025 -€102,234
2006Q3 €378,175 125.20 0.6627 -€117,909

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Interval Average New and
Second Hand Home
Price Nationally
CSO House Price
Index
CSO House Price
Index Relative to
2016Q1
Estimated Positive/
Negative Equity
Central Bank PDH
Arrears Number
2006Q4 €366,516 127.93 0.6485 -€121,028
2007Q1 €371,333 130.17 0.6374 -€127,067
2007Q2 €379,008 130.63 0.6351 -€131,166
2007Q3 €366,391 130.47 0.6359 -€126,263
2007Q4 €359,288 129.73 0.6395 -€122,789
2008Q1 €352,293 127.00 0.6533 -€116,219
2008Q2 €350,409 123.53 0.6716 -€110,061
2008Q3 €330,820 120.23 0.6900 -€98,788
2008Q4 €317,416 114.07 0.7274 -€82,536
2009Q1 €291,166 106.07 0.7822 -€60,145
2009Q2 €280,331 98.77 0.8400 -€42,252
2009Q3 €251,627 94.67 0.8764 -€30,153 63,619
2009Q4 €242,044 92.47 0.8973 -€24,205 69,647
2010Q1 €244,447 89.30 0.9291 -€16,801 76,100
2010Q2 €272,153 86.27 0.9617 -€9,691 82,377
2010Q3 €273,145 83.73 0.9908 -€2,340 86,362
2010Q4 €266,387 80.07 1.0362 €9,094 89,234
2011Q1 €269,965 76.40 1.0860 €22,197 94,518
2011Q2 €268,989 72.47 1.1449 €36,760 102,397
2011Q3 €249,696 68.13 1.2177 €52,239 110,597
2011Q4 €243,668 64.33 1.2896 €68,338 118,464
2012Q1 €243,558 61.47 1.3498 €81,130 122,941
2012Q2 €248,271 60.03 1.3820 €91,528 128,197
2012Q3 €247,499 60.73 1.3661 €86,596 141,389
2012Q4 €240,357 61.23 1.3549 €81,839 139,224
2013Q1 €242,233 59.47 1.3952 €92,954 142,118
2013Q2 €254,868 59.50 1.3944 €95,535 142,892
2013Q3 €253,732 62.87 1.3197 €78,250 141,269
2013Q4 €253,627 64.67 1.2830 €69,116 136,558
2014Q1 €250,369 65.70 1.2628 €64,024 132,217
2014Q2 €266,782 69.37 1.1961 €50,281 126,005
2014Q3 €261,930 74.97 1.1067 €27,308 117,889
2014Q4 €256,397 77.30 1.0733 €18,875 110,366
2015Q1 €260,564 77.20 1.0747 €19,679 104,693
2015Q2 €268,012 78.93 1.0511 €13,848 98,155
2015Q3 €270,065 81.47 1.0184 €5,087 92,361
2015Q4 €268,682 82.67 1.0036 €1,020 88,292
2016Q1 €270,848 82.97 1.0000 €0 85,989
2016Q2 83.90 82,091
2016Q3 87.53 79,562
2016Q4 89.73 77,493
2017Q1 90.77 76,422
2017Q2 92.77 73,706
2017Q3 97.83 72,489
2017Q4 100.37 70,488
2018Q1 101.97
This is fairly crude. National property prices for all property types and ages are used.
This is also a one-dimensional view of estimated negative equity.

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Also, the estimate of negative equity is effectively a proxy for (1 - CSO House Price Index). This in turn
is a proxy for overall economic circumstances. So the correlation could be viewed as being between
number of arrears and the state of the economy. Falling property prices are a consequence of a generally
falling economy. The apparent link between mortgage default and negative equity may therefore not be
strictly causal but indicative of a shared third common factor of general economic conditions.
The following chart shows the number of PDH arrears on the left vertical axis mapped against the
estimated negative equity on the right vertical axis. Negative equity is estimated with respect to 2016Q1.
A positive value for negative equity means the property has an estimated negative equity. A negative
value indicates an estimated positive equity.
There certainly appears to be a relationship between the number of arrears and the estimated negative
equity, Simple measures of correlation such as the correlation coefficient or R2 (which is just the square
of the correlation coefficient) yield values such as 0.956 and 0.914.
However, it is more than possible that this correlation is an example of spurious regression in two
time series where there is no causal relationship between the two series but each are related to a common
third series such as the overall economy. There are complex methods for determining if a statistical
relationship is due to spurious regression. These are outside the scope of these notes.
The following shows Ireland’s GDP and GDP and the unemployment rate from 2017Q1.

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These measures all have their issues. GDP and GNP arte distorted by the effect of multi-nationals.
The rate of unemployment is affected by the various activation and education programmes and the
number being allocated to disability payments. The unemployment rate, being a proportion of the
employable population, will also be affected by emigration that increased during the financial crisis that
decreased the size of the employable population.
It is possible to attempt to correct for these factors. The adjustment would be complicated by factors
such as those who emigrated would be less likely to be mortgage holders and therefore less likely to be in
mortgage arrears. This is outside the scope of these notes.
The following chart tracks the unemployment rate shown in red on the right hand axis with the number
of arrears shown in blue on the left axis. At best, it could be said that any relationship indicates that the
increase in the number of arrears tracked the increase in the unemployment rate at a lag of 2 or more
years.

Page 11
House Price Data Notes
The Department of the Environment published quarterly property price data for both new and second-
hand properties at the links listed above. New property prices are available separately from 1975.
Second-hand property prices are available separately from 1978.
The CSO retrospectively published new and second-hand monthly property price data from 2010 in the
time series HPM02 Residential Dwelling Property Transactions by County, Dwelling Status, Stamp
Duty Event, Type of Buyer, Type of Sale, Month and Statistic
http://www.cso.ie/px/pxeirestat/Statire/SelectVarVal/Define.asp?maintable=HPM02&PLanguage=0.
These two sets of property price data do not agree. The following table shows the two data sets with the
CSO monthly price average averaged over the quarter.
Quarter Department of the
Environment New
Department of the
Environment
Second Hand
CSO New CSO Second Hand
2010Q1 €226,245 €247,534 €244,210 €190,959
2010Q2 €226,833 €279,839 €212,800 €190,392
2010Q3 €230,868 €280,315 €219,423 €194,841
2010Q4 €229,531 €272,638 €210,309 €161,716
2011Q1 €241,749 €274,750 €202,256 €167,053
2011Q2 €232,174 €275,233 €189,240 €160,220
2011Q3 €226,215 €253,678 €188,864 €168,737
2011Q4 €225,067 €246,823 €169,002 €144,800
2012Q1 €215,587 €248,302 €185,498 €141,736
2012Q2 €227,376 €251,815 €179,850 €141,129
2012Q3 €221,123 €251,972 €184,619 €167,139
2012Q4 €216,810 €244,350 €166,451 €152,757
2013Q1 €225,340 €245,098 €151,251 €151,637
2013Q2 €224,432 €260,030 €172,018 €155,931
2013Q3 €232,083 €257,404 €176,995 €172,730
2013Q4 €231,011 €257,462 €165,410 €182,428
2014Q1 €234,098 €253,128 €172,858 €159,719
2014Q2 €241,912 €271,000 €172,639 €178,620
2014Q3 €247,398 €264,394 €199,967 €205,165
2014Q4 €258,989 €255,958 €210,472 €188,278
2015Q1 €267,517 €259,385 €195,888 €189,604
2015Q2 €275,235 €266,787 €206,389 €183,984
2015Q3 €285,015 €267,530 €234,526 €202,021
2015Q4 €298,551 €263,616 €253,016 €193,636
2016Q1 €309,703 €264,258 €267,172 €197,551
2016Q2 €273,188 €200,899
2016Q3 €282,714 €216,816
2016Q4 €298,384 €212,193
2017Q1 €299,364 €214,622
2017Q2 €309,452 €216,723
2017Q3 €315,823 €234,758
2017Q4 €325,086 €232,367
2018Q1 €343,541 €228,941
The following chart shows this information visually.

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The CSO prices are significantly lower than those published by the Department of the Environment.
It is outside the scope of these notes to reconcile these differences.
The Central Bank of Ireland also changed historical data in their arrears time series without any
notification or explanation. The following table lists differences between the data published in
September 2017 and December 2017.
Mar-17 Jun-17 Sep-17
Number Balance
€ (000)
Arrears
€ (000)
Number Balance
€ (000)
Arrears
€ (000)
Number Balance
€ (000)
Arrears
€ (000)
Total outstanding classified as
restructured - at end of quarter
-95 -18,571 -675 -26 -7,570 -448 -19 -6,704 -546
Interest Only
Interest Only - up to one year
Interest Only - over one year -4 -760 -9 -3 -431 -14 -3 -424 -14
Reduced Payment (less than
interest only)
-51 -9,994 -930 -18 -3,889 -289 -7 -1,654 -262
Reduced Payment (greater than
interest only)
Term Extension
Arrears Capitalisation -118 -16,495 202 -117 -18,012 -388 -133 -21,266 -588
Payment Moratorium
Deferred Interest Scheme
Split Mortgage -52 5 -58 8 -58 9
Permanent Interest Rate
Reduction
-81 -13,991 -239 -70 -12,065 -125 -73 -12,584 -151
Temporary Interest Rate
Reduction
Trade Down Mortgages
Other 159 22,721 296 182 26,885 360 197 29,282 460
of which are not in arrears 1 -3,136 16 -189 31 1,387

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Legislative and Other Interventions in the Mortgage Market
The intent of the Central Bank of Ireland paper was to determine the impact, if any the Dunne
Judgment had on repossessions. This was singled-out because of its apparent effect of freezing
repossessions because of the uncertainty it introduced
However, there have been many legislative, regulatory and other administrative interventions into the
mortgage market during the interval of the financial crash. Any analysis of repossessions should look at
the range of these interventions in their entirety to attempt to determine their impact on mortgage
default behaviour.
These legislative interventions were:
 Land and Conveyancing Law Reform Act 2009
(http://www.irishstatutebook.ie/eli/2009/act/27/enacted/en/html) enacted on 1 Dec 2009 – S.I. No.
356/2009 - Land and Conveyancing Law Reform Act 2009 (Commencement) Order 2009
(http://www.irishstatutebook.ie/eli/2009/si/356/made/en/print)
 November 2010 Cooney Report - Irish Expert Group on Mortgage Arrears and Personal Debt. The
Cooney Report introduced the Central Bank MARP process.
 January 2011 Central Bank of Ireland Mortgage Arrears Resolution Process (MARP)
https://www.centralbank.ie/docs/default-source/Regulation/consumer-protection/other-codes-of-
conduct/24-gns-4-2-7-2013-ccma.pdf
 September 2011 Inter-Departmental Mortgage Arrears Working Group
http://www.finance.gov.ie/wp-content/uploads/2017/08/170828-Keane-Report-30-September-
2011.pdf
 July 2013 Central Bank of Ireland Code of Conduct on Mortgage Arrears (CCMA)
https://www.centralbank.ie/docs/default-source/Regulation/consumer-protection/other-codes-of-
conduct/24-gns-4-2-7-2013-ccma.pdf
 Start Mortgages & Ors v Gunn & Ors – the Dunne Judgment
http://www.courts.ie/judgments.nsf/6681dee4565ecf2c80256e7e0052005b/89f3e895ac665956802578da
002fcd0e?OpenDocument&Highlight=0,Gunn – 25 July 2011
 Land and Conveyancing Law Reform Act 2013
(http://www.irishstatutebook.ie/eli/2013/act/30/enacted/en/html) enacted on 31 Jul 2013 - S.I. No.
289/2013 - Land and Conveyancing Law Reform Act 2013 (Commencement) Order 2013
(http://www.irishstatutebook.ie/eli/2013/si/289/made/en/print)
 December 2013 Report of the Expert Group on Repossessions -
http://www.justice.ie/en/JELR/ExpGroupReportFinal.pdf/Files/ExpGroupReportFinal.pdf
There was also the Personal Insolvency Act, 2012
http://www.irishstatutebook.ie/eli/2012/act/44/enacted/en/html which had an effect on how arrears were
handled. Elements of this Act came into effect on different times:

Page 14
 1 Mar 2013 - S.I. No. 63/2013 - Personal Insolvency Act 2012 (Commencement) (No. 2) Order 2013
http://www.irishstatutebook.ie/eli/2013/si/63/made/en/print
 18 Jan 2013 - S.I. No. 14/2013 - Personal Insolvency Act 2012 (Part 6) (Commencement) Order 2013
 31 July 2013 S.I. No. 285/2013 - Personal Insolvency Act 2012 (Commencement) (No. 3) Order 2013
 Dec 2013 S.I. No. 462/2013 - Personal Insolvency Act 2012 (Part 4) (Commencement) Order 2013
Any analysis of the effects of external legal interventions on arrears and on repossessions should look at
the relatively active legal and regulatory landscape over the 8 year interval being analysed.
It would be difficult to determine the impact of a single intervention in the context of these series of
interventions that introduced doubt and uncertainty into the repossession process.
The following overlays the times of some of these key legislative interventions that may have affected
mortgage arrears on the original mortgage arrears and negative equity data.
What we are trying to analyse and estimate here is whether borrowers in arrears change their behaviour
in response to external positive or negative incentives.
So, is negative equity a predictor of arrears and thus an indicator of strategic default or do the two share
a common third cause?
Can the mortgage holders in market be segmented into a number of groups, such as:

Page 15
 Those who will resume paying their mortgage when they are able to do so
 Those who resume paying their mortgage when the negative equity is such they see a benefit in
paying to retain the asset
 Those who do not resume paying their mortgage because they see they do not see any consequences
to not paying
Intuitively, the size of the negative equity could lead to a decision on behalf of the borrower to stop
repaying the loan because the underlying asset has not value and a view that they are only throwing
good money after bad. When the borrower stops making loan repayments, the property cannot be sold.
This would be accompanied by a view from the lender that repossession of a poor quality distressed asset
would lead to them having to recognise their losses after selling the recovered property at a significant
loss and a view from the borrower that this is also the case.
This would then be combined with a complex, lengthy, cost and uncertain repossession process that acts
as a barrier to repossessions.
Conversely, when the negative equity falls, the borrower is more likely to make repayments because the
load to value ratio is reduced. The borrower may be more inclined to accept a small loss when selling the
property in order to be able to more to a more desirable property. The borrower may also perceive that
the lender is more likely to seek repossession as the loss they would have to accept is reduced.
This intuitive insight may however be simplistic and is certainly speculative. As I said above, the
estimated negative equity amount is simply a proxy for (1 - CSO House Price Index).
By way of comparison, this chart shows the Department of Environment national new and second hand
property price mapped against the CSO national House Price Index, shown on the right vertical axis.
The divergence in the average price of new and second-hand property is an interesting, if minor,
secondary observation.
The following shows the two dimensional view of the progress of average estimated national negative
equity for domestic property bought in any quarter at all subsequent quarters. It really demonstrates
the massive trough of negative equity that occurred at the depth of the financial crisis.

Page 16
Central Bank of Ireland Restructured Mortgages and Mortgages in Arrears Not
Restructured
The PDH arrears statistics https://www.centralbank.ie/statistics/data-and-analysis/credit-and-banking-
statistics/mortgage-arrears contains the following rows:
A Total mortgage arrears cases outstanding - at end of quarter which are:

Page 17
B Total outstanding classified as restructured - at end of quarter
C of which are not in arrears
So the number of mortgages that are in arrears and have been restructured is B – C.
The number of mortgages that are in arrears and have not been restructured is A – B + C.
The following table shows the calculations for the last five quarters:
Classification Dec-16 Mar-17 Jun-17 Sep-17 Dec-17
Total Residential Mortgage Loan Accounts
Outstanding
736,894 734,106 732,439 731,119 729,722
Total Mortgage Arrears Cases Outstanding 77,493 76,422 73,706 72,489 70,488
Total Outstanding Classified As Restructured 120,944 120,641 120,047 119,051 118,477
Restructured Not In Arrears 94,441 94,335 94,656 94,012 92,999
In Arrears Restructured 26,503 26,306 25,391 25,039 25,478
In Arrears Not Restructured 50,990 50,116 48,315 47,450 45,010
Total Mortgage Arrears Cases Outstanding % 10.52% 10.41% 10.06% 9.91% 9.66%
In Arrears Not Restructured % 65.80% 65.58% 65.55% 65.46% 63.85%
From this, the following can be seen:
 A large number of mortgages have been restructured without being classified as being in arrears:
 A much smaller number of mortgages that are in arrears have been restructured
 A larger number of mortgages in arrears have not been restructured - nearly twice the number that
are in arrears and have been restructured
This chart profiles the numbers of mortgages to which various types of restructuring have been applied
over time:

Page 18
It also shows the number restructured mortgages. The number of restructured mortgages reached a peak
in September 2015 and has remained roughly at this level since then.
The key trends in the type of restructuring arrangement are isolated in the following chart:
These key trends are:
 Split Mortgage increased to the current position where they account for nearly one quarter of
restructuring arrangements
 Arrears Capitalisation now account for one third of arrangements
 Reduced Payment (Greater Than Interest Only) have fallen to less than 5% of arrangements
 Reduced Payment (Less Than Interest Only) have fallen to less than 0,5% of arrangements
 Interest Only - Up To One Year have fallen to less than 1,5% of arrangements
This chart profiles the balances of mortgages to which various types of restructuring have been applied
over time:

Page 19
It also shows the balance of the restructured mortgages. The balance of restructured mortgages reached
a peak in September 2015 and has been dropping since then.
The following chart contains a profile of the numbers of mortgages in arrears that have been
restructured and those that have not.
Roughly two thirds of mortgages in arrears have not been and have never been restructured.
The following chart contains a profile of the balance of mortgages in arrears that have been restructured
and those that have not. The vertical axis amounts are in thousands.

Page 20
Again, roughly two thirds of mortgages balances in arrears have not been restructured. This shows a
residual high-level of non-engaged or not-engaged mortgages in arrears.
The following chart shows the proportions of arrears that have been restructured and not restructured
over the interval:

Page 21
This illustrates the substantial number of mortgages in arrears have yet to be restructured. This points
to a core of non-engaging mortgage holders who are in arrears.
Repossessions
The following chart shows the percentage of mortgages in arrears and the number of repossessions per
quarter as a percentage of mortgages in arrears.
This chart shows the number of repossessions – those as a result of a legal process and those voluntarily
surrendered – on the right vertical axis and the number of mortgages in arrears. It also overlays the
dates of legal interventions listed above to provide a context for any changes.

Page 22
Intuitively, the legal interventions do not appear to have impacted repossessions.
This may not be the complete picture. It may be that the various legal interventions caused repossession
legal cases in progress to be abandoned. It may have been that financial institutions were preparing to
initiate greater volumes of repossessions and that the Dunne judgement and other interventions caused
them to stop this activity.
However this speculation cannot be verified. The low rate of repossessions, particularly those on foot of
legal action are so very low.
The following chart overlays the previous chart with an estimated linear extrapolation of the Legal
Repossession values from the intervals Sep 09 to Sep 11 for the intervals before the Dunne judgement
occurred to the later intervals Dec 11 to Jun 13.

Page 23
The rate of repossessions is very low. The risk of involuntary repossession is very low.
The total number of PDH repossessions over the measured interval of over eight years is 8,506. Of these
2,860 repossessions occurred on foot of an order. The balance of 5,646 were voluntarily surrendered or
abandoned. The correlation between the number of arrears and the number of repossessions is very low.
Local Authority Mortgage Defaults
While Local Authority mortgage lending is not regulated by the Central Bank (or any other regulator), it
provides an interesting potential contrast to causes of arrears. The subject of Local Authority arrears
was not covered in the Central Bank paper.
Local Authority home loan statistics are available from
http://www.housing.gov.ie/housing/statistics/house-prices-loans-and-profile-borrowers/local-authority-
loan-activity.
The profile of PDH loan arrears in the latest home loan statistics for December 2017 produced by the
Central Bank at https://www.centralbank.ie/statistics/data-and-analysis/credit-and-banking-
statistics/mortgage-arrears is:
Number Balance Number %
Of Total
Value % Of
Total
Total Home Loans 729,722 €98,521,574,000
In Arrears Over 90 Days 48,433 €9,694,109,000 6.64% 9.84%
In Arrears Over 720 Days 28,946 €6,417,284,000 3.97% 6.51%
The similar arrears profile for the latest Local Authority home loans for Q4 2017 is:
Number Value Number %
Of Total
Value % Of
Total

Page 24
Total Home Loans 15,893 €913,370,742
In Arrears Over 90 Days 3,807 €400,867,568 23.95% 43.89%
In Arrears Over 720 Days 1,534 €76,234,873 9.65% 8.35%
The arrears data is in different formats over different intervals. The following table aggregates the
available data into a single view from Q1 2010 to Q3 2017. The blank cells are because of discontinuities
in the Local Authority home loan data. I have filled-in some of the blanks.
The arrears data is in different formats over different intervals. The following table aggregates the
available data into a single view from Q1 2010 to Q3 2017. The blank cells are because of discontinuities
in the Local Authority home loan data. I have filled-in some of the blanks.

Page 25
Year and
Quarter
Total Loan Book Loans In Arrears
Between 0 - 90 Days
Loans In Arrears
Between 90 - 180 Days
Loans In Arrears Over
180 Days
180-360 Days
360-720 Days
720 Days
Number Value € Average
Outstanding
Loan Amount
Number Value € Number Value € Number Value € Number Value € Number Value €
2010Q3 24,405 €1,345,610,918 €55,137 1,735 €54,358,247 4,325 €114,895,907
2010Q4 23,909 €1,316,137,267 €55,048 1,577 €56,666,806 4,488 €120,978,701
2011Q1 23,560 €1,304,652,037 €55,376 1,506 €49,503,439 4,501 €126,300,626
2011Q2 23,112 €1,290,622,536 €55,842 1,656 €60,956,340 4,541 €132,395,697
2011Q3 22,616 €1,277,119,336 €56,470 1,543 €62,702,965 4,656 €141,561,228
2011Q4 22,008 €1,263,112,738 €57,393 1,629 €66,727,283 4,715 €153,608,643
2012Q1 22,390 €1,261,818,255 €56,356 1,556 €64,930,329 4,759 €161,657,541
2012Q2 22,071 €1,246,408,605 €56,473 1,479 €60,413,426 4,801 €152,201,999
2012Q3 21,061 €1,236,974,251 €58,733 1,463 €59,437,595 4,870 €174,420,725
2012Q4 20,802 €1,226,067,605 €58,940 1,391 €58,781,758 4,919 €180,382,194
2013Q1 20,409 €1,212,398,496 €59,405 1,340 €55,658,799 4,975 €191,380,443
2013Q2 20,339 €1,203,272,046 €59,161 1,307 €54,285,309 4,968 €193,245,375
2013Q3 20,015 €1,189,764,959 €59,444 1,289 €51,994,280 4,921 €194,289,971
2013Q4 19,788 €1,177,152,139 €59,488 1,243 €52,194,614 4,892 €197,172,461
2014Q1 19,065 €1,161,007,843 €60,897 1,241 €50,236,833 4,774 €195,889,598
2014Q2 19,083 €1,141,160,222 €59,800 1,174 €47,437,069 4,749 €192,745,007
2014Q3 18,912 €1,126,834,181 €59,583 1,113 €45,952,435 4,714 €197,365,093
2014Q4 18,679 €1,108,323,965 €59,335 1,037 €42,862,988 4,631 €198,245,421
2015Q1 18,559 €1,098,248,646 €59,176 1,038 €57,726,874 4,494 €300,720,759 1,128 €74,497,753 1,184 €83,536,914 2,182 €142,685,592
2015Q2 18,364 €1,087,983,057 €59,245 995 €55,037,600 4,380 €299,543,884 1,078 €68,882,579 1,124 €82,222,507 2,178 €148,438,798
2015Q3 18,079 €1,070,892,303 €59,234 951 €52,688,282 4,261 €286,575,011 1,040 €63,030,660 1,110 €80,232,295 2,111 €143,312,057
2015Q4 17,845 €1,061,931,494 €59,509 892 €47,129,682 4,091 €281,477,264 1,003 €60,211,997 1,039 €73,656,948 2,049 €147,608,318
Q4 2015 17,992 €1,047,135,254 €58,200 3,476 €199,593,982 863 €48,014,763 3,776 €237,796,796 943 €56,887,485 995 €67,455,871 1,838 €113,453,440
Q1 2016 17,669 €1,028,012,545 €58,182 3,617 €204,791,379 935 €49,472,276 3,896 €231,120,410 942 €55,718,426 1,024 €62,387,189 1,930 €113,014,795
Q2 2016 17,411 €1,014,204,922 €58,251 3,323 €185,421,158 845 €43,378,856 3,741 €221,162,762 897 €51,853,886 978 €59,375,103 1,866 €109,933,773
Q3 2016 17,182 €993,443,770 €57,819 3,187 €176,770,253 820 €41,746,370 3,668 €208,526,260 877 €49,197,556 953 €56,961,879 1,838 €102,366,825
Q4 2016 16,884 €970,555,810 €57,484 3,336 €193,307,698 875 €44,645,924 3,497 €193,118,924 840 €47,320,923 924 €53,160,748 1,733 €92,637,254
Q1 2017 16,591 €953,660,780 €57,481 3,451 €202,843,304 818 €42,515,138 3,355 €183,303,815 801 €44,642,757 892 €51,092,998 1,662 €87,568,059
Q2 2017 16,352 €940,913,690 €57,541 3,398 €199,637,542 763 €37,560,638 3,266 €177,840,951 782 €43,777,973 866 €49,347,330 1,618 €84,715,649
Q3 2017 16,107 €924,553,638 €57,401 3,375 €199,007,989 761 €37,769,868 3,192 €170,945,610 768 €43,151,107 852 €47,542,445 1,572 €80,252,058

Page 26
In summary, the current amount of Local Authority home lending is €913.4 million. This compares to
the €146.3 million of Credit Unions home lending or over 6 times the value. However the total value of
Local Authority home lending is only 0.92% of the PDH home loan lending by retail banks. So it is still
relatively quite small. The proportion of the number of Local Authority mortgages In Arrears Over 90
Days is 3.6 times that of retail banks. The proportion of the value of mortgages In Arrears Over 90
Days is nearly 4.5 times that of retail banks.
The average outstanding loan amount for Local Authorities - €57,470 - when compared to retail banks -
€135,012.
The In Arrears Over 720 Days numbers for Local Authorities is over 2.4 times that of the retail banks.
It is possible that the different profile of borrowers availing of Local Authority loans will give rise to a
higher default rate because of a possible higher risk profile. But without more information, this is just an
unvalidated statement.
The available information is at a very gross level: not broken down by age of loan, original loan amount,
type of property and Local Authority.
Local Authorities have been effectively running-down their mortgage book. The rate of new home
lending is currently very low. So the relatively high-level of arrears should be assessed in the context of a
very old portfolio of loans and a very low rate of home lending since the late 1980s. The current 7,147
home loans in arrears would mean that nearly every loan issued since 1991 is in arrears. 7,685 new loans
were drawn-down since 2016.
This is clearly unlikely. So the profile of loans in arrears must include some loans that are in arrears must
be very old – 25 years and more.
When you include Local Authority loans in any arrears, the details are:
Year and Quarter Number of Loans Number Of All
Loans In Arrears
Number Of All
Loans In Arrears
As % Of The
Total Loan Book
Q4 2015 17,992 8,115 45.10%
Q1 2016 17,669 8,448 47.81%
Q2 2016 17,411 7,909 45.43%
Q3 2016 17,182 7,675 44.67%
Q4 2016 16,884 7,708 45.65%
Q1 2017 16,591 7,624 45.95%
Q2 2017 16,352 7,427 45.42%
Q3 2017 16,107 7,328 45.50%
Q4 2017 15,893 7,147 44.97%
The age profile of loans in arrears combined with the relatively small value of these loans would lead to
the reasonable inference that economic circumstances are not a major contributor to arrears.
This indicates a possible additional driver of loan arrears such as poor Local Authority lending and
collection practices combined with a belief that if a Local Authority property is repossessed the occupier
will have to be rehomed by the Local Authority.

Page 27
The following table aggregates Local Authority lending home lending by year and combines it with
overall lending and average national home price across all property types. This gross level of granularity
provides little detailed insight other than general trends. The figures are for loans approved and drawn-
down.
Year Local
Authority
Number of
Home
Loans
Approved
Local
Authority
Total
Value of
Home
Loans
Approved
€M
Local
Authority
Number of
Home
Loans
Paid
Local
Authority
Total
Value of
Home
Loans
Paid €M
Average
Local
Authority
Loan
Approved
Average
National
Home
Price
Local
Authority
Loan
Approval
% Of
Average
National
Home
Price
National
Total
Loans
Approved
National
Total
Value
Approved
€M
Local
Authority
% Of Total
Number Of
All Home
Loans
Local
Authority
% Of Total
Value Of
All Home
Loans
1976 5,113 26.5 6,732 32.1 €5,190 €15,564 33.35% 25,240 242.6 20.26% 10.94%
1977 5,884 39.1 5,021 23.9 €6,646 €18,754 35.44% 24,540 277.2 23.98% 14.11%
1978 8,370 72.0 5,697 41.1 €8,601 €24,082 35.72% 26,777 358.3 31.26% 20.09%
1979 8,950 91.5 6,943 63.4 €10,229 €29,387 34.81% 30,051 29.78% 19.30%
1980 10,381 132.2 7,998 88.8 €12,733 €34,967 36.41% 28,728 522.4 36.14% 25.30%
1981 8,971 135.4 7,826 121.3 €15,088 €40,167 37.56% 29,485 632.5 30.43% 21.40%
1982 7,595 123.2 8,126 125.8 €16,217 €44,060 36.81% 26,824 646.4 28.31% 19.05%
1983 5,333 87.4 6,150 98.8 €16,381 €44,448 36.85% 30,257 803.9 17.63% 10.87%
1984 4,959 87.1 5,365 88.4 €17,565 €45,419 38.67% 28,852 787.4 17.19% 11.06%
1985 5,046 95.4 5,135 91.3 €18,898 €46,542 40.60% 31,203 879.7 16.17% 10.84%
1986 6,646 146.7 5,444 108.1 €22,067 €48,256 45.73% 30,091 876.6 22.09% 16.73%
1987 7,186 128.0 8,299 186.0 €17,811 €48,151 36.99% 31,874 986.3 22.55% 12.98%
1988 2,062 45.1 4,444 78.1 €21,860 €52,450 41.68% 42,543 1430.0 4.85% 3.15%
1989 1,489 33.5 2,343 39.4 €22,512 €58,178 38.70% 45,090 1777.8 3.30% 1.89%
1990 1,085 26.5 1,369 26.0 €24,459 €65,541 37.32% 34,812 1491.9 3.12% 1.78%
1991 1,254 31.2 1,278 27.4 €24,909 €66,914 37.23% 37,058 1611.7 3.38% 1.94%
1992 1,167 29.2 1,269 27.4 €25,025 €69,264 36.13% 44,433 2013.6 2.63% 1.45%
1993 759 18.8 871 18.7 €24,759 €69,883 35.43% 45,390 2161.0 1.67% 0.87%
1994 489 12.2 634 13.2 €24,927 €72,732 34.27% 50,204 2445.0 0.97% 0.50%
1995 371 10.3 403 9.5 €27,763 €77,994 35.60% 49,288 2666.2 0.75% 0.39%
1996 313 9.9 376 9.5 €31,629 €87,202 36.27% 61,006 3677.0 0.51% 0.27%
1997 225 7.2 259 7.2 €32,000 €102,222 31.30% 64,652 4424.1 0.35% 0.16%
1998 173 6.2 211 6.1 €35,838 €125,302 28.60% 68,925 5654.9 0.25% 0.11%
1999 112 5.0 141 5.0 €44,643 €148,521 30.06% 78,572 7692.7 0.14% 0.06%
2000 156 9.5 113 4.7 €60,897 €169,191 35.99% 80,856 9003.7 0.19% 0.11%
2001 192 14.9 155 10.7 €77,604 €182,863 42.44% 69,062 8732.6 0.28% 0.17%
2002 218 20.0 224 17.6 €91,743 €198,087 46.31% 93,136 14359.3 0.23% 0.14%
2003 162 13.9 215 16.4 €85,802 €224,567 38.21% 97,888 17446.1 0.17% 0.08%
2004 171 16.0 215 16.2 €93,567 €249,191 37.55% 104,305 21019.2 0.16% 0.08%
2005 147 16.3 193 14.3 €110,884 €276,221 40.14% 120,037 27753.3 0.12% 0.06%
2006 166 20.3 242 20.8 €122,289 €305,637 40.01% 114,593 31382.2 0.14% 0.06%
2007 57 6.8 92 7.8 €119,298 €322,634 36.98% 88,747 24064.1 0.06% 0.03%
2008 50 5.5 75 7.3 €110,000 €305,269 36.03% 55,879 15140.3 0.09% 0.04%
2009 65 8.3 75 7.0 €127,692 €242,033 52.76% 27,924 6431.1 0.23% 0.13%
2010 92 12.1 69 7.4 €131,522 €228,268 57.62% 20,021 4,153.9 0.46% 0.29%
2011 110 12.3 106 11.0 €111,818 €230,303 48.55% 12,834 2427.7 0.86% 0.51%
2012 174 17.3 149 14.7 €99,425 €220,415 45.11% 17,769 3225.0 0.98% 0.54%
2013 212 20.0 143 11.4 €94,340 €228,216 41.34% 19,258 3709.3 1.10% 0.54%
2014 222 22.7 171 13.1 €102,252 €246,378 41.50% 31,897 6187.2 0.70% 0.37%
2015 298 32.4 247 22.8 €108,725 €281,432 38.63% 32,236 6326.0 0.92% 0.51%
2016 330 37.7 257 26.6 €114,242 €313,483 36.44% 35,037 7284.8 0.94% 0.52%

Page 28
The number of loans paid is smaller than the number of loans paid. Also loans paid will be at a lag
relative to loans approved.
The following charts use the loans approved numbers and so over represent the Local Authority loan
numbers.
Local Authority home lending, from a peak in 1981 where it accounted for over 36% of homes and over
and 25% of the loan home amount, has fallen to where it represents less than 1%. However, the recent
affordable homes initiative, being delivered through Local Authorities, may cause this to increase. In
this context, the apparently unregulated lending practices of Local Authorities may come under
examination. Another hidden factor that would be worth considering in terms of Local Authority home
lending is not just lending practices but some form of index of lending efficiency – number of loans issued
and operated for numbers of personnel relative to other lenders.
The average Local Authority loan approved is considerably than the average mortgage and the average
non-Local Authority property purchase price. The latter may be due to Local Authorities selling their
housing stock at sub-economic prices.
The following chart shows the numbers of home loans approved nationally and by Local Authorities, It
shows that Local Authorities effectively stopped large scale lending after 1987

Page 29
The following chart shows the proportion that Local Authority loans represented as a percentage of the
number and value of home lending. Again, it shows the rapid fall after 1987.
The following shows a profile of RFSP PDH and Local Authority mortgages in arrears for over 90 days
with the RFSP numbers shown on the left vertical axis and the Local Authority numbers shown on the
right vertical axis.

Page 30
While the proportion of loans in arrears is much greater for Local Authorities, the arrears percentage
profiles are very similar. The R2 value of these two series is 0.9096 indicating a high statistical
correlation. The same comments as before apply to the possibility of spurious regression
Local Authority mortgage lending and collections practices are potentially important as Local
Authorities may be the vehicle for increased mortgage lending for social and affordable housing in the
future. The high rates of arrears and their long duration may be due to poor collections practices by
Local Authorities. These numbers also do not take into account the cost of home loan issuing and loan
management by Local Authorities.
Local Authority mortgage lending is currently not regulated by the Central Bank.
Mortgage Arrears Cohort Analysis
These are just some notes on a possible approach to analysing movements between arrears cohorts.
Central Bank mortgage arrears data is measured at 90 day intervals. Arrears are classified into 90 day
cohorts:
 Not In Arrears
 In Arrears Up To 90 Days
 In Arrears 91 To 180 Days
 In Arrears Over 720 Days
 Repossessed

Page 31
So, for example, a new mortgage issued during Interval 1 could move to the either of the cohorts Not In
Arrears or In Arrears Up To 90 Days at the end of Interval 2.
Similarly, the number of mortgages in the cohort In Arrears 720+ Days could move to any of the cohorts
in the next measurement interval:
1. Repossessed – the mortgaged property is repossessed and so no longer mortgaged
2. 720 + Days – their arrears continue unpaid and get older
3. In Arrears 361 - 720 Days – the older arrears are paid but some of the newer arrears remain
4. In Arrears 181 To 360 Days – the older arrears are paid but some of the newer arrears remain –
5. 91 - 180 Days – the older arrears are paid but some of the newer arrears remain
6. 1 – 90 Days – the older arrears are paid but some of the newer arrears remain
7. Not In Arrears – all arrears are paid off
Schematically, the possible movement between cohorts is:

Page 32
Modelling this movement at this level of detail would be quite complex and would add little insight as
the probabilities with which elements of one cohort move to another cohort change over time. The
underlying data was volatile over the interval being measured.
You could model this using simple matrix algebra.
The numbers of mortgages that fall into the various categories would be represented as:
Mortgage
Paid Off
New
Mortgage
Not In
Arrears
In Arrears
Up To 90
Days
In Arrears
91 To 180
Days
In Arrears
181 To 360
Days
In Arrears
361 To 720
Days
In Arrears
Over 720
Days
Repossessed
A1 B1 C1 D1 E1 F1 G1 H1 I1
The probabilities of moving between cohorts at the end of an interval could be represented as a second
matrix. This shows the values for the cohort In Arrears Up To 90 Days.
Mortgage
Paid Off
New
Mortgage
Not In
Arrears
In Arrears
Up To 90
Days
In Arrears
91 To 180
Days
In Arrears
181 To 360
Days
In Arrears
361 To 720
Days
In Arrears
Over 720
Days
Repossessed
BD
CD
DD
ED
FD
GD
HD
Where:
BD = proportion of New Mortgages that go into In Arrears Up To 90 Days
CD = proportion of existing mortgages Not In Arrears that go into In Arrears Up To 90 Days
DD = proportion of already In Arrears Up To 90 Days remain In Arrears Up To 90 Days
ED = proportion of In Arrears 91 To 180 Days move to In Arrears Up To 90 Days
FD = proportion of In In Arrears 181 To 360 Days move to In Arrears Up To 90 Days
GD = proportion of In Arrears 361 To 720 Days move to In Arrears Up To 90 Days
HD = proportion In Arrears Over 720 Days move to In Arrears Up To 90 Days
Multiplying the two matrices would give you:
Mortgage
Paid Off
New
Mortgage
Not In
Arrears
In Arrears
Up To 90
Days
In Arrears
91 To 180
Days
In Arrears
181 To 360
Days
In Arrears
361 To 720
Days
In Arrears
Over 720
Days
Repossessed
A2 B2 C2 D2 E2 F2 G2 H2 I2

Page 33
In this simple example:
D2 = B1 x BD + C1 x CD + D1 x DD + E1 x ED + F1 x FD + G1 x GD + H1 x HD.
You could start with some assumptions to make the model easier such as the population in one cohort
only moves right to the next lowest cohort, moves to the Not In Arrears cohort by paying off all arrears
or by moving to the Repossessed cohort.
Then:
D2 = B1 x BD + C1 x CD + E1 x ED + H1 x HD.
The Central Bank mortgage arrears data only contains the more details set of arrears cohorts from Sep
2012 onwards.
The proportions of numbers in one cohort in any interval relative to the number in the previous interval
are:
Dec-
12
Mar-
13
Jun-
13
Sep-
13
Dec-
13
Mar-
14
Jun-
14
Sep-
14
Dec-
14
Mar-
15
Jun-
15
Sep-
15
Dec-
15
Mar-
16
Jun-
16
Sep-
16
Dec-
16
Mar-
17
Jun-
17
Sep-
17
Dec-
17
Not In Arrears 0.979 0.989 0.993 0.999 1.002 1.004 1.010 1.009 1.010 1.006 1.006 1.001 1.001 0.999 1.002 1.000 1.001 0.997 1.002 1.0001.001
In Arrears Up
To 90 Days
0.937 0.993 0.967 0.945 0.943 0.976 0.912 0.924 0.962 0.957 0.919 0.959 0.987 0.997 0.933 0.947 1.001 1.004 0.941 0.9931.012
In Arrears 91 To
180 Days
0.935 0.983 0.967 0.947 0.916 0.891 0.915 0.865 0.840 0.910 0.907 0.907 0.938 0.978 0.968 1.031 0.966 0.996 0.965 0.9930.981
In Arrears 181
To 360 Days
0.958 0.990 0.995 0.962 0.935 0.912 0.892 0.877 0.847 0.851 0.889 0.885 0.889 0.935 0.955 0.974 0.960 0.971 0.981 0.9761.008
In Arrears 361
To 720 Days
1.029 1.036 1.004 0.990 0.958 0.941 0.948 0.914 0.883 0.908 0.871 0.860 0.893 0.911 0.925 0.919 0.944 0.946 0.970 0.9581.064
In Arrears Over
720 Days
1.124 1.119 1.113 1.103 1.055 1.051 1.050 1.011 1.008 1.004 1.003 0.981 0.974 0.985 0.977 0.988 0.968 0.985 0.976 0.9830.915
Not In Arrears 0.979 0.989 0.993 0.999 1.002 1.004 1.010 1.009 1.010 1.006 1.006 1.001 1.001 0.999 1.002 1.000 1.001 0.997 1.002 1.0001.001
The proportions are not consistent over time. These proportions tend to indicate an inconsistency in the
Central Bank mortgage arrears data.
There are some discrepancies with the Central Bank mortgage data. For example, from Jun-12 to Sep-12
the numbers of mortgages increased from 765,267 to 794,275 and then fell back to 778,375 in Dec-12.
The corresponding new mortgage numbers from the BPFI show just 3,983 new mortgages from Jun-12
to Sep-12 and 6,043 from Sep-12 to Dec-12.
IFRS 9, Non-Performing Loans and Repossessions
IFRS 9 (‘Financial Instruments’) is a new accounting standard which will succeed IAS 39, and is to be
implemented for annual periods beginning on or before 1 January 2018. A key part of IAS 39 and IFRS
9 relates to impairment accounting. IAS 39 used an ‘incurred loss model’ (impairment recognised when a
credit loss event occurs), while IFRS 9 introduces an ‘expected loss model’ (expected credit losses
(“ECL”) recognised even if an actual loss event has yet to occur). In addition, under IFRS 9 entities

Page 34
must take into account future expectations/ forecasted conditions combined with historic / existing
conditions in its assessment of credit impairment.
It would be worthwhile tracking the impact of IFRS 9 on mortgages in arrears.
Retail mortgages – PDH and BTL - account for around 57% of non-performing loans (NPLs).
Impairment in IFRS 9 is based on an expected loss (EL) model. It affects the way credit losses are
recognised in a bank’s profit and loss statement. Impairments are currently based on incurred losses.
The main impact on banks is the need to recognise EL for all financial products. Banks will have to
update their estimated losses to reflect changes in the credit quality of their assets.
Essentially non-performing loans must have an impairment allowance, measured as the present value of
all credit losses projected for the instrument over their full lifetime, reported on the bank’s profit and
loss statement.
The assumption is that all loans in arrears for 90 days or more must be classified as non-performing but
this can be modified for defined cases. IFRS 9 does not state that restructured loans in arrears do not
have to be so classified.
In response to IFRS 9, retail banks will have to reduce their bad debts. This includes mortgages in
arrears. It is easier for these banks to divest themselves of those mortgages by selling them in bulk
quickly than to devote resources to attempting to engage with a core of non-engagers that have been in
arrears for some time. The repossession route is still long, slow and expensive.
Summary
Arrears in financial service provider mortgages appear to be closely correlated with the amount of
negative equity. Being in arrears is a pre-requisite to repossession on foot of a legal process. Voluntary
possession dos not strictly require any arrears in order to occur.
In the last 10 years, there have been many legal and regulatory interventions that have affected the way
in which properties whose mortgages are in arrears can be repossessed. The repossession route is still long,
slow and expensive.
This has been combined with a possible reluctance by retail banks whose bail-outs were financed by tax
payers engaging in widespread repossessions.
Two thirds of mortgages in arrears have not been subject to any form of restructuring.
The rate of repossessions is extremely low. The risk of repossession is very low. The correlation between
the number of arrears and the number of repossessions is very low. The Dunne Judgment may have had
an effect in stopping latent repossession actions becoming actual. But this is difficult to establish.
IFRS 9 will cause banks to sell non-performing loans in bulk rather than attempting the time-consuming
and expensive process of trying to engage with a core of non-engagers that have been in arrears for some
time. The loans will probably be sold at a considerable discount to organisations that will pursue
repossession or some other financial arrangement. This will represent a loss to the bank as well as to
taxpayers that have funded those banks.

Page 35
A very high proportion of Local Authority mortgages are in arrears. Many of these arrears are more than
20 years old. The drivers for Local Authority mortgages arrears appear to be very different that those
that apply for financial service provider mortgages.

Page 36
For more information, please contact:
http://ie.linkedin.com/in/alanmcsweeney

Mortgage Arrears, Strategic Default and Repossessions

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