Autonomous Province of Trento – Agency for Water Resources and Energy (APRIE) joins the Advisory Council of the Energy Efficient Mortgages Pilot Scheme

Pilot Banks Meeting – Riga, Latvia – 24 April 2019

Energy Efficient Mortgages Data Reporting: a small step for banks, a big step for sustainable finance

By EMF-ECBC

Introduction

At the time this article is written, EeDaPP is at a turning point. By March 2019, the project will enter its second year, while its twin project, the Energy Efficiency Action Plan will successfully come to an end. At the same time, the Energy Efficient Mortgages Initiative Pilot scheme, the operational experimental phase involving more than 40 European banks and 50 institutions is entering a new determining cycle.

The interactions and synergies that took place between the two projects and the pilot scheme were determinant in achieving the first milestones of the EeDaPP project. In its first year, the EeDaPP partners, with the help of market stakeholders and pilot banks managed to fulfil their main objectives:

  • Identify and list best practices in data storage, management and structuration, existing templates and protocol to build upon;
  • Define a minimum set of energy efficiency reporting criteria to fulfil the reporting requirements for the Energy Efficient Mortgages Asset Class;
  • Start defining and designing a standardised data protocol, collecting feedbacks from pilot banks.

Energy Efficiency minimum pan-European reporting criteria

The energy efficiency mortgage value chain is complex and fragmented, which is fully reflected in how data is being collected, managed, shared and reported. EEMI brings together a wide range and diverse set of individual stakeholders including lending institutions, borrowers, energy assessors, valuers and data warehouses, operating at different stages of the property life cycle who often have very different interests and priorities and typically tend to think and act in silos. Mainstreaming energy efficiency mortgages and linking it to sustainable finance requires to increase data accessibility, comparability and disclosure. Yet, in order to do so, the final reporting requirements must build as much as possible on the already wide range of information that banks need to report on for regulatory purposes. The extra mile that banks will have to provide to link the additional information on the energy performance of assets, a valuation method that include such “green” inputs and the traditional information reported on financial characteristics and performance at loan level must be facilitated and rationalise in order to reach a practical and effective implementation in the short-medium term. 

With this operational constraint in mind, the EeDaPP consortium extracted a minimum core list of energy performance and efficiency criteria that can reflect, at European Level a fair assessment of the energy performance of the whole building stock (new and existing building, residential or commercial properties, individual or collective housing).

The following figure is displaying the data reporting structure, or “data tree” developed for EEM. It is made of three pillars; identifiers, financial and banking data and energy efficiency data. The additions to existing regulatory reporting requirements (from the European Central Bank, the European Banking Authority and the European Securities & Markets Authorities) are restricted to three core indicators: the Energy Performance Certificate, the “upgraded” property valuation assessment (taking into account energy performance criteria) and the link to existing public energy efficiency scheme (of European, National, or local level). Among those, the EPC is identified as the most important information for banks to collect, a small step in the reporting protocol and a huge step in linking the sustainable finance objectives to the real economy.

Figure 1. EEM Reporting Data Tree
Source: EMF-ECBC

The publication of the White Paper in February 1st, detailing the reporting criteria list, its rationale and main principles is intended first and foremost to start a consultation with lending institutions, data providers, built environment professionals and other relevant market stakeholders to assess the relevance of the proposed data points, both mandatory and voluntary, their respective categorisations as such, and the feasibility of gathering, processing and disclosing them. In this sense, the protocol should be considered as a “living” list to be adapted and refined according to market feedback.

EeDaPP – Energy efficiency Data Protocol and Portal –  is an initiative by the European Mortgage Federation – European Covered Bond Council (EMF-ECBC), Ca’ Foscari University of Venice, CRIF S.p.A., European DataWarehouse GmbH, Hypoport BV, TXS GmbH and SAFE Goethe University Frankfurt. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 784979.

Energy efficiency and credit risk: uncovering correlation

By Daniele Vergari, Gianluca Natalini, Stella Fumarola, CRIF

Introduction

One of the key objectives within the EeDaPP project is to investigate the correlation between energy efficiency and credit risk, measuring how this affects obligor’s credit risk and thus a “green” mortgage portfolio performance.

To this end, CRIF, closely working with University of Venice “Ca’ Foscari” and the other EeDaPP consortium partners, will be preparing the ground for the quantitative analyses. These will focus on the two main components of credit risk and its cost trying to consolidate our previous research evidence:

  • Probability of default: energy efficient borrowers have a better payment behavior and therefore a lower credit risk;
  • Recovery rate: energy efficient properties are more valuable and show greater resilience to economic cycle.

Energy Efficient Mortgage Pilot Scheme

In order to make the study as sound and robust as possible, different market players and stakeholders are involved firstly in the creation of the analysis data pool:

  • Financial institutions provide information about mortgage loan applications (i.e. customer and contract data) and corresponding performance (i.e. the customer failed to pay its obligations);
  • Institutional players, like ENEA or other institutions, where needed, may integrate the banks’ own internal data and evidence with EPC information that may prove to be scarcely available for most financial institutions in the manner it is required by the analysis (e.g. historical time series);
  • Consortium member CRIF is able to further integrate the above data (i.e. estimated property value, property value time series, etc.).   

Once the pool data is available, a rigorous process of data normalization (needed to make data coming from different sources and / or institutions comparable and coherent) takes place followed then by the quantitative (econometric) analyses. The overall process is summarized in the following five steps:

  1. Data organization – going from data specifications preparation and data gathering through to data normalization and enrichment, data quality analysis. This ultimately leads to the data pool consisting of both energy efficient and non-energy efficient loans and mortgages so as to allow for comparative analyses of risk and its impacts;
  2. Model design – the fundamental pillars of the quantitative analysis are defined. They include the risk analysis (i.e. risk definition, choice of the appropriate time horizon, sample selection, segmentation, etc.) and the impact analysis (e.g. assessment of credit risk of energy efficient vs non-energy efficient portfolios, impacts on portfolio expected credit losses, regulatory capital absorption, etc.);
  3. Correlation analysis – based on the model design, the econometric analyses defined above are carried out to assess how energy efficiency affects credit risk and recovery rates (from property sales). At this stage, the a priory hypotheses are verified and preliminary evidence also further investigated;
  4. Impact analysis – quantification of the impact of such correlation evidence on the portfolio performance (i.e. risk, cost of risk);
  5. Reporting – final document reporting assumptions and findings.

Impact of Energy Class on Credit Risk

Crif has already carried out a preliminary assessment of the impact on credit risk of energy class using a sample of about 18.000 mortgage loans for which all customer level (e.g. age, marital status, residential status, etc.) and contract level information (e.g. property EPC, loan amount, property value, downpayment amount, term, etc.) was available. Credit performance was also available allowing to observe credit risk differences between energy efficient and non-energy efficient obligors. In order to take in due account potential customer profile differences, the portfolio was clustered into segments homogeneous in terms of property value and loan-to-value rate.

The analyses showed that, within the identified clusters, that energy classes A and B report a much lover one-year default rate compared to the other classes (that are twice as risky and classes A and B).

The sample size is not large enough to generate robust evidence. Further analyses and larger and more representative samples are necessary in order to confirm and possibly fine-tune the above evidence.

Impact of Energy Class on Property Value

Another aspect that must be taken into consideration is the value of “green” properties and how real estate markets value them. These two elements may have a potential impact the collateral value (represented by the property) and therefore on the recovery rate realized from the property sale. The underlying assumption is that energy efficient properties have greater value than non-energy efficient ones (all the other features being the same) and that this value is less affected by the economic cycle (property resilience).

Contrarily to the probability of default, gaining robust evidence on recovery rates may prove rather difficult considering the average duration of the recovery processes in some European countries (e.g. Italy). Most financial institutions do not have EPC information at all, some others have started to collect it although only recently and then lacking it for most of the cases with complete workout processes for which recovery evidence is more robust.

The WP5 team is also facing this potential issue; completion of the data pool creation will tell how relevant this may be. Automatic Valuations Models (AVM) come into the game to help cope with such data limitations. The Automatic Valuation Model used by Crif, compliant with the the definition adopted by the European AVM Alliance®, is a system that provides an estimate of value of a specified property at a specified date (also in the past), using mathematical modelling techniques in an automated manner. The model  does not necessarily require any previous values of the property to be provided as input, but it only requires that a property be specified and therefore they can function merely based on property address (or cadastral reference or other forms of unique property identification)  and a few basic property characteristics. By analyzing these property attributes, (using the market comparison approach), it provides property valuation in different points in time allowing to observe how such value varies throughout time (possibly considering also impact of a full economic cycle).

A study has been carried out using a sample of 40.000 mortgage loans for which the ECP information was available. The property value corresponding to such loans was estimated for the years 2011-2018, separately for energy efficient and non-energy efficient properties. The preliminary evidence shows that energy efficient properties actually have different value trends and prove to be more resilient compared to the non-energy efficient ones. The expected “energy efficiency” effect on property value is illustrated in the exhibit.

Conclusions & Next Steps

We are at the very early steps of WP5’s correlation analysis study. However, some preliminary analyses have provided some promising hints into how energy efficiency can affect credit risk and the ability to recover from property sale. The above studies were conducted on limited data samples and the gained evidence may be affected by the used data. The ground for the WP5 study has been prepared. The data gathering phase, the most crucial one, has already started with the aim of building a pool large enough to be representative of the market and to allow for robust analyses. Data availability and quality are crucial. WP5 team has then prepared a plan for data remediation and enrichment so as to effectively cope with potential data issues.

Further evidence will be made available as the study progresses.

E.ON joins forces with BNP Paribas Personal Finance to help UK home owners unlock energy efficiency potential through ‘Energy Efficient Mortgages’

By Marco Marijewycz, E.ON  

Around 19 million UK households – equal to around 71% of the UK’s 27 million homes – currently fall below an Energy Performance Certificate (EPC) Band C rating, which means they are missing out on energy savings of up to £380 a year by not having basic measures in place.

Tackling energy efficiency levels of existing housing stock is one of the biggest infrastructure challenges of this generation and is part of the Government’s Clean Growth Strategy which aims by 2035 to bring as many homes as possible up to EPC Band C level where practical, cost-effective and affordable.

Under the umbrella of the Energy Efficient Mortgage Initiative, E.ON is working with BNP Paribas Personal Finance to develop and pilot an innovative Energy Efficient Mortgage product, which will allow movers, first time buyers, and re-mortgagers to use their mortgage to borrow further via a linked ‘energy efficiency home improvement loan’ to improve the energy efficiency of their homes. Under this model BNP Paribas Personal Finance would provide the improvement loan financing and E.ON would provide a managed service to install appropriate energy efficiency solutions. This service would help the customer to identify what measures would deliver the greatest savings potential, E.ON would then install the measures and offer a range of in-life energy services.

The improvements funded through the scheme loan could also result in a discounted mortgage rate once the energy efficiency measures have been verified via an updated EPC.

Michael Lewis, Chief Executive, E.ON UK, said: “We need to find ways to radically increase interest and action on energy efficiency in homes, but property owners often face a significant financing barrier when wishing to do so. In the UK, attempts have been made in the past to tackle this barrier through schemes like the Green Deal, but they have not been successful, in part because they weren’t designed with the customer front and centre.

Energy efficient mortgages have the potential to be a game changer in the delivery of affordable finance and we are ready to meet the challenge for home-owners motivated to take the step into energy efficient living. Our agreement with BNP Paribas Personal Finance is a further step along this journey and brings together two well-known international companies with expertise in financing and delivering energy saving solutions across Europe.”

Easier access to affordable financing via an energy efficient mortgage should provide an added incentive for customers to better insulate buildings, replace old heating systems or increase their energy independence through solar panels, batteries or virtual storage. It can also ease the purchase of existing energy-efficient houses or commercial buildings through preferential financing in conjunction with a mortgage.

The ambition of this Energy Efficient Mortgage pilot is to provide a competitively priced home improvement loan provided by BNP Paribas Personal Finance linked to a mortgage to fund a range of personalised energy efficiency solution bundles delivered by E.ON. These could include measures such as insulation, energy efficient boilers and smart meters and smart thermostats. For customers wishing to prepare their home for tomorrow’s energy world, smart energy technologies such as electric vehicle charging points, solar panels and battery storage could also be funded as part of the Energy Efficient Mortgage pilot, as well as heat pumps. All of which E.ON intends to steer by its innovative Home Energy Management System Dashboard.

E.ON and BNP Paribas Personal Finance are working towards further collaborations with building societies and High Street finance providers to pilot and develop this innovative new financing solution to customers, initially for the UK market, in the first half of 2019. This collaboration aligns closely to the recommendations of the UK Government’s Green Finance Task Force.

The partnership follows consumer research undertaken by E.ON as part of the EeMAP project in several European countries in February 2018 to understand if customers would take advantage of an energy efficient mortgage where E.ON found a positive consumer appeal towards the concept, particularly in Great Britain. The research conducted by E.ON in several European countries looked into the question of whether customers would even take advantage of a standardized “energy efficient mortgage”. The result is consistently positive with the overall high level of appeal towards the concept particularly high in Italy and Great Britain. In Germany and Sweden, respondents welcomed the fact that, in addition to existing funding instruments, there was an alternative or more extensive offer.