Greek Real Estate challenges: An integrated approach on property valuations amidst turbulent times Regulated by RICS

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Page 1 Dimitris Andritsos MSc MRICS Chief Executive Officer Eurobank Property Services Greek Real Estate challenges: An integrated approach on property valuations amidst turbulent times Regulated by RICS October 2015

Table of Contents Page 2 I. Real Estate Market Overview II. New Challenges in the Role of Valuers III. The Contribution of the Greek Banking System IV. Advanced Tools V. Case Study: Valuations v/s Actual Transactions VI. Conclusion VII. APPENDIX

I. Real estate market overview Page 3 Inherent Problems: Lack of Transparency Tax Regime (Varying tax laws with high tax factors) Urban Planning Complications Overall Bureaucracy Negative pressure attributed to: Current Economic Climate Political Instability and Uncertainty Unfavorable Macroeconomic Forecasts Resulted in: Deferral or Cancellation of Investment Initiatives Decrease in Development Activity Precarious Forecasts Requirement for Higher Yields Note: Impact on recent developments (i.e. Capital Controls, MOU III) not yet factored in. Source: ELSTAT

I. Real Estate Market Overview Page 4 Sources: The World Bank, Bank of Greece, Eurobank Property Services Research

I. Real Estate Market Overview Structural Changes of Institutional Framework Page 5 A series of structural reforms in legislation have been introduced to attract investments. These are: Deregulation of commercial leases (Negotiable duration minimum 3 years instead of 12 years) (4242/2014) Significant decrease in property transfer tax to 3% (4223/2013) Composite Touristic Investments (e.g. Hotels and housing in the same development) (2012) Special Plan of Spatial Development of Public Estate (ΕΣΧΑΔΑ 3986/2011) Special Plan of Spatial Development of Strategic Investments (ΕΣΧΑΣΕ 4146/2013) Recapitalization of the Banking System. Source: European Commission (May 2015), ELSTAT (September 2015)

I. Real Estate Market Overview: A light at the end of the tunnel? Page 6 2013 2014 5 th Emerging Trends in Real Estate (ULI & PWC Report) Investment Trends Traditionally safe investment destinations are oversaturated (London, Zurich, Paris etc.) Investors seeking returns are more willing to assume additional risk (German Stalwart Cities, European Recovery Plays etc.) 28 th Source: Emerging Trends Europe survey 2014 Source: Emerging Trends Europe survey 2015 Investments & Infrastructure Announcements (Indicatively) Athens Metro and Tram extensions Faliron Seafront Regeneration Pedestrianization of Panepistimiou Avenue Exploitation of former Hellinikon airport (Lamda Development & Foreign Investors) Completion of Iconio-Thriasio Rail line (logistics)

II. New Challenges in the Role of Valuers Page 7 Market value definition by International Valuation Standards: The estimated amount for which an asset or liability should exchange on the valuation date between a willing buyer and a willing seller in an arm s length transaction after proper marketing and wherein parties had each acted knowledgeably, prudently and without compulsion. Critical Question How can this be applied in a Market which is: Intransparent Stagnating (reduced transaction volume) Distressed Prerequisites for reliable valuations: In-depth Knowledge of Valuation Methodologies and Practices: High Academic and Professional Credentials of Valuers Continuous Professional Development Market Intelligence Access to Reliable Market Data Monitoring of Market Trends & Changes Quality Control: Effective Reviewing Mechanisms

II. New Challenges in the Role of Valuers Page 8 Sophistication of Appraisal Practices Progress on an institutional level: Increasing demand for high level of professional and academic credentials Specialized institutions presence (e.g. TEGOVA, AVAG, HVI, RICS, ULI, ICSC) in the Greek market Supported by senior property professionals Organization of training events (Life-long learning programs through seminars, workshops) Increase in headcount of officially certified valuers TEGOVA: 29 members in 2009; 504 in 2014 New categories of accreditations have been added: (e.g. Valuer specializing in Plant and Equipment) RICS: 27 members in 2003; 151 in 2015 Number of accredited valuers by TEGOVA 2011-2015, Source: AVAG

Volume in bn Page 9 III. The Contribution of the Greek Banking System Banking system is the major stakeholder in Greek Real Estate, controlled and supervised by European organizations such as European Central Bank, and national supervision authorities (Bank of Greece) Wide network of accredited valuers on a national level with in depth knowledge of local sub-markets Valuers are qualified professionals, certified by international organizations with high professional recommendations and having undergone special training Assessment of valuers per case and on an annual basis 300 250 200 150 100 50 0 Total Volume of Outstanding Loans Consumer loans Residential loans Source: Bank of Greece (BoG) Bussiness loans Total NPLs

III. The Contribution of the Greek Banking System: Quality Control Page 10 Multiple steps of reviewing process 4-eye principal (or 6- or 8-eye for complex cases), Centralised character of reviewing on a senior level according to predetermined control criteria, Red flag check, Sample checking of valuations by external independent valuers. Appraisal 1 st Review 2 nd Review Sample Checking Specialized Software development (REAL II, WAVE etc.), Software developments along with the requirements of Internal Control result in high level risk audit. Development and exploitation of sophisticated tools

IV. Advanced Tools Page 11 Advanced tools used for valuation assessment and effective risk management: 1. Regularly Updated Market Reports 2. Residential & Commercial Indices which help monitoring Market Trends & Changes 3. Forecasts 4. Sophisticated Statistical Tools which provide Current Market Price Estimations & monitor Risk (e.g. Automated Reviewing Mechanism (ARM))

IV. Advanced Tools: Market Intelligence Page 12 A wide range of reports covering all major property markets are updated regularly, estimating the sale price and rent ranges per property type for each geographical area, early identifying changes in market trends Property Age (residential properties) Up to 10 years 11-20 21-30 31-40 >40 years Market Reports Location Expensive Medium Economic Structure of Residential Market Reports Annual Nation-wide reports on local commercial property markets (offices retail) in their entirety as well as their sub-segments. Periodical Prefecture level reports on all major markets (residential offices retail). For the prefectures of Attica and Thessaloniki we publish the respective reports for each of their municipalities. The number of total reports updated semi-annually is 233. Specialized market reports as well as major market sub-segment reports (e.g. Offices on Syngrou Avenue) or specific area reports (e.g. island of Rhodes hotel market) etc.

IV. Advanced Tools: Residential and Commercial Indices Page 13 Residential Indices Commercial Indices 15 Indices in Attica Year of Construction Office Retail 24 Indices in Thessaloniki & Rest of Greece 1 Index for Greece 2 Indices for Greece (Old & New Apartments) 2 Indices for Athens (Old & New Apartments) Valuations are collected on a quarterly basis.

IV. Advanced Tools: Residential and Commercial Indices Page 14 120 Residential Index Comparison: BoG - EPS - PropIndex 120 EPS Commercial Index 100 100 80 80 60 60 40 40 20 20 0 2007 2008 2009 2010 2011 2012 2013 2014 2015 BoG EPS PropIndex 0 Quarter All Office Retail Residential: 40% decrease since 2007 Commercial: 50% decrease since 2007

IV. Advanced Tools: Forecasts Page 15 Residential Index Forecasts are based on: World leading quality macro economic data and forecasts at local level Exhaustive collection of local level planning and building activity data Outcome of advanced econometric modelling, consistent with latest theoretical scientific literature, fully integrated with relevant macroeconomic variable forecasts (Inflation, Interest Rates, Household Disposable Income etc.) Covering from short term to long term (over 4 years) horizon, with quarterly predictions.

IV. Advanced Tools: Automated Reviewing Mechanism (ARM) Page 16 Automated Reviewing Mechanisms (ARM)s are testing instruments based on the structure of Automated Valuation Models (AVMs). ARMs use the same tools and information with the AVMs. The uniformity and performance of ARM s database has been carried out according to the Standards on Automated Valuation Models (AVMs), approved by the IAAO* and ANEVAR. ARMs enable quick and effective monitoring of valuations. ARMs work as an ALERT system that point toward the cases with Forecasting & Questionnaires Hedonic Regression Model Extensive Database & Updated Market Reports abnormal deviations. Four-phased procedure: An efficient and transparent process of continuous monitoring Phase 1 Valuation Phase 2 1 st Review Phase 3 Phase 4 Real Time ARM Filter 2 nd Review AVM Initial Certified Valuation of portfolio or single property 1 st review from specialized experts (market researchers and reviewers) Usage of ARM checker for identification of large deviations 2 nd Review for cases with deviations over 20% *International Association of Assessing Officers

IV. Automated Reviewing Mechanism: Performance Procedures Page 17 Average deviation 1.30% 12.80% Mean Absolute Deviation at National Level 54.22% of appraisals with deviation less than 10% About 80.60% of appraisals with deviation less than 20% The quality of the data is checked daily under a fourphase procedure.

V. Case Study Valuations v/s Actual Transactions : Data Collection Page 18 1. Collection of transactions data from multiple sources: i. Eurobank Property Services Database ii. Local Real Estate Agents 2. Type of Transactions i. Commercial Office Transactions Residential (focused on apartments - total sample: 200) ii. Retail Residential Commercial (Limited # of transactions - total sample: 34) Apartments (90% of Sample) Semi-detached houses Detached houses Research focused on Attica due to the high concentration of transactions. Source (images): kasrawy.deviantart.com, www.rightmove.co.uk

V. Case Study Valuations v/s Actual Transactions : Limitations Page 19 No study goes without limitations: Grammy Award Winning Artist Phil Hansen once said: Embrace your LIMITATIONS and watch yourself become LIMITLESS In this case study, the following limitations, regarding transaction data were faced: 1. Insufficient address data (e.g. The street name was Source: Image - http://dfwhailrepair.com/ on 23/9/2015 known but not the exact location street number etc.) 2. Subjective evaluation of property characteristics amongst agents (e.g. condition of maintenance, view etc.), 3. Exact Transaction Date (Indexation purposes e.g. 2 nd Semester of 2014 was expressed as 15/9/2014), 4. Insufficient property characteristics (e.g. floor number, condition of maintenance etc.) for a small number of transactions.

V. Case Study Valuations v/s Actual Transactions : Procedure Page 20 Three (3) sets of values were created to be compared to transactions: Statistically Estimated Value (produced by ARM) Certified Valuation (desktop) Market Range For a transaction to be considered special (non-ordinary), the criterion was to FAIL all three sets of values. An ordinary transaction only needed to pass one test. 1 st check Statistically Estimated Value Checks the deviation between the value created by the mathematical model and the transaction. 2 nd check Certified Valuation Checks the deviation between the value created by the network and the transaction. 3 rd check Market Range Checks whether the transaction lies between the range of the reports or the extended range +/- 20% (loose criterion). SPECIAL TRANSACTION

V. Case Study Valuations v/s Actual Transactions : Residential Results Page 21 Results: Ordinary Transactions (68%) Special Transactions (32%) Ordinary Transactions (68%) Summary Transaction /Desktop Transaction /ARM Market Report Ranges Mean Deviation Mean Absolute Deviation -5.6% -6.1% Within Range 12.9% 14.2% Within Range

V. Case Study Valuations v/s Actual Transactions : Residential Results Page 22 Results: Non-Ordinary Transactions (32%) The results indicate that those transactions were special (nonordinary). The sale prices are not close to any of the values and additionally do not fall within the market report ranges, leading to extremely large deviations. The results imply that transactions have occurred in a different level of prices due to: Tax Motives (not arm s length) Special Circumstances (e.g. rumors for haircuts on bank accounts, capital controls etc.) Forced Sales (distressed sales) Other

V. Case Study Valuations v/s Actual Transactions : Commercial Results Page 23 Results: All Transactions (Non-ordinary & Ordinary) Special Transactions (12%) Ordinary Transactions (88%)

V. Case Study Valuations v/s Actual Transactions : Commercial Results Page 24 Results: Commercial Ordinary Transactions (88%)

V. Case Study Valuations v/s Actual Transactions : Commercial Results Page 25 Results: Commercial Non-Ordinary Transactions (12%)

V. Case Study Valuations v/s Actual Transactions : Summary of Results (Cumulative Charts) Page 26

VI. Conclusion Page 27 An integrated approach was adopted to improve reliability of valuations in turbulent times: 1. Improved Qualifications of Valuers (training, continuous professional development, certifications etc.) 2. Development of Sophisticated Systems (Review Mechanisms, Software REAL, WAVE etc.) 3. Utilization of Tools (indices, market reports to capture market trends, ARM, forecasts). This approach resulted in a success rate of valuations between deviation ranges [-20%,20%] of 80% for both residential and commercial properties.

VII. APPENDIX Page 28 APPENDIX

VII. Legislative aspects of an AVM Page 29 Internationally (UK): The Financial Service Authority provides general guidance in its Prudential sourcebook for Banks, Building Societies and Investment Firms (known as BIPRU). Rule 3.4.66 sets out the method for monitoring property values, noting that it allows statistical methods to be used to monitor the value of the property and to identify property that needs revaluation. AVM is bound to limitations in usage in line with international practice Explicit terms and conditions are provided on the EPS website

VII. Development of EPS AVM Page 30 The overall construction and assessment of the EPS AVM has been established according to ANEVAR s guidelines. EPS followed the hereinafter stages: Stage 1: Sampling Procedures Stage 2: Sample Size Stage 3: Data Management and Data Quality Analysis Stage 4: Stratification Stage 5: Determining Model Specifications Stage 6: Model Calibration Stage 7: Model Testing for Quality Stage 8: Model Validation Stage 9: Model Application Stage 10: Periodic Check of Model Accuracy

VII. Advanced Tools: Automated Valuation Model (AVM) Page 31 Hedonic Regression Model: is in the heart of ARM and Index developments Ln(V6li/V8li) = Σb1ljVji + Σb2jLji + Σb3jaji + eli provides the optimum coefficients for each property characteristic, useful in developing a successful mathematical process based on: Market forecasting Indices are based on historical data and therefore reflect both the present and the past) Market Reports Cover multiple areas. Present the current sale price and rent ranges for each geographical area. Specialized Questionnaires filled in by Market Experts Forecasting & Questionnaires Extensive Database & Updated Market Reports AVM Hedonic Regression Model

VII. Advanced Tools: Uniformity and Performance of Database Page 32 The uniformity and performance of ARM s database has been carried out according to the Standards on Automated Valuation Models (AVMs), approved by the International Association of Assessing Officers. Ratio Study Performance Standards Area Characteristics COD* PRD* Newer, more homogeneous areas 10.0 or less 0.98-1.03 Older, heterogeneous areas Rural residential and seasonal 15.0 or less 0.98-1.03 20.0 or less 0.98-1.03 Greek Real Estate has shown a more heterogeneous performance with COD less than 15 (12.8) and an automatic reviewer model that shows a very good performance both to low valued and high valued properties (PRD close to 1). *ARM: Automated Reviewing Mechanism *COD: Coefficient of Dispersion *PRD: Price Related Differential