9.2.2023 valid documentation

Basic data of the statistics

Data description

The statistics on households’ assets describe the total amount, structure and distribution of households’ assets among different population groups. The statistics describe both real and financial assets. In addition to different types of assets, the statistics also contain data on other matters that have a bearing on the financial position of households, such as income and debts.

Information is published at the household and personal level. The household level information comprehensively describes the amount of real and financial assets and the demographic distribution of wealth. At personal level, information is published only about publicly traded shares and mutual funds.

Statistical population

The target population of the statistics on households’ assets are private households and their members in Finland at the end of the statistical reference year (31 December).

The frame population includes all private households and their members living permanently in Finland at the end of the statistical reference year (31.12.). 

The household-dwelling population is formed by all persons living permanently at dwellings. Good two per cent of the entire population are excluded from the statistics. They include persons without a postal address, the institutional population (e.g. long-term residents of old people's homes, care institutions, prisons or hospitals), persons permanently resident abroad and persons temporarily resident in Finland. Conscripts are regarded as part of the population in these statistics.

Statistical unit

The statistical units of the statistics on households' assets are households and persons.

Unit of measure

The units of measure in the households' assets statistics are euros, %, numbers of households and persons.

Base period

Data in euros are given in the value of the latest statistical year.

Reference period

The data of the households' assets statistics describe data for the statistical reference year, which is the whole calendar year, and for the end of the statistical reference year (31 December).

Reference area

The data of the statistics on households' assets are published on the level of the whole country and according to the NUTS2 regional classification.

Sector coverage

The statistics on households' assets cover the main asset items reasonably well. The 2019 household survey included the following asset items: main residence, free-time residences, other dwellings, forests, farm land, cars, boats, other vehicles, deposits, investments in mutual funds, publicly traded shares, unquoted shares, net wealth of business activities and groups, bonds, derivatives, voluntary pension insurance, savings and investment insurance, loans, participation certificates and statutory pensions.

Asset items missing entirely in the 2019 wealth survey are cash and valuables. In 1987 to 2004, data on valuables were included as interview data. The 2009 and 2013 surveys do not contain data on savings and investment insurances.

Time coverage

The wealth survey has been conducted in 1987, 1988, 1994, 1998, 2004, 2009, 2013, 2016 and 2019. Apart from 2004, the data have been formed for the sub-sample (1987 to 1998) or for the entire sample (2009 to 2019) of Statistics Finland’s income distribution statistics. The 2004 survey was a separate sample survey. The survey method of the wealth surveys in 2009, 2013, 2016 and 2019 differs significantly from that of the surveys in earlier years. Their wealth data have mainly been derived from registers or estimated. Previous surveys are face-to-face interview surveys. Register based statistics about the publicly traded shares and mutual funds of persons are available for 2009 and 2013-2021.

Frequency of dissemination

The household-level data of the statistics are released at set intervals of years on Statistics Finland's website. Starting from the statistical reference year 2013, the household-level data have been published at three-year intervals. Individual-level data of the statistics on quoted shares and mutual funds are published annually.


Disposable money income

Households' disposable money income includes monetary income items and benefits in kind connected to employment relationships. Money income does not include imputed income items, of which the main one is imputed rent.

The formation of disposable money income can be described as follows:

+ wages and salaries
+ entrepreneurial income
+ property income (without imputed rent)
= factor income
+ current transfers received (without imputed rent)
= gross money income
– current transfers paid
= disposable money income

When current transfers paid are deducted from gross money income, the remaining income is the household's disposable money income.

The primary income concept used in the income distribution statistics is household's disposable money income according to international recommendations, in which case sales profits and taxes paid on them do not belong to the scope of the income concept. Following international recommendations, they are treated as a memorandum item outside the income concept.

The concept of disposable money income in the total statistics on income distribution differs from disposable money income in the income distribution statistics. As a conceptual difference, the income concept of the total statistics on income distribution includes taxable realised capital gains. For practical reasons, the total statistics on income distribution do not include the majority of interest income and current transfers received and paid between households (e.g. child maintenance support). Real property tax is not deducted in the total statistics on income distribution either.

GINI co-efficient

The Gini coefficient is the most common indicator describing income differences. The higher value the Gini coefficient gets, the more unequally is income distributed. The biggest possible value for the Gini coefficient is one. Then the highest earning income recipient receives all the income. The smallest Gini coefficient value is 0, when the income of all income recipients is equal. In the income distribution statistics, Gini coefficients are presented as percentages (multiplied by one hundred). The Gini coefficient describes relative income differences. The Gini coefficient does not change if the incomes of all income earners change by the same percentage.


A household is formed of all those persons who live together and have meals together or otherwise use their income together. The concept of household is only used in interview surveys.

Excluded from the household population are those living permanently abroad and the institutional population (such as long-term residents of old-age homes, care institutions, prisons or hospitals).

The corresponding register-based information is household-dwelling unit. A household-dwelling unit is formed of persons living permanently in the same dwelling or address. More than one household may belong to the same household-dwelling unit. The concept of household-dwelling unit is used in register-based statistics in place of the household concept.

Reference person

In the income distribution statistics and in the statistics of household's assets the person with the highest personal income is chosen as the household's reference person. Personal income is defined according to register data and interview data.

Although income is the main criterion determining the reference person, in some cases (e.g. entrepreneur households) the activity of the whole household is taken into account. Households of pensioner parents with children (including those over the age of consent) are also special cases where the parent with the higher income is selected as the reference person if the combined incomes of the parents clearly exceed those of a child.

Accuracy, reliability and timeliness

Overall accuracy

Only administrative register data are used as the data sources for the annually published data on the dwelling population in the statistics on households' assets. The quality of data sources is good in statistics compilation based on a register system.

The sample data of the statistics on households' assets, from which comprehensive data on households' net wealth are published at set intervals, are based on a representative sample survey. The reliability of the sample data is essentially affected by the unit non-response due to the fact that some households refuse to or do not take part in the survey for some other reason. It can be concluded from the structure of non-response whether it has been distributed unevenly or randomly. The non-response of the survey is examined in more detail in the quality description of the income distribution statistics.

Efforts have been made to compare the results of the wealth survey by type of wealth with external sources. Some of the data are available not only as a sample but also as total data, in which case comparisons have been made with the key figures of the so-called household-dwelling population. Such data include investment funds, quoted shares, bonds and unquoted shares. Comparisons have also been made with financial accounts, asset balances and statistics on indebtedness. In the pricing of dwellings, prices per square metre have been compared with the data of the statistics on prices of dwellings and the real estate purchase price statistics. The estimates of the wealth survey can deviate significantly from the comparison sources due to differences in methodology and coverage. The data are not directly comparable with, for example, the asset balance data. Further information about the comparisons is available from Statistics Finland.


The data of the statistics on households’ assets are released approximately 18 months after the reference period.


The data of the statistics on households' assets have been published on the days indicated in the release calendar.


Comparability - geographical

Starting from 2009, Statistics Finland's wealth survey is part of the Household Finance and Consumption Survey (HFCS) for the euro area coordinated by the European Central Bank (ECB). The Household Finance and Consumption Survey coordinated by the ECB is output-harmonised. The countries participating in the survey produce predefined data contents in the manner they deem best. Participation in the survey does not require asking exactly the same questions or applying the same data collection modes. Finland stands out from other countries by using register data clearly more extensively.

In addition to data collection methods, the comparison between the countries in the euro area is affected by differences in the characteristics of the household population and the distribution of ownership of different types of assets. For example, the size distribution of households differs considerably from one country to another. One of the main phenomena behind the differences between countries is the relative share of owner-occupiers in the population. For example, in Germany and Austria fewer than 50 per cent of households live in a dwelling they own. The corresponding share is over 80 per cent in Croatia, Lithuania, Hungary, Malta and Slovakia. Further information on the comparability of the results between countries is available in the methodological report published on the ECB's web pages.

Comparability - over time

The comparability of the time series is affected by changes in concepts and research methods. The wealth concept of 2009 and 2013 is in some respects narrower than in the interview surveys of earlier years. In 2016, the wealth concept was slightly expanded in connection with savings and investment insurances. In 2009 and 2013, no data are available on savings and investment insurances, cash and outstanding loans. The method of the statistics changed significantly in 2009, because the vast majority of asset items were derived from register data or estimated. Methodological changes were made in 2016 concerning other dwellings and investment funds.

Housing wealth
There are no essential methodological changes in the determination of the value of owner-occupied dwellings between 2013, 2016 and 2019. The definition of ownership shares was revised in other dwellings in housing companies and in residential real estate in 2016, which increased the value of other dwellings in housing companies and lowered the value of other residential real estate. The corresponding revision was made retrospectively to the data for 2013.

In 1987 to 2004, data on the values of dwellings are the household's own estimates of the selling price of the dwelling. This may affect the comparability of the data especially for single-family houses.

Other debts
Since 2012, the debt register has not included continuous credits, which are, for example, credit card credits, accounts with overdraft facilities, and other credits that consumers can use continuously within the credit limits without a separate decision to grant credit from the lender. The insufficient data were supplemented in 2013, 2016 and 2019 by asking the households in the interview about their amounts of credit card, charge card, part payment and other debts. As regards these data, it was checked that there were no overlaps in the data in the interview and register debts. In 2009, debt data were obtained comprehensively from registers and the data on debts for the year in question were formed altogether from registers.

Values of free-time residences
Fewer free-time residences are obtained from register data than from interviews, which was the method used in 1987 to 2004. Thus, the data on free-time residences are not comparable between 1987 to 2004 and 2009 to 2019.

Value of transport equipment
In 2016 and 2019, driven kilometres could also be used in pricing, and they were not used in 2013. Other vehicles consist of non-taxable vehicles in the vehicle register, such as mopeds, quad bikes, snowmobiles and trailers. These have been priced separately with the help of asking prices of websites advertising vehicles for sale. Ownership of boats is based on Traficom’s watercraft register and price data on the price data of websites advertising vehicles for sale. In 2013, 2016 and 2019, car holders were included, while in 2009 only owners were included. As a result, the share of households owning a car is smaller in 2009.

Value of farm land
In 1987 to 2004, the value of farm land is not included in assets.

Deposits in the statistics on households’ assets in the statistical reference years 2013, 2016 and 2019 are based on household interview data from the third and fourth survey rounds of the interview for the income and living conditions survey in spring 2014, 2017 and 2020. The data were collected and formed divided into current accounts and savings and investment accounts. For the first and second survey rounds the data were modelled with predictive mean matching, combining the real donor method and regression model. The data for 2009 have been modelled from the 2004 data by statistical combining. The data for earlier years were collected with interviews.

Value of unquoted shares
The value of unquoted shares is not comparable between 1987 to 2004 and 2009 to 2019, because older data are based on interview data and they were nominal values.

Net wealth of business activities and groups
Net wealth of business activities is included only in the data for 2013, 2016 and 2019. The group's net wealth is included from 2009 onwards.

Investments in mutual funds
The data for 2013, 2016 an 2019 are more exhaustive than in the previous years because they include shares of foreign collective investment schemes.

Individual pension insurance
Data have been produced yearly with the perpetual inventory method starting from the statistical reference year 2009. The data for 1987 to 2004 are interview data.

Savings and investment insurances
Data are not available for 2009 and 2013.

Other financial assets
In 2016, the number of households owning participation certificates is higher than before due to yield shares of cooperative banks.

Total assets
In 2013, 2016 an 2019, the net wealth of business activities and groups are included in real assets. There are no data on the net wealth of business activities in 2009. No data are available for the years 1987 to 2004 on the value of farm land or business wealth. There are no data on the value of forests for 1987 to 2004. For this reason, separate data have been formed in the data set and statistical tables, which do not include forests, fields and business wealth. The data for 1987 and 1988 do not include other housing wealth.

Coherence - cross domain

The sample and income and background data of the wealth survey are the same as those of the income distribution statistics, so asset data also extend the content of the income distribution statistics to assets at set intervals of years. The sample is also the same as in the EU Statistics on Income and Living Conditions (EU-SILC), so the data also extend the content area of Finland's EU-SILC data.

The wealth survey is part of the ECB's Household Finance and Consumption Survey for the euro area (2009, 2013, 2016 an 2019). The concept of wealth and the classification of assets may differ from the ECB's definitions, as national statistics also aim to retain key time series.

Statistics Finland's annual statistics on indebtedness describe household-dwelling units' indebtedness. The statistics are based on total data, while the data of the wealth survey are based on a sample. The debt items derived from registers are the same in the statistics, but in the wealth survey their classification may differ (e.g. only owners of dwellings have housing loans). The wealth survey also contains supplementary interview data on debts and debt service expenses which are not included in the statistics on indebtedness. The wealth survey enables proportioning debts to assets, whereas in the statistics on indebtedness debts can only be proportioned to income.

Statistics Finland's financial accounts describe the financial assets of the sectors of the national economy at the macro level and starting from autumn 2014, data on real assets have also been published in connection with them. Due to conceptual differences and differences in definitions as well as different production methods, the estimates of total amounts of assets in the wealth survey cannot be directly compared with the household sector data of financial accounts.

Coherence - internal

Data on quoted shares and mutual funds are available on both the individual and household levels. The data concerning the individual-level dwelling population are fully based on register-based total data, while the household-level data are based on sample data (starting from 2009, data on quoted shares and mutual funds have been combined from register data to the sample). The use of fully register-based total data makes it possible to apply more detailed classifications than those of sample statistics.

Source data and data collections

Source data

Statistics Finland's wealth survey represents sample-based statistics. Most of the basic data of the survey have been collected from administrative registers, and deficiencies are covered by a supplementary interview data collection. The background data of the survey are based on both register and interview data.

A majority of the survey data derive from administrative registers and statistical registers. The register sources of the wealth survey are:
  • The Population Information System of the Digital and Population Data Services Agency and Statistics Finland’s database on the population, buildings and dwellings in Finland
  • Basic data of Statistics Finland's statistics on real estate prices, which are based on the transaction price data of the National Land Survey's register of real estate purchase prices
  • The Tax Administration's tax database, real estate register, data collected for asset transfer tax calculation purposes, book-entry securities data, price quotes of vehicles, and inheritance and gift tax data
  • Vehicle register and watercraft register (Traficom)
  • The Social Insurance Institution of Finland's registers of pension insurance, health insurance compensation and rehabilitation, registers of child maintenance allowances, financial aid for students and housing allowances
  • The National Institute for Health and Welfare's register of social assistance
  • The register of pension contingency of the Finnish Centre for Pensions
  • Statistics Finland’s Register of Completed Education and Degrees
  • The State Treasury's database on the military injuries indemnity system
  • The Education Fund's data files
  • The farm register of the Information Centre of the Ministry of Agriculture and Forestry (TIKE)
  • Statistics Finland's Business Register
  • The Financial Supervision Authority's data (earnings-related unemployment allowances)
The survey's interview data collection was an additional section in the 2019 Survey on income and living conditions in spring 2020, in which data were collected for the national income distribution statistics and the EU Statistics on Income and Living Conditions (EU-SILC). For the wealth survey, supplementary questions on debts, especially consumer credits and their payments, deposits and some relevant questions from the ECB questionnaire were added to the questionnaire. Of asset items, deposits and saving and investment insurance are based on interview data, as no register data are available on them. Debt data supplement deficiencies in register data especially as concerns so-called continuous consumer credits.

The sample in the wealth survey is the same as in the income distribution statistics. The sample is based on a rotating panel design. The households participate in the survey in four consecutive years, so the data for the statistical reference year consist of households that have been included in the sample for one to four rounds.

The sampling design is a two-phase stratified sampling. In the first phase, a so-called master sample is formed by selecting 50,000 target persons aged 16 or over by means of systematic sampling from Statistics Finland’s population database. The household-dwelling units of target persons included in the sample are formed by combining the persons living permanently at the same address with the target person with the help of the code for place of domicile. In the second phase, the actual sample for the income distribution statistics is selected from the master sample by strata. The probability of a household being included in the sample depends not only on the stratification criteria but also on the number of household members who are aged 16 or over.

The strata are created based on the tax data of the year preceding the statistical reference year. The strata are formed based on the household-dwelling unit’s income subject to state taxation and the socio-economic groups of the household members. The socio-economic groups formed based on the data from the tax register are wage and salary earners, farmers, other self-employed persons, pensioners and others. In defining the sample size by stratum, or in sample allocation, the special requirements of the income distribution survey are considered. The sampling design puts a relatively strong emphasis on persons of high income and as a result, on wealthy persons, which is an asset in the wealth survey. Entrepreneurs and those with high income have a higher probability than others of being included in the sample.

For the statistical reference year 2019, a supplementary sample was made for the sample for the first survey round, for which 500 households were drawn. An additional sample was needed, because due to the corona pandemic that started in spring 2020, the response rate for the first time was clearly lower than in the previous years. The reason for this may be not only the general fall in responsiveness, but also an interruption in trying to get face-to-face interviews from households that could not be reached by telephone because of the corona pandemic. An additional sample was selected to represent strata where the growth in non-response was particularly large and the numbers of observations were clearly lower than in the year before: self-employed persons, wage and salary earners with the lowest income and pensioners with the lowest income.

Data collection

The household-level survey data for the statistical reference years 1987, 1988, 1994, 1998 and 2004 were collected as a face-to-face interview survey. The data collection method for the years 2009, 2013, 2016 and 2019 was mainly a telephone interview (CAPI). Further information about the data collection method can be found in the documentation of the income distribution statistics.

Frequency of data collection

The data collection for the household-level survey has been carried out at three-year intervals since the statistical reference year 2013. The reference period of the register data is the last day of the statistical reference year (31 December). Interview data are collected in the survey year following the reference period. For example, the interview data for the statistical reference year 2019 were collected in early 2020.

Personal data on quoted shares and mutual funds of the dwelling population are collected annually from administrative files.


Data compilation

The variables of the supplementary data collection for the wealth survey are connected to so-called item non-response and the missing data due to this have partly been generated by imputation with statistical methods. In addition, deposit variables have been entirely imputed for households in the third and fourth survey rounds participating in the survey for the first or second time.

The general method for imputation was predictive mean matching, or the PMM method. The substitution of missing data is described in more detail below for each asset category.

Households and persons whose participation has been approved receive a weighting coefficient with which their data are raised to represent the data of the basic population. The weights are formed in the same way as in the income distribution statistics, that is, a preliminary correction for non-response by strata is made for the panel-specific design weights, and these weights are calibrated to external marginal distributions. The same data as in the income distribution statistics (weight variable YKOR) were used in calibrating the weights of the data of the 2019 wealth survey, supplemented by some asset data. The calibration data were:
  • Area (the division of regions, in which Helsinki and other parts of the Helsinki Metropolitan area are shown separately; statistical groupings of municipalities)
  • Size of municipality of residence
  • Age and gender groups of members
  • Level of education of persons aged 16 and over
  • Total sums of the main income items: wages and salaries, entrepreneurial and property income, unemployment allowances (basic unemployment allowance and labour market allowance, earnings-related share), pensions, interest on housing and student loans, number of income recipients (earnings-related unemployment allowance, wage and salary income, pension income)
  • number of persons belonging to low-income household-dwelling units in the household-dwelling population in the total statistics on income distribution (register-based income concept)
  • number of persons owning investment funds and total value of investment funds
  • number of persons owning quoted shares over the median of the population according to the conditional median, and
  • total value of quoted shares
In most cases, the only information the registers provide is that a person owns a certain asset item, after which the market value of the asset item must be established. Each asset item has its own pricing source. For example, in the pricing of dwellings in housing companies, the purchase prices of dwellings have been raised with price indices of dwellings in housing companies to the level of the statistical reference year.

Data validation

Several different register data sets and data collected during the interview are used as source data for the statistics. The sum data calculated from micro level register data are compared with macro data, such as Statistics Finland's financial accounts data or the Bank of Finland’s data. The comments recorded by the interviewer during the interview are partly examined manually. In addition, the distribution data of the key result variables, such as minimum and maximum, are checked to assess possible errors or deviating observations.

Principles and outlines

Contact organisation

Statistics Finland

Contact organisation unit

Social Statistics

Legal acts and other agreements

The compilation of statistics is guided by the Statistics Act. The Statistics Act contains provisions on collection of data, processing of data and the obligation to provide data. Besides the Statistics Act, the Data Protection Act and the Act on the Openness of Government Activities are applied to processing of data when producing statistics. 

Statistics Finland compiles statistics in line with the EU’s regulations applicable to statistics, which steer the statistical agencies of all EU Member States.  

Further information: Statistical legislation 

Confidentiality - policy

The data protection of data collected for statistical purposes is guaranteed in accordance with the requirements of the Statistics Act (280/2004), the Act on the Openness of Government Activities (621/1999), the EU's General Data Protection Regulation (EU) 2016/679 and the Data Protection Act (1050/2018). The data materials are protected at all stages of processing with the necessary physical and technical solutions. Statistics Finland has compiled detailed directions and instructions for confidential processing of the data. Employees have access only to the data essential for their duties. The premises where unit-level data are processed are not accessible to outsiders. Members of the personnel have signed a pledge of secrecy upon entering the service. Violation of data protection is punishable. 

Further information: Data protection | Statistics Finland (stat.fi

Confidentiality - data treatment

The classifications used in releases of data on the statistics on households' assets have been made less detailed so that data on individual households cannot be deduced from the tables. Changes have been made to the variables in the micro data released for research use to prevent direct identification. In the so-called production files submitted to the ECB, persons' background information (e.g. occupation, gender, age, industry) has been removed and the values of some outlying observations have been replaced with their weighted average.

Release policy

Statistics Finland publishes new statistical data at 8 am on weekdays in its web service. The release times of statistics are given in advance in the release calendar available in the web service. The data are public after they have been updated in the web service. 

Further information: Publication principles for statistics at Statistics Finland 

Data sharing

The Finnish data of the statistics on households' assets for 2019 are included in the data of the ECB’s fourth international Household Finance and Consumption Survey. 

National survey data have been formed from the basic data of the wealth survey for all years and they are released for research purposes. In addition, the ECB has formed research data also on the euro area data for researchers, and Finland's data for 2009, 2013, 2016 and 2019 are included. The data for 1998, 2009 and 2013 have also been delivered to the Luxembourg Wealth Study (LWS) database.

Accessibility and clarity

Statistical data are published as database tables in the StatFin database. The database is the primary publishing site of data, and new data are updated first there. When releasing statistical data, existing database tables can be updated with new data or completely new database tables can be published.   

In addition to statistical data published in the StatFin database, a release on the key data is usually published in the web service. If the release contains data concerning several reference periods (e.g. monthly and annual data), a review bringing together these data is published in the web service. Database tables updated at the time of publication are listed both in the release and in the review. In some cases, statistical data can also be published as mere database releases in the StatFin database. No release or review is published in connection with these database releases. 

Releases and database tables are published in three languages, in Finnish, Swedish and English. The language versions of releases may have more limited content than in Finnish.   

Information about changes in the publication schedules of releases and database tables and about corrections are given as change releases in the web service. 

Data for 2009, 2013, 2016 and 2019 are available as part of the ECB's Household Finance and Consumption Survey (HFCS) for the euro area, both in table format and as research data. Further information about these is available on the ECB's home page (Household Finance and Consumption Network).

Data revision - policy

Revisions – i.e. improvements in the accuracy of statistical data already published – are a normal feature of statistical production and result in improved quality of statistics. The principle is that statistical data are based on the best available data and information concerning the statistical phenomenon. On the other hand, the revisions are communicated as transparently as possible in advance. Advance communication ensures that the users can prepare for the data revisions. 

The reason why data in statistical releases become revised is often caused by the data becoming supplemented. Then the new, revised statistical figure is based on a wider information basis and describes the phenomenon more accurately than before. 

Revisions of statistical data may also be caused by the calculation method used, such as annual benchmarking or updating of weight structures. Changes of base years and used classifications may also cause revisions to data. 

Quality assessment

In 2010, the Advisory Board of Official Statistics of Finland updated the quality criteria for statistics that should be fulfilled by statistics in the Official Statistics of Finland series. These criteria were harmonised with the Eurostat quality criteria. The purpose of the criteria is to develop and maintain the usability of OSF statistics in order to meet society’s information needs. The OSF quality criteria can be found on Statistics Finland's web pages.

Quality assurance

Quality management requires comprehensive guidance of activities. The quality management framework of the field of statistics is the European Statistics Code of Practice (CoP). The quality criteria of Official Statistics of Finland are compatible with the European Statistics Code of Practice. 

Further information: Quality management | Statistics Finland (stat.fi) 

User access

Data are released to all users at the same time. Statistical data may only be handled at Statistics Finland and information on them may be given before release only by persons involved in the production of the statistics concerned or who need the data of the statistics concerned in their own work before the data are published. 

Further information: Publication principles for statistics 

Unless otherwise separately stated in connection with the product, data or service concerned, Statistics Finland is the producer of the data and the owner of the copyright. The terms of use for statistical data. 

Statistical experts

Tara Junes
Senior Statistician
029 551 3322

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