Property valuation evolved from simple empirical judgements to automated valuation models and their application have extended from single property to mass valuation. Many governments across the world have used AVMs to get a valuation in thousands of properties for tax related purposes. The literature review is extensive and it is growing day by day. The island of Cyprus was introduced to computer assistant mass appraisal (CAMA) in 2013 when the Department of Land and Surveys (DLS) performed a general valuation and then to revaluation in 2018. The aim of this research is to provide more transparency to the reliability of the data used in the latest general valuation. An automated valuation model was developed, using the MRA method and Hedonic Pricing Model, to test the performance of the data and compare them with the minimum standards a valuation model should have according to the International Association of Assessing Officers (IAAO). A case study using a holdout sample with data from Lakatamia Municipality was created to observe the reliability of the data but also to improve the accuracy of the Automatic Valuation Model. Three regressions were carried out: a) Basic regression with 503 observations and 10 variables, b) Regression with the previous variables plus 10 nearest neighbors as predictors and c) Regression with the previous variables plus 10 nearest neighbors as predictors, with 450 best observations – deleted outliers based on absolute error. The coefficient of determination (R-squared) measures the goodness of fit of the regression line, in other words, how close the data are to the estimated line. Initially the R-squared was 0.319 which is above IAAO standards but it was increased to 0.765 after the application of the third model. This accuracy showing better performance than the mass valuation system applied by the Department of Land and Surveys in Cyprus with accuracy of 0.384 Concluding the research ends with a critical discussion about the reliability of the data and some suggestions that could be applied by the DLS to improve the performance of the data. It is worth mentioning that the Cypriot data have a limitation due to the high heterogeneity found between properties.
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