German mortgage banks face an increasingly regulatory framework for real estate valuations. The introduction of this framework had two effects. It has made the approval for low value properties such as apartments more time consuming and hence costly, but at the same time it allows to build a more consistent and improved data base for analysis. Lending institutions will be looking to find solutions to decrease the additional costs these regulations have caused. A possibility could be the development of a model that is projecting lending values based on a set of valuation parameters, which are supplied for a loan application. In this paper a sample set of valuation parameters of apartments for a regional sub-market is used to build the model. The dataset will be employed in a range of statistical tests, which will include tests of publicly available data in order to identify outliers. The timeframe of the dataset was chosen to exclude any behavioural shifts in the market. Such an approach to valuation obviously only lends itself to a relatively homogenous real estate class such as apartments. However, if a relationship between the valuation parameters and the lending value can be established this result will enable lending institutions to be more cost efficient in their approval process for this asset class.