As part of its services, the Mohammed Bin Rashid Housing Establishment allows citizens to apply for a housing loan or grant. A citizen’s income is the primary criterion for approving a housing loan or grant. Typically, citizens with an income lower than a pre-determined threshold are eligible for a grant, while those with an income higher than the threshold qualify for a loan. In this paper, to enhance customer experience and improve the quality of services provided to the citizens, we propose a multilevel profiling method to determine if the received application requires special consideration. Additionally, the proposed method can be used as a supportive tool to automate determining the income threshold and grant/ loan amount. The proposed method consists of two stages. In the first stage, an outlier detection mechanism is employed to analyze the newly received application. By performing such analysis, this stage aims to determine if the received application requires further evaluation. The second stage works by utilizing the available information about the housing market to determine if the income threshold and/or the financial support amount should be revisited. We have performed several experiments to evaluate the performance of the presented method, and the results show that the proposed method achieves an average of 95% accuracy.