Human beings are quite complex. Every individual is different and various set of parameters need to be evaluated according to the background of the person in order to prepare a profile of any particular individual. However, some patterns emerge and equipped with machine learning some predictions can be construed. This paper presents profiling of candidates applying for Home Loans using various machine learning algorithms and techniques. This will enable bank officials to better understand their customers, thereby reducing the ratio of loan defaults. The myriad of data present with the bank which relate to past records of home loan candidates have been used by the machine learning algorithm in order to learn and produce a profiling output. Candidates are then placed into categories and a further investigation can be carried out depending on which category a candidate is allocated to.
