Credit Rating Model

Student Name: T.Kamal Kanth

In this project an unsupervised learning technique was implemented to understand the process of bond ratings provided by rating agencies like CRISIL, ICRA or CARE. Again the standard financial ratios were used as the indicators or independent variables for ratings. However the ratings by a rating agency were not used for their modeling, unlike other studies conducted on similar topic under my supervision. Instead here the objective was to discover the kind of rating a class of companies with like financial ratios should get, from the available data. Towards this end, a cluster analysis of financial ratios of manufacturing firms was conducted, and significant difference between the mean vectors of the proposed clusters were confirmed using MANOVA. Then the CRISIL and ICRA ratings of the firms falling in the same cluster were observed and a remarkable consistency was found to exist between these rating agency ratings and the formed clusters. This in a way validated and established a new relationship between ratings of rating agencies and financial ratios, apart from providing an alternative new framework and model of predicting or providing a rating.