Abstract: Systems and methods of generating rating indicators for a portfolio of financial assets are described. A machine learning model is trained using a training data set that includes one or more qualitative features and one or more first quantitative features to generate an output predictor of the performance of the portfolio. The qualitative features are converted into quantitative features before being used as input to the machine learning model. Input features are generated for a new portfolio of financial assets whose rating indicator is to be generated, and fed into the trained machine learning model to generate a new output predictor for the new portfolio of financial assets. The rating indicator for the new portfolio of financial assets is determined based at least on the generated new output predictor.

Abstract: Systems and methods of generating rating indicators for a portfolio of financial assets are described. A machine learning model is trained using a training data set that includes one or more qualitative features and one or more first quantitative features to generate an output predictor of the performance of the portfolio. The qualitative features are converted into quantitative features before being used as input to the machine learning model. Input features are generated for a new portfolio of financial assets whose rating indicator is to be generated, and fed into the trained machine learning model to generate a new output predictor for the new portfolio of financial assets. The rating indicator for the new portfolio of financial assets is determined based at least on the generated new output predictor.