DISCRIMINATIVE ABILITY IN ESTIMATING PROBABILITY OF DEFAULT WITH CERTAIN MACHINE LEARNING ALGORITHMS

Authors

Keywords
probability of default, machine learning, risk assessment, credit risk

The article highlights the importance and added value of some machine learning algorithms in assessing default probability. The results of the research highlight the discriminative ability added to many other essential aspects of machine learning in assessing credit risk. These aspects can be identified as specific opportunities and challenges. As for the discriminative ability regarding the analysed sample, the results prove the superiority of machine learning over the traditionally established and known models. For individual business organizations with exposures to credit risk, machine learning could contribute to reducing the credit losses with larger volumes of business transactions.

JEL: Â23, C58, G32
Pages: 12
Price: 2 Points

More titles

  • ON SOCIAL REALITY, THEORY AND ECONOMICS EDUCATION

    The article is an attempt to defend the based on the Seneca’s maxim thesis that the present is to fix the past and foresee the future. Employing a broader socio-economic paradigm, it analyses the essence of societal reality and economic reality in particular; the dominance of economic considerations surpassed by time and the necessity for a more ...

  • POSSIBILITIES FOR OVERCOMING ISSUES IN THE PHASE OF OLD-AGE PENSION PAYMENTS FROM AN UNIVERSAL PENSION FUND

    The structuring of the pension model, the exploration of its characteristics and parameters, as well as of pension products, their role, and the potential to ensure long-term social security in an environment marked by socio-economic and demographic challenges, is a significant and relevant thematic area. The focus of the study is on presenting ...

  • INTELLECTUAL CAPITAL AND MARKET CAPITALIZATION OF PUBLIC COMPANIES

    Value creation is the main goal of economic agents operating in capital markets. The subject of research are the intangible fixed assets reflecting the intellectual capital of companies. The object of the article are some current issues regarding the assessment of the influence of intellectual capital on the stock market capitalization of public ...