 An intelligent multi-level optimisation model for retail loan portfolioSrilatha Kappagantula and Vikas Srivastava International Journal of Indian Culture and Business Management, 2024, vol. 32, issue 2, 164-186 Abstract: The paper discusses the multi-level portfolio selection problem, which combines hierarchical optimisation of credit portfolio, incorporating regulatory and capital constraints, in the context of emerging retail-banking loans. The proposed model allows for twin objectives of risk minimisation, simultaneously providing scope for maximising returns. The present paper analyses the portfolio optimisation problem, as a holistic 2-level optimisation problem: 1) at loan level, to reduce the default risk; 2) at bank level, to decide the right capital allocation between loan classes. The current study develops a model for multi-level optimisation of loans, and solves the model using multi objective algorithm for allocation of loan data across four retail asset classes, namely small business loans, credit card loans, home loans and auto loans, using a dataset of 229,000 loan records. The multi-level optimised portfolio is compared against the original portfolio for potential gains. Keywords: banking; portfolio optimisation; portfolio allocation; portfolio selection; retail banking; machine learning; artificial intelligence; AI. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ids:ijicbm:v:32:y:2024:i:2:p:164-186 Access Statistics for this article More articles in International Journal of Indian Culture and Business Management from Inderscience Enterprises Ltd |
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