A new approach to rating scale definition with quantum-inspired optimization
Fuente:
arXiv
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| Autori principali: | , , , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| Soggetti: | |
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| _version_ | 1866918413361741824 |
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| author | Spada, Patrizio Cappelli, Laura Cibrario, Francesca Mattia, Christian Magnaldi, Daniele Argenton, Matteo Calore, Enrico Schifano, Sebastiano Fabio Bozzi, Concezio Corbelletto, Davide |
| author_facet | Spada, Patrizio Cappelli, Laura Cibrario, Francesca Mattia, Christian Magnaldi, Daniele Argenton, Matteo Calore, Enrico Schifano, Sebastiano Fabio Bozzi, Concezio Corbelletto, Davide |
| contents | In finance, assessing the creditworthiness of loan applicants requires lenders to cluster borrowers using rating scales. Financial institutions must define the scales in compliance with strict institutional constraints, resulting in solving a complex combinatorial constrained optimization problem. This contribution studies how to solve this problem using a Quadratic Unconstrained Binary Optimization (QUBO) model, a formulation suitable for quantum hardware. We validate this approach by testing the proposed formulation with classical heuristics. We then benchmark the results against a brute-force method to demonstrate consistent solution quality and highlight the framework's suitability for more complex scenarios. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_26583 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | A new approach to rating scale definition with quantum-inspired optimization Spada, Patrizio Cappelli, Laura Cibrario, Francesca Mattia, Christian Magnaldi, Daniele Argenton, Matteo Calore, Enrico Schifano, Sebastiano Fabio Bozzi, Concezio Corbelletto, Davide Emerging Technologies In finance, assessing the creditworthiness of loan applicants requires lenders to cluster borrowers using rating scales. Financial institutions must define the scales in compliance with strict institutional constraints, resulting in solving a complex combinatorial constrained optimization problem. This contribution studies how to solve this problem using a Quadratic Unconstrained Binary Optimization (QUBO) model, a formulation suitable for quantum hardware. We validate this approach by testing the proposed formulation with classical heuristics. We then benchmark the results against a brute-force method to demonstrate consistent solution quality and highlight the framework's suitability for more complex scenarios. |
| title | A new approach to rating scale definition with quantum-inspired optimization |
| topic | Emerging Technologies |
| url | https://arxiv.org/abs/2603.26583 |