Tekstbaseret machine learning forbedrer konkursmodellering
Report published by the Danmarks Nationalbank as its own text. Dated 2019-01-21.
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- Tekstbaseret machine learning forbedrer konkursmodellering Danmarks Nationalbank · published 2019-01-21 · Retrieved for the candidate pack on 2026-11-04 (SHA-256 ea65818567557cfdae8889c3bd5af7d5639c52bf594a5f1cfce99bc8c00162e3). Retrieved again at admission on 2026-11-06 (SHA-256 35c24c3da59b74cbed3653607cd84784d90a8388b40b7d78d17d31e23fd12f18; web pages are served with new markup on each request). HTML landing page of the Analysis as served on 2026-11-04 (Danish; its summary paragraph); the PDF is source dn-2019-text-ml-bankruptcy-pdf · In Danish (da)
- Tekstbaseret machine learning forbedrer konkursmodellering (Analyse nr. 3, PDF) Danmarks Nationalbank · published 2019-01-21 · Retrieved for the candidate pack on 2026-11-04 (SHA-256 c9522edff1ce7caa7d691c8d3b107b3381879f2d9203280a2165e14021586f66). Retrieved again at admission on 2026-11-06 (same file). PDF of the Analysis (seven pages) as served on 2026-11-04; located by a second check by a model of another family; the same SHA-256 as its copy · In Danish (da)
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- AI can improve nowcasting and policy analysisDanmarks Nationalbank’s Analysis of 21 January 2019 on text-based machine learning and bankruptcy modelling states, in its summary, that machine-learning methods make data modelling more flexible and allow unstructured data to be used, and that using them to include auditors’ remarks and management reports substantially increases the accuracy of calculated bankruptcy probabilities.2019-01-21 · publication · Stated in source · Supported Inspect claim & evidence ↗AI can improve nowcasting and policy analysis: propositions page →
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