Insuring Algorithmic Operations: Liability Risk, Pricing, and Risk Control
Identification
- Public canonical key
- doi:10.3390/risks14020026
- Authors
- Zhiyong Liu · Se Jin Park · Mengying Wang · He Wen
- Reported year
- 2026
- Reported language
- en
- Source type
- article
- First detected
- 2026-11-09T19:04:47.786945+00:00
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- 2026-11-09T19:04:47.786945+00:00
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Indiana State University
Reported affiliation countries
US
Documentary abstract — original language
Businesses increasingly rely on algorithmic systems and machine learning models to make operational decisions about customers, employees, and counterparties. These “algorithmic operations” can improve efficiency but also concentrate liability in a small number of technically complex, drifting models. Algorithmic operations liability (AOL) risk arises when these systems generate legally cognizable harm. We develop a simple taxonomy of AOL risk sources: model error and bias, data quality failures, distribution shift and concept drift, miscalibration, machine learning operations (MLOps) and integration failures, governance gaps, and ecosystem-level externalities. Building on this taxonomy, we outline a simple analysis of AOL risk pricing using some basic actuarial building blocks: (i) a confusion-matrix-based expected-loss model for false positives and false negatives; (ii) drift-adjusted error rates and stress scenarios; and (iii) credibility-weighted rates when insureds have limited experience data. We then introduce capital and loss surcharges that incorporate distributional uncertainty and tail risk. Finally, we link the framework to AOL risk controls by identifying governance, documentation, model-monitoring, and MLOps practices that both reduce loss frequency and severity and serve as underwriting prerequisites.
Identifiers
- OPENALEX
- W7126378148
- DOI
- 10.3390/risks14020026
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- article
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OpenAlex · Record 1 · Record 2
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Cite this reference
Zhiyong Liu; Se Jin Park; Mengying Wang; He Wen. Insuring Algorithmic Operations: Liability Risk, Pricing, and Risk Control. 2026. https://doi.org/10.3390/risks14020026
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- APA
- Zhiyong Liu; Se Jin Park; Mengying Wang; He Wen. (2026). Insuring Algorithmic Operations: Liability Risk, Pricing, and Risk Control. https://doi.org/10.3390/risks14020026
- Chicago
- Zhiyong Liu; Se Jin Park; Mengying Wang; He Wen. Insuring Algorithmic Operations: Liability Risk, Pricing, and Risk Control. 2026. https://doi.org/10.3390/risks14020026
- ISO 690
- Zhiyong Liu; Se Jin Park; Mengying Wang; He Wen. Insuring Algorithmic Operations: Liability Risk, Pricing, and Risk Control. 2026. https://doi.org/10.3390/risks14020026
UDTR Global Rights of Nature Legal Library. Insuring Algorithmic Operations: Liability Risk, Pricing, and Risk Control. Documentary record: https://www.declarationuniverselledesdroitsdelarbre.org/global-rights-of-nature-radar/reference/r-796c6da7d07299b5a5b55cf8f4e8cf72/ · Last HTTP verification: not performed
Field provenance and record version
Version de370bd3ea7a4b5c · udtr-reference-1.1.2
- Title
- OpenAlex · source · 2026-11-09T19:04:47.786945+00:00
- Authors
- OpenAlex · source · 2026-11-09T19:04:47.786945+00:00
- Year
- OpenAlex · source · 2026-11-09T19:04:47.786945+00:00
- Identifiers
- OpenAlex · source · 2026-11-09T19:04:47.786945+00:00
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- OpenAlex · source · 2026-11-09T19:04:47.786945+00:00
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50000c619d42b764 · 2026-11-09T19:04:47.786945+00:00
ec890c51a2a17f05 · 2026-11-09T19:04:47.786945+00:00
abb503c9d6086372 · 2026-11-09T19:04:47.786945+00:00
de370bd3ea7a4b5c · 2026-11-09T19:04:47.786945+00:00
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Discovery source · https://doi.org/10.3390/risks14020026
Discovery source · https://openalex.org/W7126378148
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