The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Believing the Bot - Model Risk in the Era of Deep Learning
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“As discussed by Richman, Rummell, and Wuthrich (2019), machine learning models are often more complex and less transparent than traditional models.”
From The Discriminating (Pricing) Actuary (2023) · cites this paper as Richman, Rummell, and Wuthrich (2019)
Citations
Cites
The perceptron: A probabilistic model for information storage and organization in the brain.
Rosenblatt, F. (1958) · Psychological Review · doi:10.1037/h0042519 · Cited by 12,280
Cited by
Sorted by citations
The Discriminating (Pricing) Actuary
Frees, E. W. (., & Huang, F. (2023) · North American Actuarial Journal · doi:10.1080/10920277.2021.1951296 · Cited by 56
From bias to black boxes: understanding and managing the risks of AI – an actuarial perspective
du Preez, V., Bennet, S., Byrne, M., Couloumy, A., Das, A., Dessain, J., Galbraith, R., King, P., Mutanga, V., Schiller, F., et al. (2024) · British Actuarial Journal · doi:10.1017/s1357321724000060 · Cited by 15
Metadata
- Authors
- Richman, R., von Rummell, N., & Wuthrich, M. V.
- Venue
- SSRN Electronic Journal
- Publisher
- Elsevier BV
- Published
- 2019
- ISSN
- 1556-5068
- Cited by
- 10
- References
- 1
- Language
- en
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Believing the Bot - Model Risk in the Era of Deep Learning. https://app.cochat.ai/papers/10.2139/ssrn.3444833
- The paper
- Richman, R., von Rummell, N., & Wuthrich, M. V. (2019). Believing the Bot - Model Risk in the Era of Deep Learning. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3444833
