Claim · 2022-10-11 · publication · Stated in source · Supported

The Bank of England (including the PRA) and the Financial Conduct Authority state in Discussion Paper DP5/22 of 11 October 2022 that AI models may become correlated in subtle ways and add to risks of herding or procyclical behaviour in market stress, and that uniformity across firms’ models could amplify procyclical behaviour.

One recorded claim. The claim panel gives its qualification, the source passages with their place in each source, and how it was checked.

What it connects

DP5/22 - Artificial Intelligence and Machine Learning → articulates → AI raises financial-stability risks through correlated behaviour

Where it appears

AI and money: what central banks and financial authorities have said, 1997–2026 →

Claim and evidence

DP5/22 - Artificial Intelligence and Machine Learningarticulates ↓AI raises financial-stability risks through correlated behaviour

Machine-checkedStated in sourceSupported

Supporting evidence: primary · 1 source

Date: 2022-10-11 · publication Records dated 2022 →
Role: Articulation
Register (kind of text): Nonfiction

Scope and limitsA discussion paper inviting responses; it states possible risks and does not record that herding from AI has occurred or adopt a policy.

The evidence 02

primary sourceSupports the claim

DP5/22 - Artificial Intelligence and Machine Learning

Bank of England · 2022-10-11

Cite the original source

Cite the original document, not Selekoa. Check these details against it.

Source excerpt

“models may become correlated in subtle ways and add to risks of herding, or procyclical behaviour at times of market stress.”

Location in source Executive summary, “Financial markets”

How it was read Retrieved directly from the publisher

Machine-checked · 2026-11-06

Source details and check notes

Authors: Bank of England (including the PRA) and Financial Conduct Authority
Version: Retrieved for the candidate pack on 2026-11-02 (SHA-256 657c63bd007f934dc9a66a2b843a838fe60a939d3c66f69357460cef64fafd2f). Retrieved again at admission on 2026-11-06 (SHA-256 fabde4a2e27cacea27129ee7c9c635c6bb0196ea3313c6dfd79a89f88565076d; web pages are served with new markup on each request). HTML of the discussion paper page as served on 2026-11-02
Canonical address: Open the canonical source ↗
Accessed: 2026-11-06
Language: English (en)
Attribution: Bank of England (including the PRA) and Financial Conduct Authority, “DP5/22 - Artificial Intelligence and Machine Learning”, 2022-10-11.
Reuse: No open redistribution licence asserted. Bibliographic metadata, editorial paraphrases and short attributed quotations (at most 50 words each). Recheck terms before wider redistribution.
Check notes: Candidate pack passage, AI and money (research/ai-money). The quotation (21 words) matched a fresh retrieval of 2026-11-06. Matching ignored differences of whitespace, case, quotation marks, dashes, line-break hyphens and Unicode compatibility forms. No human editorial review.

primary sourceSupports the claim

DP5/22 - Artificial Intelligence and Machine Learning

Bank of England · 2022-10-11

Cite the original source

Cite the original document, not Selekoa. Check these details against it.

Source excerpt

“algorithms may result in uniformity across models and approaches at multiple firms, which could amplify procyclical behaviour and lead to herding in certain use cases, such as algorithmic trading.”

Location in source Chapter 3, para 3.22

How it was read Retrieved directly from the publisher

Machine-checked · 2026-11-06

Source details and check notes

Authors: Bank of England (including the PRA) and Financial Conduct Authority
Version: Retrieved for the candidate pack on 2026-11-02 (SHA-256 657c63bd007f934dc9a66a2b843a838fe60a939d3c66f69357460cef64fafd2f). Retrieved again at admission on 2026-11-06 (SHA-256 fabde4a2e27cacea27129ee7c9c635c6bb0196ea3313c6dfd79a89f88565076d; web pages are served with new markup on each request). HTML of the discussion paper page as served on 2026-11-02
Canonical address: Open the canonical source ↗
Accessed: 2026-11-06
Language: English (en)
Attribution: Bank of England (including the PRA) and Financial Conduct Authority, “DP5/22 - Artificial Intelligence and Machine Learning”, 2022-10-11.
Reuse: No open redistribution licence asserted. Bibliographic metadata, editorial paraphrases and short attributed quotations (at most 50 words each). Recheck terms before wider redistribution.
Check notes: Candidate pack passage, AI and money (research/ai-money). The quotation (29 words) matched a fresh retrieval of 2026-11-06. Matching ignored differences of whitespace, case, quotation marks, dashes, line-break hyphens and Unicode compatibility forms. No human editorial review.

Status and meaning

Editorial status. Machine-checked. Machines found this record and checked it against its sources; no person accepted it individually. Each evidence record above shows how it was checked.

Relation. A passage of the document meets the proposition’s criterion. The record documents what the text states, in its register (fiction and satire are labelled); it is not evidence that the proposition is true and implies no influence on or from another text.

Date. Date of publication, as the text gives it.

Record ID am-u01-boe-2022-dp5-22