Claim · 2019-06-30 · publication · Stated in source · Supported

The BIS Annual Economic Report 2019 (chapter III) states in an endnote that complex and opaque algorithms render biases in machine-learning credit scoring particularly difficult to detect and therefore to prevent.

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

III. Big tech in finance: opportunities and risks → bears on → The opacity of AI models complicates risk management and supervision

Where it appears

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

Claim and evidence

III. Big tech in finance: opportunities and risksbears on ↓The opacity of AI models complicates risk management and supervision

Machine-checkedStated in sourceSupported

Supporting evidence: primary · 1 source

Date: 2019-06-30 · publication Records dated 2019 →
Role: Context
Register (kind of text): Nonfiction
Missing element: Does not say whose task (firms’ risk management or supervisors’ assessment) the opacity makes harder; the passage concerns detecting discriminatory bias in big tech algorithms.

Scope and limitsAn endnote to a chapter on big tech in finance.

The evidence 01

primary sourceSupports the claim

III. Big tech in finance: opportunities and risks

Bank for International Settlements · 2019-06-30

Cite the original source

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

Source excerpt

“The complex and opaque algorithms render biases particularly difficult to detect, and therefore to prevent.”

Location in source Endnote 16

How it was read Retrieved directly from the publisher

Machine-checked · 2026-11-06

Source details and check notes

Authors: Bank for International Settlements
Version: Retrieved for the candidate pack on 2026-11-02 (SHA-256 d54cb638f14d3782de1deb6db86275cbcbb98228ebda50609dd5b09ffe4899ac). Retrieved again at admission on 2026-11-06 (same file). BIS HTML chapter as served on 2026-11-02 (requested at https://www.bis.org/publ/arpdf/ar2019e3.htm, redirected)
Canonical address: Open the canonical source ↗
Accessed: 2026-11-06
Language: English (en)
Attribution: Bank for International Settlements, “III. Big tech in finance: opportunities and risks”, 2019-06-30.
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 (15 words) matched a fresh retrieval of 2026-11-06 (the same file the candidate pack read). 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 bears on the proposition without meeting its criterion; the record names the missing element. It is not an articulation and implies no influence.

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

Record ID am-u04-bis-2019-aer-ch3