Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 176

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Credit risk measurement and procyclicality

Open access
Lowe, Philip·2003·Banking Supervision at the Crossroads

Abstract

This paper examines the two-way linkages between credit risk measurement and the macroeconomy. It first discusses the issue of whether credit risk is low or high in economic booms. It then reviews how macroeconomic considerations are incorporated into credit risk models and the risk measurement approach that underlies the New Basel Capital Accord. Finally, it asks what effect these measurement approaches are likely to have on the macroeconomy, particularly through their role in influencing the level of bank capital. The paper argues that much remains to be done in integrating macroeconomic considerations into risk measurement, particularly during the upswing of business cycles that are characterised by rapid increases in credit and asset prices. It also suggests that a system of risk-based capital requirements is likely to deliver large changes in minimum requirements over the business cycle, particularly if risk measurement is based on market prices. This has the potential to increase the financial amplification of business cycles, although other aspects of risk-based capital requirements are likely to work in the other direction. Further work on evaluating the net effects is important for both supervisory and monetary authorities.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.4337/9781781950531.00019

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 1 references

Cited by

See all 176

Metadata

Authors
Lowe, P.
Venue
Banking Supervision at the Crossroads
Published
2003-11-26
OpenAlex
W1536402420
Cited by
176
References
1
FWCI
42.17
Type
book chapter
Language
en
Open access
bronze

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 ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Credit risk measurement and procyclicality. https://app.cochat.ai/papers/10.4337/9781781950531.00019
The paper
Lowe, P. (2003). Credit risk measurement and procyclicality. Banking Supervision at the Crossroads. https://doi.org/10.4337/9781781950531.00019

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.