Predicting Credit Deterioration: Internal Default Models versus Lending Rates

Anders Kärnä () and Karin Östling Svensson
Additional contact information
Anders Kärnä: Financial Stability Department, Central Bank of Sweden, Postal: Research Institute of Industrial Economics (IFN)
Karin Östling Svensson: Financial Stability Department, Central Bank of Sweden, Postal: Sveriges Riksbank, SE-103 37 Stockholm, Sweden

No 458, Working Paper Series from Sveriges Riksbank (Central Bank of Sweden)

Abstract: This paper examines how accurately Swedish banks’ internal probability of default (PD) models under IFRS 9 accounting rules predict changes in the borrowing firms’ credit risk levels. Using a sample of matched bank lending and firm-level data, we find that PDs align well with aggregate transitions to an elevated risk level, but explain little of the variation across individual borrowers. Lending rates, in contrast, provide limited information on moderate distress levels but are more predictive of severe credit events. The findings suggest that PDs capture both risk assessment and accounting conventions in a non-linear and complex pattern, highlighting the importance of combining regulatory and market-based indicators when monitoring credit risk.

Keywords: Probability of Default; Bankruptcy; Financial Distress (search for similar items in EconPapers)
JEL-codes: G33 L25 (search for similar items in EconPapers)
Pages: 38 pages
Date: 2025-12-01
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.riksbank.se/globalassets/media/rapport ... us-lending-rates.pdf Full text (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hhs:rbnkwp:0458

Access Statistics for this paper

More papers in Working Paper Series from Sveriges Riksbank (Central Bank of Sweden) Sveriges Riksbank, SE-103 37 Stockholm, Sweden. Contact information at EDIRC.
Bibliographic data for series maintained by Lena Löfgren ().