Post-Hoc Macroeconomic Adjustment of IFRS 9 Probability of Default Estimates: An Exploratory Study of Norion Bank’s Swedish Unsecured-Loan Portfolio
Publicerad
Författare
Typ
Examensarbete för masterexamen
Master's Thesis
Master's Thesis
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
This thesis examines whether post-hoc macroeconomic adjustments can explain
- and potentially reduce - the spread between Observed 12-month Default rates
(OD12m) and the Probability of Default estimates-model (PD12m) used by Norion
bank for unsecured consumer loans in Sweden. The analysis cover June 2019 to
February 2024, and consists of individual contracts that are aggregated to monthlyaverages,
a total of 56 months. We analyse the total portfolio in its entirety, as well
as segmented on borrower characteristics like age, mortgage status, and co-borrower.
A Linear Regression model using ordinary least square (OLS) is employed to estimate
the spread, defined as the difference between realized OD12m and predicted
PD12m. Correlation filtering, ElasticNet regularization, VIF screening, are used as
feature selection techniques. Where autocorrelation is detected in the residuals, a
Cochrane-Orcutt AR(1) correction is optionally introduced. The model is assessed
using standard metrics like MAE, R2, adjusted R2, and residual diagnostics.
For the total portfolio, three macro variables—a 24-month change in the tradeweighted
krona (KIX), a 6-month change in household confidence, and a 12-month
change in unemployment - explains the spread. While out-of-sample test errors remain
low, MAE comparison reveals overfitting. Segment analysis shows that models
for young borrowers, older borrowers, and non-mortgage holders capture the patterns
of observed spread, whereas middle-aged borrowers, mortgage holders, and
single borrowers exhibit severe overfitting and unstable macroeconomic relationships.
The results indicate that linear macroeconomic overlays can add interpretive value
and support PD12m-model monitoring, but they are not yet stable enough for direct
IFRS 9 adjustments. Key limitations include the short time series, structural
changes in the macroeconomic landscape around COVID-19 time, and potential
macro leakage already embedded in borrower-level PD12m-models . Future research
can explore non-linear models, rolling training windows, and direct macroeconomic
integration into PD12m estimation.
Beskrivning
Ämne/nyckelord
Credit risk, IFRS 9, probability of default, expected credit loss, macroeconomic adjustment, regression, time series, segmentation, residual diagnostics, model validation