Modelling probability of default and optimal PTI level by using a household survey

Abstract

The risks of household lending are still a major issue in Hungarian banking. The proportion of nonperforming loans is rising continuously. We constructed a model to fi nd those factors which have signifi cant effect on the probability of default of households' mortgages. We also used this model to calibrate the optimal level of household mortgages' payment-to-income ratios, which is important from a regulatory point of view. Our results show that the denomination of the loan and the indebtedness of the household are crucial factors in the performance of the loan. We also show that loans contracted via agents are riskier than others. The results carry two important messages from a regulatory perspective. Prescribing the same payment-to-income (PTI) ratios for HUF and FX loans may be unnecessarily restrictive for the former and excessively permissive for the latter. The uniform regulation of households with different income levels may also lead to undesired anomalies. JEL classifi cation indices: E58, G01, G21Keywords: FX lending, probability of default, payment-to-income ratio, bank regulation *We are grateful to the two anonymous reviewers for their valuable comments and suggestions.

Overdue Debts and Financial Exclusion

“…The question may arise as to whether the coefficients shown above also represent a direction of causality. Due to overdue debts, employment is lower or vice versa, and due to the lack of declared work, repayment is more difficult and therefore the probability of overdue debts will be higher (Ben-Galim and Lanning 2010;Balás et al 2015;Campbell and Cocco 2015;Dimitrios et al 2016). In the above model, we account for a number of explanatory variables affecting both overdue debts and employment, but it is worth considering what other potential confounding variables may be omitted from the analysis.…”

“…It is well-documented in the literature that employment is an important factor in repaying household loans. If someone loses their job, the probability of non-payment increases significantly (Ben-Galim and Lanning 2010;Balás et al 2015;Campbell and Cocco 2015;Dimitrios et al 2016). Some recent papers recognized, however, that there is reverse causality, too, as overdue debts have a negative effect on employment as well.…”

Adjustable-rate mortgages in the era of global reflation: How to model additional default risk?

“…In the Bank of England’s model, a 1% change in the mortgage income gearing caused a 0.3 percentage point change in the arrears rate [ 28 ]. Balás et al [ 34 ] analyzed the factors affecting the probability of default (PD) empirically and they found a strong relationship, too. A change of 1 percentage point in the payment-to-income ratio caused a 0.76 percentage point increase in the default rate.…”

Spatializing the future: financial expectations, EU convergence and the Eastern European Forex mortgage crisis

“…By 2010, the total value of home mortgages rose fourfold (Schepp & Pitz, 2012), due almost exclusively to Forex mortgages ( Figure 1). By 2011, 15.2 per cent of households had a mortgage and an additional 3.9 per cent a home equity loan (KSH, 2011), with 55 per cent of the former and 82 per cent of the latter denominated in foreign currency (Balas et al, 2015). A total of 88 per cent of Forex mortgages were denominated in Swiss francs (authors' calculation based on data from MNB, 2011).…”